Climate change and the New Zealand marine environment · Climate change and the New Zealand marine environment 1 1. Introduction 1.1 Preamble This report forms a summary of the likely

Climate change and the New Zealand marine environment

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NIWA Client Report: NEL2007-025 October 2007 NIWA Project: DOC08305

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Climate change and the New Zealand marine environment T.J. Willis* S.J. Handley F.H. Chang C.S. Law D.J. Morrisey A.B. Mullan M. Pinkerton K.L. Rodgers P.J.H. Sutton A. Tait

Prepared for

Department of Conservation

NIWA Client Report: NEL2007- 025 October 2007 NIWA Project: DOC08305

*Trevor J. Willis National Institute of Water & Atmospheric Research Ltd Email: [email protected] 217 Akersten St, Port Nelson P O Box 893, Nelson, New Zealand Phone +64-3-548 1715, Fax +64-3-548 1716 www.niwa.co.nz

Contents Executive Summary iv

1. Introduction 1 1.1 Preamble 1 1.2 New Zealand’s ocean in a warming world. 1 1.3 Current work to update these scenarios 5

2. Sea level rise 6 2.1 Projected effects 7 2.2 Vulnerable habitats and species 8 2.2.1 Estuaries and wetlands 8 2.2.2 Mangroves 9 2.2.3 Rocky intertidal habitats 10 2.2.4 Shallow subtidal reefs 11 2.2.5 Open coast sand beaches 12

3. Wind and rainfall patterns 12 3.1 Projected effects 14 3.2 Vulnerable habitats and species 14 3.2.1 Estuaries and soft sediment communities 14 3.2.2 Mangroves 15 3.2.3 Subtidal rocky reefs 15 3.2.4 Intertidal coastlines, animals and seabirds 16

4. Ocean acidification 17 4.1 Projected effects 17 4.2 Vulnerable habitats and species 18

5. Current patterns and ocean warming 23 5.1 Projected effects 25 5.2 Vulnerable habitats and species 28

6. Indirect effects 29 6.1 Primary production 29 6.1.1 Carrying capacity 29 6.1.2 Primary production around New Zealand 29 6.1.3 Global primary production 30 6.1.4 General conclusions 32 6.2 Algal blooms 33 6.2.1 Observations of short-term ‘climate change’ on algal blooms 33 6.2.2 Projected climate effects on algal blooms in New Zealand 36

6.3 Vulnerability to invasive species 37 6.4 Vulnerability to disease and parasites 38

7. Potential indicators 38 7.1 Sea level 39 7.2 Wind and rainfall 39 7.3 CO2 and acidification 40 7.4 Ocean warming and currents 41

8. Research gaps and priorities 41 8.1 Summary of future work needed to improve climate modelling

predictions at varying spatial and temporal scales 41 8.2 Ocean warming and currents 43 8.2.1 Models 43 8.2.2 Observations 43

8.3 Mitigation of anthropogenic impacts to build resilience to climate change 44

8.4 Prediction of the effects of climate change – key questions 46

9. Conclusions 49

10. Acknowledgements 53

11. References 54

12. Appendix 1: Projected climate change over the New Zealand landmass 76

Reviewed by: A.B. MacDiarmid Approved for release by Don

Robertson:

Climate change and the New Zealand marine environment iv

Executive Summary

The Intergovernmental Panel on Climate Change (IPCC) released its Fourth Assessment Report in

2007, which updates previous efforts to predict the effects of climate changes at a global level. The

documents forming that assessment provide a useful summary of global climate trends, but do not

provide detailed advice at regional levels. Reasons for this are highlighted in recent reviews on climate

change in Australia, which illustrate the lack of many basic tools with which to make specific

predictions at scales at which appropriate management measures can be taken. This stems from three

main gaps in marine ecological research: 1) the lack of long-term time series of data to establish

correlations with past environmental fluctuations; 2) a limited understanding of the way ecosystems

are structured by interactions between species and the environment; and 3) little information on the

tolerances of habitat-forming species to variability in the environmental factors that may be affected

by climate change.

Marine systems may be impacted by a number of physical variables that are likely to interact in

inconsistent ways. The system responses will be further complicated by biological interactions among

species. These factors, coupled with the broad range of possible outcomes of model predictions, lead

to considerable variance in opinion as to the seriousness of climate change effects in the short- to

medium term. For example, it has been suggested that changes in regional oceanography will have

either little effect on current systems in northern New Zealand, or that spin-up of the South Pacific

gyre could strengthen the East Auckland Current considerably. Similarly, acidification effects in the

Southern Ocean and Sub-Antarctic waters off southern New Zealand, brought about by the increased

uptake of CO2 may have either negligible effects, or potentially disastrous effects on productivity,

community structure and biodiversity. These inconsistencies arise primarily from a lack of data,

particularly time series, and understanding with which to refine predictive models.

Some broad-scale research questions that need to be addressed in the New Zealand context to provide

impact scenarios over the next century and beyond include:

• Which species are most at risk, and consequently, which functional groups and

ecosystems are most sensitive? How will their populations change?

• What is the range of natural variability in physical and biogeochemical systems at the

present time?

• How will climate change/variability influence biodiversity, assemblage structures, and

abundance of the key participants in biogeochemical processes, and how will these change

ecosystem function?

Climate change and the New Zealand marine environment v

• What are the natural tolerances of key species and/or major taxonomic groups to changes

in various predicted stressors to provide scenarios in impact prediction?

• How will climate change influence the rate of arrival, establishment and spread of non-

indigenous species?

• What are the rates of change in key ecosystems and what adaptive potential do key groups

have to varying rates of change?

• What interactions might occur between climate-related stressors and the energetic budgets

of marine species and ecosystems?

• What is the magnitude of potential effects of climate change compared to other

anthropogenic effects on New Zealand marine ecosystems?

• How might existing sources of anthropogenic disturbance interact with projected climate

changes to exacerbate problems?

• How vulnerable are New Zealand’s economic activities in the marine environment –

especially wild fisheries, aquaculture, and tourism – to climate change in the short to

medium term?

Research priority should be given to initiating long-term monitoring studies for those oceanographic

features for which data are currently lacking, and for characterising biological assemblages and their

natural variability at a national scale. Such a programme is open-ended by nature and does not have

specific goals, and thus will not meet the criteria usually imposed for short-term research funding. It

is, however, imperative to possess such data if shorter-term experimental work is to be validated, and

to interpret the changes brought about by climate change so that effective management interventions

can be implemented, where warranted. Time series data in the natural environment usually do not

begin to have predictive power before at least ten years have elapsed, but do provide information that

forms the basis of more specific experiments of shorter duration. Predicted climate changes over the

next few decades are relatively small, and thus are difficult to simulate effectively in manipulative

experiments. A first step would be to collate and coordinate existing monitoring and measurement

programmes with a view to identifying critical gaps.

Priority for short-term experimental work is likely to be driven by feasibility, but should be

concentrated on determining the effects of likely known impacts (e.g., temperature, salinity, pH,

sedimentation) on influential taxa within different biomes. Identification of these taxa is critical to

progress in determining future ecosystem-wide effects of incremental changes in climate.

Climate change and the New Zealand marine environment vi

Given the current information void, projections of socioeconomic impacts in New Zealand as a result

of climate change could vary from serious, if major biogeochemical processes fail and/or if ocean

productivity is affected causing fishery collapses and reduced aquaculture production, to negligible.

Climate change and the New Zealand marine environment 1

1. Introduction

1.1 Preamble

This report forms a summary of the likely expected changes to the New Zealand

environment under Intergovernmental Panel on Climate Change (IPCC) scenarios, and

describes some of the potential effects on the marine environment. There has been

little research specific to marine effects of climate change undertaken in New Zealand

to date, and the report therefore uses existing information from New Zealand and

elsewhere to infer general trends, and highlight areas where knowledge is lacking.

The marine climate drives a complex series of interacting elements that dictate

biodiversity, species distributions, productivity and ecosystem function, including

biogeochemical processes across varying spatial scales (Figure 1). Changes that are

occurring and are expected to continue due to human activities are increases in

atmospheric CO2 levels and removal of atmospheric ozone. The latter has already

increased the levels of ultraviolet radiation in New Zealand, and the former has the

dual effects of causing large-scale warming (due to the greenhouse effect) and

increasing the quantity of CO2 taken up by the world’s oceans. Warming will have

effects not only on sea temperature, but also may potentially disrupt or modify

existing weather patterns. CO2 uptake has the direct effect of acidifying seawater, with

potentially consequent effects on the productivity of many marine systems.

Here, we attempt to use overseas and New Zealand examples to identify the likely

effects of four main consequences of climate change on the New Zealand marine

environment: sea level rise, changes to wind and rainfall patterns, ocean acidification,

and current patterns and ocean warming. These factors will give rise to other indirect

effects that are summarised briefly. We put forward suggestions for research

directions that may prove fruitful in the future for predicting and mitigating specific

impacts, and also suggest potential indicators for assessing the rate at which climate

change effects are being felt.

1.2 New Zealand’s ocean in a warming world.

Much of the information presented here is taken from the Climate Change Effects and

Impacts Assessment guidance manual for local government in New Zealand (MfE

2004a, b), which was published by the Ministry for the Environment. That report used

the best available information to provide projections of future climate change around


New Zealand, and information on how these compare with present climate extremes

and variations.

Figure 1. Schematic diagram of direct and indirect consequences of climate change in the marine environment. Green boxes are causal agents that are directly influenced by climate change.


The New Zealand projections are based on global climate model (GCM) projections

presented in the Intergovernmental Panel on Climate Change (IPCC) Third

Assessment Report (2001) (see Chapter 9, Cubasch et al. 2001), using 35 different

future emissions pathways or 'scenarios', described in the Special Reports on Emission

Scenarios (SRES) for the IPCC. All the SRES scenarios project ongoing increases in

the atmospheric concentration of greenhouse gases over the coming century (even

those scenarios where the emissions start to decrease at some point before 2100). The

projected global temperature increases from all scenarios over the next 50 to 100 years

are much larger than those that have occurred over the past 1000 years. The IPCC

does not contend that any one SRES scenario is more likely than any other - it is as if

they have provided a die for predicting future conditions with 35 equally-weighted

sides.

These GCM projections have been statistically down-scaled for New Zealand based

on work presented in Mullan (2001a). Using these techniques, climate projections for

New Zealand have been prepared for changes from 1990 to 2020-2049, and from 1990

to 2070-2099. These future 30-year periods are centred around 2035 and 2085, and

are referred to in this chapter as the '2030s' and '2080s' respectively. A range of

possible values for each climate variable (temperature, rainfall, etc) is provided (Table

1, Appendix 1 Fig. A1–A6). This reflects not only the range of greenhouse gas futures

represented by the 35 SRES scenarios, but also the range of climate model predictions

for individual emission scenarios. Like the IPCC, we are unable to indicate a most

likely value from within the projection range. However the extreme ends of the

ranges may be slightly less likely than the central values, since they generally result

from the one climate model which gives the most extreme projection, rather than

reflecting agreement between a number of models.

The lowest and highest rainfall projection patterns show a strong southwest to

northeast gradient: the rainfall changes in the southwest of the country vary from no

change (or a slight decrease) to a large increase in annual mean, whereas northeastern

areas vary from a large decrease to no change. There is a lot of variability among

models, and for many locations even the sign of the rainfall change cannot be stated

with any confidence. However, in the 2080s annual mean (Figure A4), the regions of

Taranaki, Manawatu-Wanganui, West Coast, Otago and Southland tend to show

increased rainfall for all scenarios, compared to Hawkes Bay and Gisborne which

show rainfall decreases for all scenarios. Seasonally, the largest decreases occur in the

north and east of the North Island in spring.


Table 1. Summary of the main features of New Zealand climate change projections for 2030s and 2080s. Degree of confidence on projections indicated in brackets (VH = very high, H = high, M = medium, L = low). 'Very high' confidence means that it is considered very unlikely that these estimates will be substantially revised as scientific knowledge progresses, while 'low' confidence means it is possible that estimates will be revised considerably in the future.

Climate variable

Direction of change Magnitude of change Spatial and seasonal variation

Mean temperature

Increase (VH) Mid-scenario 0.5-0.7°C by 2030s, 1.5-2.0°C by 2080s (M)

Strongest warming in winter, tendency for slightly more warming in E and N

Daily temperature extremes (frosts, hot days)

Fewer cold temperatures and frosts (VH), more high temperature episodes (VH)

Unknown Large decreases in number of frost days in lower N Island and the S Island. Substantial increase in number of days above 25°C particularly at already warm northern sites

Mean rainfall Varies around country. By 2080s Taranaki, Manawatu-Wanganui, West Coast, Otago and Southland show increases; Hawke's Bay Gisborne, eastern Canterbury, eastern Marlborough show decreases (M)

Substantial variation around the country (see Appendix 1)

Tendency to increase in south and west, decrease in N and E. Largest projected seasonal decreases in spring in N and E of North Island

Extreme rainfall

Heavier and/or more frequent extreme rainfalls, especially where mean rainfall increase predicted (M)

No change through to halving of heavy rainfall return period by 2030s; no change through to fourfold reduction in return period by 2080s (L)

Increases in heavy rainfall most likely in areas where mean rainfall is projected to increase

Snow Snow cover decrease, snowline rise, shortened duration of seasonal snow lying (all M)

Unknown Unknown

Glaciers Continuing long-term reduction in ice volume and glacier length (M)

Unknown Reductions delayed for glaciers exposed to increasing westerlies


Wind (average)

Increase in the mean westerly windflow across New Zealand (M)

By 2080s, could be from slight increase up to doubling of mean annual westerly flow (L)

Unknown

Strong winds Increase in severe wind risk possible (L)

Little change up to double the frequency of winds above 30m/s by 2080s (L)

Unknown

Storms More storminess possible, but little information available for New Zealand (L)

Ex-tropical cyclones might be slightly less likely to reach New Zealand but if they do their impact might be greater. Intensity or frequency of mid-latitude storms might increase (L)

Unknown

Sea level Increase (VH) 9-88 cm rise (New Zealand average) between 1990 and 2100 (VH)

Uniform?

Waves Increased frequency of heavy swells in regions exposed to prevailing westerlies (M)

Unknown Increase in frequency of heavy seas and swell along western and southern coasts

Storm surge Storm surge height and extreme storm-tide level may increase (L)

Unknown Unknown

Ocean currents

Various changes plausible, but little research or modelling yet done

Antarctic circumpolar current likely to accelerate, would further isolate waters on Campbell Plateau and increase inflow of cold water to Chatham Rise. Increase upwelling of cooler subsurface waters along coast. (L)

For projected increased westerlies, coasts affected are west coast SI and northeast coast NI, but changes in north-south wind component could substantially modify which regions affected.

Note 1. Changes in the return period of heavy rainfall events may vary between different parts of the country, and will also depend on the rainfall duration being considered.

1.3 Current work to update these scenarios

Currently NIWA is working on an update to the climate change guidance manual for

local government in New Zealand (MfE 2004a,b). The update uses a selection of the


latest GCM projections from the IPCC Fourth Assessment (AR4) report (see Chapter

10, Meehl et al. 2007).

The IPCC made subtle changes between the Third and Fourth Assessments in the way

they expressed the climate projections. The Third Assessment stated: “The globally

averaged surface temperature is projected to increase by 1.4 to 5.8°C over the period

1990 to 2100. These results are for the full range of 35 SRES scenarios, based on a

number of climate models.” In the Fourth Assessment, the projections were expressed

as changes between 1980-1999 and 2080-2099, and projections were given separately

for 6 marker scenarios which spanned the range of the full 35 SRES scenarios. For

each of the 6 scenarios, a best estimate was provided, as well as the likely range. The

full range in global temperature increase over the 6 marker scenarios of the Fourth

Assessment was 1.1 to 6.4°C.

The New Zealand downscaled projections follow the revised IPCC approach. That is,

changes are relative to 1980-1999, which is identified with the “current climate” and

still abbreviated as “1990”. Changes are calculated for the two future periods 2030-

2049 (“2040” for short) and 2080-2099 (“2090”). Thus, the New Zealand projections

are 50 and 100 year changes, between the present (“1990”) and future periods centred

on 2040 and 2090.

2. Sea level rise

New Zealand relative sea level rise (SLR) is predicted to be similar to the global

projections of SLR by the Intergovernmental Panel on Climate Change (IPCC) Third

Assessment Report at around 1.8 mm/year (MfE 2004). This is due to the thermal

expansion of the oceans and freshwater input from ice-melt (Harley et al. 2006).

SLR will not be 'temporary' and is expected to continue for several centuries even if

greenhouse gas emissions are reduced. This is because of the long lag times needed

for the deep oceans to respond to ocean surface heating, and the expected

contributions from the massive Antarctica and Greenland ice sheets after 2100. IPCC

projects that mean sea level will rise between 9 and 88 cm between 1990 and 2100

(McCarthy et al. 2001). These projections do, however, rely on a constant rate of sea-

level rise acceleration of 0.013 ± 0.006 mm yr-1 (Church & White 2006).

In the Pacific localised climatic cycles will also affect the rate of SLR. The

Interdecadal Pacific Oscillation (IPO) which alternates between positive and negative

phases every 20 to 30 years appears to have changed around 1998 or 1999 to a

negative phase. Due to more balance resulting between El Niño and La Niña episodes


this is expected to contribute to an increased rate of SLR than that experienced over

the previous positive phase of IPO from 1976 to 1998. In which case, the next 20 to 30

years should see a faster rise in sea level than the mean long-term trend of 1.7 ± 0.5

mm/yr through the 20th century (Bindoff et al. 2007). This local acceleration of SLR is

irrespective of any changes in the rate of SLR attributable to global warming.

In Australia, much greater sea level rise is projected on the east coast than the west

due to the increased southward penetration of the warm East Australian Current

(EAC), which causes water there to expand more than in other regions (Poloczanaska

et al. 2007). Slightly higher relative increases in SLR could also therefore be seen in

northeastern New Zealand if predicted strengthening of the East Auckland Current

occurs (see Section 5).

2.1 Projected effects

Global warming is projected to raise sea level in the 21st century, with expected

dramatic impacts in low lying areas subjected to coastal hazards including inundation,

subsidence and erosion. Table 2 shows the magnitude of projected change predicted

by the IPCC in 2001 (MfE 2004).

Table 2. Projections of future sea level rise (SLR) for New Zealand above 1990 mean sea level.

Scenario Climate factors SLR by 2050 (m) SLR by 2100 (m)

Recommended NZ SLR magnitudes 0.2 0.5

IPCC-2001 'Most-likely' mid-range [Figure A2.7]

Averages of climate models & socio-economic scenarios 0.14-0.18 0.31-0.49

IPCC-2001 Outer ranges [Figure A2.7]

Intermediate zones Upper & lower extreme zones

0.10-0.24 0.05-0.31

0.21-0.70 0.09-0.88

Average historic NZ trend continues (0.16 m/century)

No change in sea-level trend over the 1900's

0.08 0.16

The effects of this SLR will be increased risk of low-lying areas to inundation by

increased water depths, which in turn will exacerbate damage from flooding events

and discharge from backed up rivers and stormwater systems. Inundation of low-lying

areas and drowning of intertidal habitats will occur more frequently during storm


events, accelerating the effects of coastal erosion. Resulting increased sedimentation

will smother habitats and species not adapted to high sediment loads. However, in

sheltered areas where sediment accumulation is high, the resulting rise in the level of

the shore may keep pace with, or even exceed, the rate of SLR. Other effects will be

changes in tidal variation increasing the mean tidal level and the shape of the tidal

prism, water movement alterations, and increased seawater intrusion into estuaries and

rivers (Short & Neckles 1999).

2.2 Vulnerable habitats and species

2.2.1 Estuaries and wetlands

Estuaries and wetlands are already disappearing worldwide due to a variety of

economic and social activities including filling, reclamation, and sediment

interception (Valiela et al. 2004). Such losses are of concern because these wetlands

provide important functions, including export of energy-rich material to deeper waters

and nursery habitats, shoreline stabilisation, and intercept land-derived nutrients and

contaminants. Although wave heights inside estuaries are often limited due to the

shallow water depths and short fetch lengths, waves can make a significant

contribution to inundation when strong winds combine with extreme water levels.

Ocean waves overtopping narrow sand or gravel barriers can also significantly

increase water levels in lagoons. It has been estimated that world-wide SLR could lead

to the loss of up to 22% of coastal wetlands (McCarthy et al. 2001). SLR will

exacerbate the loss of these habitats due to more frequent inundation and added stress

to compromised keystone species and habitats.

Important components of estuaries and wetlands are seagrass beds, which are known

for providing valuable community functions including food and nursery habitat for

many commercially and recreationally important fish, invertebrate habitat, and food

for waterfowl (Short & Neckles 1999; Turner & Schwarz 2006). Other important

ecosystem functions include regulating dissolved oxygen, chemical and physical

environment, suspended sediments, chlorophyll, and nutrients in the water column.

The effects of SLR on seagrass will be a redistribution of existing habitats, causing

some plants to relocate to areas they can tolerate, and others may be able to expand

their distribution inland. This will result due to salinity changes affecting seed

germination, propagule formation, photosynthesis, growth and biomass. Increased

water movement, tidal currents and wave action will reduce water clarity affecting

photosynthesis. Disease and fouling by epiphytes on seagrass are also expected to

increase (Short & Neckles 1999).


2.2.2 Mangroves

In geological timeframe, SLR has been cited as one of a range of contributing factors

in the loss of mangroves in the Poverty Bay – East Cape region in New Zealand,

which is below its current southern limits of Avicennia (Mildenhall 1994). In some

parts of the world, mangrove forests were able to persist during the Holocene when

sea level rose at rates of 8-10 mm/year due to the mitigating effects of large sediment

inputs (Woodroffe 1990).

Where sediment accumulation does not keep pace, rising sea level may either reduce

the width of the mangrove zone on the shore or cause them to migrate upshore, as

higher levels on the shore become flooded more frequently (McCarthy et al. 2001).

This migration may occur at the expense of saltmarshes behind the mangroves (Harty

2004), unless they too are able to migrate upshore. There is evidence for such upward

migration of mangroves during periods of SLR from studies of shoreline changes of

glacial/interglacial cycles (Wolanski & Chappell 1996). However, there may be much

larger shorter-term variation in sea level (Ramsay 2006), so that even if sedimentation

rates or mangrove migration rates are able to keep pace with the average rate of SLR,

there may be net loss of mangroves or saltmarsh during these periods of more rapid

change.

Migration of both mangroves and saltmarshes will be restricted where coastal

defences are present – a process referred to as “coastal squeeze”. In parts of Europe,

such as the Netherlands and eastern England, this potential loss of coastal habitat has

been addressed through a strategy known as “managed realignment”. Rising sea levels

are allowed to breach existing sea defences and low-lying areas behind them are

flooded and potentially revert to coastal vegetation (Wolters et al. 2005). These areas

are generally uneconomic farmland that was formerly created by infilling of the coast.

The strategy thus allows the preservation of coastal habitat and avoids the high cost of

defending low-value land.

Migration of mangroves to higher latitudes has also been predicted as a result of

climate change (McLeod & Salm 2006) as increasing average temperatures allow

them to survive at higher latitudes. Expansion of the geographical range of mangroves

in New Zealand will depend on whether mangrove propagules can actually reach

suitable habitats further south, and may also be limited by periodic extremes of

temperature.

All of these potential effects are subject to considerable uncertainty and are likely to

be influenced by other coastal changes occurring at the same time (Morrisey et al.


2007). These include changes in coastal geomorphology, water movement and

associated patterns of erosion and sedimentation. These factors make it very difficult

to predict how mangroves will respond to SLR at any given location or over a

particular period of time.

2.2.3 Rocky intertidal habitats

Rocky intertidal zones are one of the most productive environments on earth (Hurd

2000) and offer a dynamic range of habitats subject to environmental challenges of

aquatic and aerial climate regimes. As a result, rocky shore organisms and

assemblages may serve as early warning systems for the impacts of climate change

(Helmuth et al. 2005, 2006; Mieszkowska et al. 2006). Thermal and desiccation stress

can set the upper limits of zonation of many intertidal organisms (Davenport &

Davenport 2005). As position on the shore determines the length of time a sessile

organism is covered by seawater, the higher up the shore the shorter the immersion

time during the largest tides. The tidal ranges vary around the coast, but the range

differs from 1-2 m on the east coast to 3.5-4 m on the west coast (LINZ 2007). Tidal

influence determines the position of organisms on the shore (Raffaelli & Hawkins

1996), but tidal effects are modified by factors such as wave force, humidity, substrate

topography and biotic and behavioural interactions (Underwood & Jernakoff 1981).

Wave action acts as mechanical stress on intertidal organisms, but varies greatly

depending on shore slope, fetch and bathymetry waves have travelled over (Denny

1988). Erosion of rocky shores generally occurs during storms when elevated sea

levels and large waves attack the base of cliffs, resulting in undermining and failure

(MfE 2004a). Cliffs also erode slowly under wetting and drying processes. Increasing

SLR will result in increased erosion of these habitats potentially altering species

composition, alongside the gradual migration of species up-shore. Increased

sedimentation has been shown to affect the settlement and germination of the spores

of habitat-forming intertidal algal species (Schiel et al. 2006). Much like estuarine

habitats, coastal squeeze of species can also occur, but this would be more noticeable

on steeply sloping shores or those bordered by cliffs. In areas where seawalls and hard

protection measures are installed to protect against SLR, species may colonise these

structures if appropriately designed and constructed. Inappropriately designed

protective structures, can lead to displacement of erosion pressures laterally along the

beach.


2.2.4 Shallow subtidal reefs

Shallow reefs are very productive habitats (Taylor 1998) and support a large

proportion of New Zealand’s coastal biodiversity, despite forming a relatively small

percentage of the continental shelf habitat. Rocky reefs also support a large number of

endemic species, and their topographical complexity means that they contain many

habitat types within a small geographical area.

There are likely to be few long-lived sessile organisms unable to alter their vertical

distribution on reefs in the face of projected SLR. Rather, the effects on shallow reef

assemblages are likely to be more subtle and result from indirect effects of SLR,

including increased erosion and wave exposure, subsequent inundation by sediments

and detrital matter (Bishop & Kelaher 2007), and resuspension and transport of

sediments during more frequent severe storm events. Seaweeds may be especially

vulnerable to such impacts. Seaweeds provide very important ecological services

(Schiel 1990, Taylor 1998; Shears & Babcock 2004) such as primary production,

physical habitats, refugia for invertebrates (Taylor & Cole 1994; Anderson et al. 2005)

and fishes (Choat & Ayling 1987; Willis & Anderson 2003), nutrient cycling (Taylor

& Rees 1998, Tyler & McGlathery 2006), and food resources for rocky reef

communities (Zemke-White & Clements 2004; Taylor & Brown 2006). Reduced light

levels, scouring and inundation by sediment at the base of reef systems may become

more common reducing algal depth limits, whereas, storm surges could lower the

upper limits for algal assemblages (Graham 1997). The loss of habitat-forming algae

can cause cascading effects for other species resulting in unforeseen reductions in

some species (Moore et al. 2007). Increased SLR could however offset any impacts

currently present due to increased UV resulting from reduced stratospheric ozone

concentrations. Another subtle effect could result from vertical range squeeze when

abiotic stress shifts the vertical range of one species into the vertical range of a

consumer or competitor (Harley et al. 2006).

The effects of overfishing reducing keystone predator species in reef ecosystems may,

however, overshadow SLR and climate change impacts on important habitat-forming

algal communities as seen in California (Steneck et al. 2002). When the predator

species, such as rockfish, at the top of the food chain are removed, then the species

that they normally eat, such as snails and barnacles, begin to increase in number.

Many of these are herbivores that eat kelp. When herbivore numbers increase, they

decrease the amount of kelp, in turn changing how kelp forests look and the type of

species that are associated with the kelp forest. Thus, managing overfishing of

keystone species may be more important to make reef communities more resilient to

climate change (Folke et al. 2004).


2.2.5 Open coast sand beaches

Coastal sandy beaches, while not supporting particularly diverse communities as

compared with rocky reef systems, play an import role in buffering the land from

wave and wind energy. Increased SLR will be most hazardous to areas of the coastline

bordered only by foreshore beaches and sand dunes, where run-up of waves can reach

more than 6 m above MSL leading to blow-outs of dunes and flooding low-lying areas

behind the dunes (MfE 2004a). The subsequent erosion and increased sediment

transport will impact on bordering reef systems, and soft-sediment communities

below. In situations where beaches are bounded by hard artificial structures, protection

from coastal inundation is dependent on the height, slope and type of structure. In

general, the lack of dissipation of energy from these structures results in higher wave

run-up than would occur on natural beach materials. This will be exacerbated by the

increased storminess expected with climate change.

3. Wind and rainfall patterns

Climate models predict that for mid-range temperature change projections, the mean

westerly wind component across New Zealand will increase by approximately 10% in

the next 50 years (Mullan et al. 2001b, MfE 2004a) with scenarios leaning strongly

towards increasing westerly flow, particularly in the annual mean. The mid-range

projection for the 2080s is a 60% increase in the annual mean westerly component of

the flow. Projected changes in the north-south wind component are less clear. Strong1

winds are associated with intense convection (expected to increase in a warmer

climate) and with intense low-pressure systems that might also become more common.

Thus, an increase in severe wind risk could occur, which has been identified relating

to the increasing number of intense cyclones in the North Atlantic (Knippertz et al.

2000). For mid-range temperature change scenarios, the highest wind speed expected

to occur once per year could increase by about 3% by 2080. Over the sea or flat land

the annual frequency of occurrence of winds of 30 m/s or above might increase by

about 40% by 2030 and 100% by 2080 (MfE 2004a). There is however considerable

uncertainty in these predictions. How extreme winds affect different parts of New

Zealand is also likely to change in the future. The regional distribution of wind

extremes is probably dependent on the stability of the air approaching the land from

the ocean, which may change.

1 A "strong" wind is in the range 22-27 knots, or 11-14 m/sec


Figure 2. Highest expected annual precipitation change in New Zealand between 1971-2000 and 2071-2100.

A warmer atmosphere can hold more moisture (about 8% more for every 1°C increase

in temperature), so more intense rainfall events are "very likely over many areas"

(McCarthy et al. 2001). Despite a lot of variability among models in the 2080s annual

mean rainfall, the regions of Taranaki, Manawatu-Wanganui, West Coast, Otago and

Southland tend to show increased rainfall for all scenarios (Figure 2), compared to


Hawkes Bay and Gisborne which show rainfall decreases for all scenarios. Seasonally,

the largest decreases occur in the north and east of the North Island in spring (MfE

2004).

For a modelled 2°C change in temperature during a storm over New Zealand

mountains a 6-7% increase in both maximum and catchment averaged rainfall was

predicted (Gray and Larsen 2003). Similar increases were predicted for a 10% increase

in wind speed. Increasing both wind speed and temperature together led to a 16%

increase in rainfall. Various modelling studies suggest that heavy rainfall events will

occur more frequently in New Zealand over the coming century, but the likely size of

this change is uncertain. Of importance to South Island rivers, snow cover will

decrease and snowlines rise as the climate warms, but as warmer air holds more

moisture more winter snow is expected at high elevations, so warming does not rule

out increased winter snowfall and spring discharges to the sea.


Predicted increased intensity of storms will manifest as increased intensity winds and

rainfall events. These will impact the coastline by increasing erosion due to higher

intensity wave forces eroding the coastline, and increased erosion of terrestrial

catchments respectively. These will exacerbate drainage and flooding risks, increasing

the volume of sediment discharged to the coast, and increase the resuspension of soft

sediments in shallow environments. The resulting increased turbidity will further

decrease light levels. Increased rainfall intensity will also depress salinity levels in

estuaries affecting stratification, sediment transport and deposition rates.


3.2.1 Estuaries and soft sediment communities

A 7 mm inundation of terrestrial sediment has been shown experimentally to reduce

soft sediment macrofaunal individuals and species by 50% (Lohrer et al. 2004). A

thicker deposit of 2 cm thick can cause underlying sediments to become anaerobic,

killing all infauna, with incomplete recovery seen after 603 days (Thrush et al. 2003,

Thrush et al. 2004). Heavy inundations of sediment can completely bury infaunal and

epifaunal bivalves (McKnight 1969) unless waves and currents can disperse sediment

plumes. Such catastrophic events severely compromise subtidal habitats. More

importantly, are the frequent and widespread sublethal impacts of terrestrial sediment

contamination which cause chronic physiological stress to plants and animals leading

to degenerative change (Thrush et al. 2004, Poloczanska et al. 2007). Following


catastrophic events the loss of suspension feeding bivalves can uncouple the seafloor

and water column processes, allowing for regime shifts towards primary production

dominated by phytoplankton (Dame 1993, Kemp et al. 2005). This is exacerbated by

reduced light levels reducing benthic primary production because seaweeds and

seagrasses typically require more light for photosynthesis than phytoplankton (Duarte

1991, Markager & Sand-Jensen 1992).

3.2.2 Mangroves

As with SLR above, mangroves are predicted to expand in range in areas where

increases in temperature allow for their colonisation to higher latitudes, and with this

expansion will be increased conflict over the aesthetic values of mangroves and the

pressures from coastal urban developments (Morrisey et al. 2007). Because mangroves

are habitat modifiers that trap sediment, they may mitigate SLR in parts of the country

exposed to increased sedimentation from climate change induced rainfall increases

such as the west coast of the North Island. However, if mangroves were to spread

further south to historic southern limits in Poverty Bay (Mildenhall 1994), they may

be less able to cope with SLR there due to predicted drier conditions reducing

sediment inputs, which could hinder their spread during periods of drought. With SLR

and increased rainfall, mangroves are expected to outcompete salt marsh plants

leading to the loss of salt-marsh habitats (Poloczanska et al. 2007). Hydrodynamic

modifications resulting from urban and rural irrigation and drainage are however

likely to be overriding factors in the expansion of mangroves (Poloczanska et al.

2007).

3.2.3 Subtidal rocky reefs

Laboratory and in situ experiments on a gradient of sediment contamination between

Whitianga Harbour mouth and Hahei demonstrated both direct and indirect impacts of

terrestrial sediment on biodiversity of rocky reefs (Schwarz et al. 2006). Indirect

effects were decreased photosynthetic potential of Ecklonia radiata, with the greatest

degree of acclimation to low light levels at the high sediment sites. This suggested

reduced production of all primary producers. Of greatest concern was the large

decrease in epifuanal biomass colonising E. radiata, since epifauna are estimated to be

responsible for about 80% of flow of energy and materials through rocky reef

communities (Taylor 1998). The direct effects of sedimentation were sublethal

impacts on filter feeders with evidence of increased energy requirements compounded

by synergistic effects with duration of exposure. Mean survival of the amphipod Aora

typica decreased logarithmically in increasing suspended sediment concentrations, and

paua and kina larval bioassays showed lethal effects at high concentrations and again


synergistic effects with duration of exposure. In addition, Walker (2007) has shown

that fine sediments can inhibit the settlement of kina larvae, and reduce the survival

rate of recruits. Disturbingly, thresholds of “minimum concentration of effect”

recommended by Schwarz et al. (2006) for chronic and toxic impacts of sediment

contamination fell well below levels that some rocky reef environments experience at

both Whitianga and Hutt River.

3.2.4 Intertidal coastlines, animals and seabirds

While natural disturbances like storms may be important for maintaining diversity in

coastal ecosystems, increased frequency and severity of storms may reduce their

resilience by detaching coastal plants and animals, further destabilising coastlines

(Poloczanska et al. 2007). While ex-tropical cyclones might be slightly less likely to

reach New Zealand later this century, their impact may be greater (MfE 2004a).

Cyclones are considered a major threat for breeding colonies of some seabirds in

northern Australia (King et al. 1992; Garnett & Crowley 2000) and also account for

turtle kills and destruction of breeding and feeding habitats (Limpus & Reed 1985).

Storms also account for Antarctic fur seal deaths and mother-pup separations in the

Shetland Islands (Boveng et al. 1998), thus, an increase in storm severity or return

times could affect New Zealand fur seal populations especially on the west coast of

the South Island where wind and storms are predicted to increase.

In wave surge zones on exposed rocky shores, changing wave climate and resulting

hydrodynamics will affect the resilience of alga to stay attached. Algae larger than

around a tenth of a millimetre extend beyond the protection of the viscous boundary

layer (Denny 1988) and have to adapt to surviving the energy forces generated by

larger waves (Stevens et al. 2004). For survival and propagation, large seaweeds like

Durvillaea antarctica reduce the loading by around 30% due to frond interactions

between neighbouring individuals (Stevens et al. 2004). Therefore, if localised

catastrophic loss occurs, recovery may be difficult under a global warming scenario at

exposed sites. However, determining the role of climate change will be difficult as

recruitment of D. antarctica has been shown to be influenced by grazing by butterfish

Odax pullus in the absence of cover by adult kelp (Taylor & Schiel 2005). ENSO

climate variations have also been shown to affect kelp populations in southern

California with reduced density during extended periods of above normal sea surface

temperatures and increased precipitation associated with El Niño events (Grove et al.

2002).


4. Ocean acidification


A recent review of ocean acidification by the UK Royal Society has stimulated

significant concern and considerable international research activity into ecosystem and

biogeochemical impacts of decreasing pH in the surface ocean (Royal Society 2005).

The uptake of anthropogenic CO2 from the atmosphere has already resulted in a pH

decrease of 0.1 pH units since 1750 (Trenberth et al. 2007) with a further decrease in

surface ocean pH of 0.4 pH units predicted by 2100 (Caldeira & Wickett 2003; Feely

et al. 2004). This is outside the range of natural variability and will impact biological

processes such as ocean productivity, food web structure and carbon sequestration.

Recent work (Le Quére et al. 2007) has suggested that strengthening westerly winds

over the Southern Ocean (expected under IPCC scenarios) has reduced the capacity of

the ocean to act as a CO2 sink (Sabine et al. 2004). This occurs by outgassing of CO2

back into the atmosphere by wind-driven upwelling. This phenomenon may reduce the

previously projected rates of acidification, but the Southern Ocean is still a significant

sink for CO2 (Ho et al. 2006).

The only NZ study that collects relevant information is the bimonthly Munida Time

Series collected along a transect off the Otago shelf, which has not identified any

significant change in pH in Sub-Antarctic Water over the 8-year survey period (K.

Currie, unpubl. data), despite a steady increase in atmospheric CO2 during this period.

It should be noted that the expected decrease in pH induced by increases in

atmospheric CO2 is small relative to the intra-annual variability and that a trend in

acidification may become evident a the time-series is extended. Time-series

measurements of longer duration in the Atlantic and Southern Ocean have identified

increasing acidification of surface waters consistent with increasing atmospheric CO2

(Santana-Casiano et al. 2007; Yoshikawa-Inoue & Ishii 2005).

Some experiments are currently being undertaken in NZ examining pH sensitivity of

coralline algae (C. Hurd, University of Otago), but there are no studies currently

underway to determine whether NZ EEZ or Southern Ocean ecosystems will adapt or

collapse in response to acidification.

Organisms that have a carbonate exoskeleton will be most susceptible as acidification

will reduce the saturation state, and so availability, of calcium carbonate. Most

vulnerable will be groups such as pteropods (zooplankton that are a dominant

component of the pelagic food web, particularly in the Southern Ocean),

coccolithophores, cold water corals, benthic littoral and sub-littoral molluscs,


echinoderms and crustaceans (Orr et al. 2005; Langer et al. 2006). Current evidence

suggests that the pteropods, zooplankton with a calcareous shell that are a dominant

component of the Ross Sea pelagic food web, are most susceptible with shell

dissolution occurring within 48 hours when incubated at 2100 CO2 levels in laboratory

experiments (Orr et al. 2005). The pteropods are an integral part of the Southern

Ocean foodweb and replace krill as the dominant zooplankton in the Ross Sea, but it is

currently unknown whether acidification will shift their geographical range to the

north or whether they will be replaced in the food chain.

In addition, there will be impacts on non-calcifying organisms, including autotrophic

bacteria, cyanobacteria and higher organisms such as fish and squid.


Calcifying organisms in the ocean use two polymorphs of CaCO3, calcite and

aragonite, which differ in their physico-chemical properties. Aragonite is more

sensitive in terms of pH-dependence, and availability is temperature-dependent with

aragonite saturation being reduced most in colder waters. This suggests that ecosystem

response to acidification may become apparent first in Southern Ocean and sub-

Antarctic waters, as supported by recent observations that polar waters will be

undersaturated with aragonite within 50 years (Orr et al, 2005) (Figure 3).

Consequently organisms that use this form, including corals, pteropods, and some

calcareous algae, are likely to respond to lowering pH before other groups (Table 3).

This does not mean that taxa that depend primarily on calcite are not at risk. Some

groups use a Manesium-Calcite combination that is potentially more susceptible to

lower pH than aragonite.

Increasing acidity is likely to put all calcifying taxa under physiological stress, with

possible consequences for growth and productivity across the board, especially in high

latitudes where calcium concentrations are already naturally low. Indeed, recent

research has found that long term reconstructions of past climate variability are

possible using δ18O-time series in crustose coralline red algae (Halfar et al. 2007).

Thus, despite the increased resistance to acidification of calcite forms, they will

eventually become vulnerable. This has implications for the stability of ecosystems

including calcareous species that are major predators and/or grazers. For example sea

urchins (Evechinus chloroticus) are known to be important grazers of macroalgae on

northern New Zealand reefs (Andrew & Choat 1982), and spiny lobsters important

predators of urchins (Babcock et al. 1999; Shears & Babcock 2002).


Figure 3. Distributions of (A) aragonite and (B) calcite saturation depths in the global oceans. The level at which aragonite and calcite are in thermodynamic equilibrium is known as the saturation depth. This depth is significantly shallower for aragonite than calcite, because aragonite is more soluble in seawater than calcite (from Feely et al. 2004. Science 305: 362-366. Reprinted with permission from AAAS).

Increasing CO2 levels have the potential to reduce productivity of all marine fauna by

increasing the energetic demands of respiration. Although large increases in CO2

concentration are likely to have only minor direct effects on oceanic productivity from

phytoplankton (Beardall & Raven 2004, Giordano et al. 2005), CO2 and acidity

covary, making it difficult to separate the effects of increasing CO2 concentration and

decreasing pH. Where primary productivity is dependent on calcareous organisms

(such as coccolithophores), acidification could result in the collapse of whole food

webs, at least at local scales. Coccolithophores, however, are not major contributors to

southern ocean productivity (F.H. Chang, pers. comm.), and projected changes in pH

are unlikely to have major effects on primary production in the short- to medium-term.

They are however a potentially significant source of the trace gas, dimethylsulphide

(DMS) which influences aerosol production in the marine troposphere and

subsequently the albedo (reflectance) of the atmosphere.


Table 3. Comparison of the characteristics of the aragonite and calcite forms of CaCO3.

Aragonite Calcite

Structure Orthorhombic triagonal

Solubility High Low

Calcifying species Corals, pteropods, macroalgae Foraminifera, macroalgae, coccolithophores, Crustacea

No significant evidence yet exists of acidification effects on coastal ecosystems

(Nicholls et al. 2007). Some experimental evidence indicates that increasing CO2

levels may have indirect, but variable, effects on kelp growth and may delay decay

processes resulting in reductions in shallow-water nutrient recycling (Swanson et al.

2007), which can have consequences for productivity. Projections indicate that

aragonite saturation levels will decrease considerably by 2100 (Figure 4), and calcite

will probably follow suit. Although New Zealand waters contain photosynthetic corals

– already known to be extremely vulnerable (Royal Society 2005; Poloczanksa et al.

2007) – only at the Kermadec Islands (Schiel et al. 1986), reefs from shallow coastal

habitats to deepwater seamounts possess corals that form important habitats

throughout the region (Cairns 1995). Indeed the unique shallow cold-water coral

ecosystems in Fiordland are particularly exposed and so vulnerable to acidification2. It

has been recently mooted that changing aragonite saturation levels are likely to place

70% of the world’s known deep-sea bioherm-forming corals in unsaturated waters by

2100, making these habitats increasingly marginal for coral survival (Guinotte et al.

2006; Turley et al. in press).

Acidification may become a threat to the profitability of the New Zealand aquaculture

industry and some fisheries if it causes cooler, more southern coastal waters to become

calcium-deficient. Crustacean and mollusc species may allocate relatively more

energy to maintaining chemical balances at the expense of growth and reproduction.

Crustaceans may spend longer periods unable to feed after moulting, and remain

vulnerable to predation for longer. Some molluscs may experience a reduction in shell

strength. For example, abalone shell is formed from layers of aragonite along with

calcite and proteins (Belcher et al. 1996) and may be vulnerable. Bivalves are

particularly susceptible at the juvenile stages when their surface area: volume ratio is

higher. Although New Zealand’s main aquaculture species, Perna canaliculus,

possesses a strong periostracum making it less vulnerable to calcium loss, continuing

2 Note this does not include the iconic black coral Antipathella fiordensis, as this species is not calcified.


acidification could conceivably result in a more brittle shell, reducing market value

and increasing handling costs. Experimental work is needed to determine the likely

risk to cultured species. It should be noted that coastal regions experience greater

variation in pH than open-ocean regions, and so organisms in the latter region may be

more susceptible to ocean acidification. Estuarine systems in particular often have

high CO2, and so it is likely that the extant calcifying species are adapted to this.

Figure 4. Historical and projected changes in the saturation levels of the aragonite form of calcium in world oceans (from Feely et al. in press, with permission, available through http://iodeweb3.vliz.be/oanet/FAQacidity.html).

There will also be other impacts on non-calcifying organisms via biogeochemical

changes in nutrient and carbon supply and availability. In warmer sub-tropical water

recent evidence (Hutchins et al. 2007) indicates that elevated CO2 increases cell

growth and nitrogen fixation by Trichodesmium, a large colonial cyanobacterium.

Cyanobacteria have relatively inefficient carbon-concentrating mechanisms and are to

some extent carbon-limited in the present day ocean; consequently increasing


dissolved CO2 increases cellular uptake via diffusion, so allowing diversion of energy

to growth and nitrogen fixation. Trichodesmium sp. may not be the only potential

“winner”, as nitrogen fixing cyanobacteria are responsible for significant new nitrogen

supply and support community primary productivity and carbon export in nutrient

poor sub-tropical waters. Consequently the positive response to acidification may be

reflected in increased productivity of sub-tropical waters, although there is also the

possibility that this may be limited by the ecosystem being driven into phosphate

limitation.

Impacts on the upper food chain may be more direct as well and not limited to indirect

effects such as loss of prey species. Physiological responses such as hypercapnia, the

acidification of the blood, is a potential problem for fish in high CO2 water where the

elevated CO2 gradient between the blood and water in the gills results in increased

acidosis of the blood and decreased oxygen-carrying capacity. Deep-sea fish and squid

are particularly sensitive to increases in seawater CO2 (Ishimatsu et al. 2004); there is

a pH effect on oxygen binding by the main blood pigment, haemocyanin, in squid that

effectively ceases to hold oxygen at a pH of 7.2.

Potential adaptation to acidification is a major uncertainty. Recent research on

coccolithophores suggests that some species, at least over relatively long time periods

(104-105 years), have the capacity for adaptation whereas others do not (Langer et al.

2006). Timeframe is a source of uncertainty in the interpretation of short-term

acidification experiments. Laboratory cultures of the freshwater algae,

Chlamydomonas did not display any adaptation to decreased pH over 1000

generations (Collins & Bell 2004). Conversely morphological adaptation has been

identified in scleractinian corals maintained in low pH water, with calcium carbonate

skeleton dissolution and dissociation of the colonial form accompanying successful

growth of the organism in the naked hydroid form (Fine & Tchernov 2007). It should

be noted that the rate of change in atmospheric CO2 and decreasing pH in the ocean is

more rapid than at any time in the last 800,000 years and likely longer, which may

limit the capacity for adaptation.

It should also be noted that the response to and impact of acidification will be

influenced by synergistic interaction with other climate change variables. This may be

at the physiological level where increased energy diversion to the process of

calcification reduces organism capacity to cope with other environmental pressures

such as increased temperature. Some susceptible groups are not mobile and will have

difficulty adapting their geographical zone; whereas other groups, such as corals, may

be caught in a “crunch’ zone whereby migration to waters of higher calcium carbonate

saturation may be limited by their temperature range.


5. Current patterns and ocean warming

The coupled atmosphere-ocean global climate models do not include enough detail to

show the narrow ocean currents that flow around New Zealand, and very little analysis

has been done of future patterns. This means that no quantitative statements about

these climatic features can be made at this stage.

The upper 700 m of the global oceans on average have warmed about 0.6°C since

1950 (Bindoff et al. 2007). This warming was not uniform spatially. Two thirds of the

increased heat content of the oceans has gone into the upper 700m. In addition, there

are significant horizontal variations, with the New Zealand region showing

particularly strong warming through the 1990s.

There have also been significant global salinity changes, with the general pattern

being freshening at high latitudes and increasing salinity in the tropics and subtropics,

consistent with an acceleration of the hydrological cycle (Wong et al. 1999; Curry et

al. 2003). This pattern means the surface ocean north of New Zealand region is

increasing in salinity, while the surface ocean south of New Zealand is freshening.

The changes in upper ocean temperature and salinity have impacts on stratification,

with warming and freshening serving to increase stratification. Increased stratification

could be expected to decrease nutrient fluxes from the deeper ocean into the euphotic

zone. However, this relationship may not be simple, with complicated feedbacks in the

coupled ocean/atmosphere system.

There are also both observed and predicted changes in deeper water masses, e.g. a

freshening of intermediate water masses. These deeper changes are not discussed here

because, while they are important for climate issues, they are incidental to ecosystem

changes.

There are predictions from global models of what changes are likely in the regional

and global wind patterns. Changes in winds hold clues as to what might be expected in

the ocean (Mullan et al. 2001b). The warm currents flowing down the eastern coast of

the North Island are part of the subtropical gyre (Stanton et al. 1997) and are driven

primarily by the ‘twisting’ action of the winds over the subtropical South Pacific. The

wind patterns over the subtropics show little change in the model runs; however,

westerly winds are projected to increase at higher latitudes and are likely to have

impacts on the current systems. Recent research (Roemmich et al. 2007) has linked the

~1°C warming around New Zealand through the 1990s to a ~20% spin-up of the

subtropical gyre resulting from an enhanced Southern Annular Mode (SAM), i.e.,


increased westerlies south of New Zealand. The predicted future increased high-

latitude westerlies could therefore be expected to result in a spin-up of the subtropical

gyre with stronger current flows and warmer conditions in the gyre centre (i.e., around

NZ).

Figure 5. Major ocean current systems of the New Zealand region

The cold Antarctic Circumpolar Current (ACC) would also be expected to accelerate

as a result of the strengthened high-latitude westerlies. This current system presently

reaches as far north as the southern flank of Campbell Plateau (Figure 5) where it

forms the Subantarctic Front. There are no predictions as to the detailed structure

south of New Zealand, but it is quite likely that the strength of the SAF may change.

Much of the complexity of the current systems is controlled by bottom topography

(Tilburg et al. 2001), reducing the likelihood of large changes in position of major


features, although analysis of recent trends suggests that the core of the SAF flow may

move south and accelerate (Gille 2007).

The predicted increased high-latitude westerly winds also have other implications.

Higher winds will result in more mechanical stirring in the mixed layer and will

increase the likely wave and swell field. There is also the likelihood of increased

localised coastal upwelling.


Increasing water temperatures should cause a general pole-ward movement in the

distribution of many species, a phenomenon that will be most strongly felt in depths

where water temperatures are most prone to short-term fluctuations (e.g. Helmuth et

al. 2006). Most marine species are adapted to a particular temperature range, and

physiological stress generally occurs when these limits are approached (e.g. Pörtner &

Knust 2007). Metabolic rate is also affected by increasing temperature, and tends to

shorten the duration of the planktonic larval stage of marine organisms. This implies

that a general increase in SST is likely to influence the dispersal of larvae, and may

reduce gene flow between populations (O’Connor et al. 2007).

The observation that warming has been most strongly seen in the upper 700 m of the

water column indicates that coastal and shelf habitats are those most likely to be

vulnerable (Harley et al. 2006). Elsewhere, significant changes in species distributions

have already been documented, particularly in the North Sea (Southward et al. 1995;

Perry et al. 2005), Mediterranean (Sabatés et al. 2006), and North America

(Roemmich & McGowan 1995; Smith et al. 2006). A strengthening series of

southward-flowing currents down the east of the North Island is likely to distribute

warm-temperate species toward Cook Strait and the northern South Island. East Cape

is regarded as something of a biogeographic break point, dividing the warmer Bay of

Plenty from cooler East Coast faunas (e.g. Adams 1994; Roberts & Stewart 2006).

This demarcation is likely to move south or disappear altogether. The process will

have the concomitant effect of reducing or eliminating cooler water species from east

Northland.

Shifts in species composition in assemblages may not necessarily be the direct result

of increasing temperatures, but may occur by cascading responses to changes in

abundance of habitat forming taxa (Schiel et al. 2004). Species that occur in temperate

zones are subject to much greater natural variability in temperature than those

occurring in tropical or polar regions, and therefore tend to have a much wider

tolerance range to temperature per se (Compton et al. in press).


The combination of spin-up of the subtropical gyre together with a warming ocean is

likely to see more tropical pelagic species in New Zealand waters. There were media

reports that sea turtles were seen off Northland in 1998, and marlin were caught as far

south as New Plymouth and Wairarapa. Our knowledge of the current systems of

northeastern New Zealand and the biological effects of their variability, coupled with

observations from previous ENSO events, allows us some ability to predict likely

effects on reef fishes.

The reef fish fauna of east Northland is known to be strongly influenced by the East

Auckland Current (EAUC), which is formed as an offshoot of the East Australian

Current that traverses the Tasman Sea (Stanton et al. 1997). In years when the EAUC

is strong, it facilitates recruitment of subtropical species (probably originating from

coastal Australia, the southern Great Barrier Reef and Norfolk Island) on the

Northland coast and shelf (Francis & Evans 1993). Studies at the Poor Knights Islands

have shown that variability between years is high, and this variability is reflected in

the fish fauna because most subtropical fish recruits do not persist when SST drops

(Choat et al. 1988; Denny et al. 2003). Responses in certain species, particularly

wrasses (Labridae) are rapid. A SST increase of c. 1˚C seen in the Tasman Sea during

1998-2000 (Sutton et al. 2005) followed a switch in ENSO from El Niño to La Niña

and was felt as a 0.5-1.7˚C increase over the long term average SST in the Hauraki

Gulf from late 1998 until mid-2000 (Leigh Marine Lab Climate Records). Fish

surveys in May 1999 detected strong recruitment pulses of Coris sandageri, Coris

picta, Pseudolabrus luculentus and Suezichthys aylingi at the Poor Knights (Denny et

al. 2003). Two of these (C. sandageri and P. luculentus) persisted at only slightly

reduced densities for 2 further years, whereas C. picta and S. aylingi decreased

continuously in density once the La Niña phase of ENSO pattern ended and SST

returned to average values. The latter species therefore probably have less tolerance of

lower temperature than the former. Juveniles of the tropical wrasse Thalassoma

lutescens were also commonly seen during early 1999 (T.J. Willis, pers. obs.), but not

detected subsequently. These observations suggest that rises in mean SST of more

than about 1˚C will establish subtropical species for which Northland is currently

marginal habitat, and result in increasing incidences of truly tropical fishes. The

likelihood of a species becoming established is probably less dependent on changes in

the annual average temperature than changes in winter minima.

Incursions of the EAUC on to the continental shelf at points south of the Mokohinau

Islands have been linked to the strength of episodic periods of easterly winds

(Sharples 1997). Since climate models predict an increase in westerly wind flow,

transport of warmer EAUC water into coastal ecosystems may be reduced, although

the EAUC will remain strong offshore. Limited evidence suggests that increases in the


mean SST in northern New Zealand are likely to reduce the ranges of species with

cold-water affinities. For example, fish monitoring at Hahei, eastern Coromandel

Peninsula, showed density reductions in blue cod (Parapercis colias) during the La

Niña conditions of 1998-99 (Willis et al. 2003). This result is correlative, however,

and research is needed on temperature tolerances of this species to make links between

water temperature and coastal fish density.

The effects of the potential changes in current flow on local-scale eddy and upwelling

systems is unknown over large scales, however changes in the position and

distribution of these is likely to alter patterns of recruitment. Chiswell & Booth (1999)

found distributions of rock lobster Jasus edwardsii larvae to be contained by the

Wairarapa Eddy off the eastern North Island, and suggested that this containment is

necessary to maintain the population. A shift in position or breakdown of the eddy

may have negative consequences for future lobster recruitment. Local-scale upwelling

systems of northeastern New Zealand are seasonal and appear to be driven to a large

extent by interactions between the strength of the EAUC and wind climate (Zeldis et

al. 2004). These upwellings are rich in nitrate that is limiting for the growth and

composition of the phytoplankton assemblage (Chang et al. 2003b; Zeldis 2004).

General increases in SST are likely to alter the reproductive cycles of many marine

species, resulting in earlier spawning times. Centres of productivity (e.g. upwelling

systems) may be influenced by temperature changes where these exceed the normal

tolerance range of primary producers.

Increasing SST over the last few decades has been implicated in an increase in the

reported incidence of disease in marine environments (Harvell et al. 1999, 2002; Ward

& Lafferty 2004). Mass mortality events caused by disease, or interactions between

disease agents and other factors, can cause large-scale changes in assemblage

structure, particularly where they affect habitat-forming species. Natural disease

outbreaks in New Zealand marine species are not well documented, although the

information base is improving through study of pathogens and parasites associated

with the aquaculture industry. Recent natural mortality events have affected pilchards

Sardinops neopilchardus (and S. sagax in Australia), and kelp Ecklonia radiata (Cole

& Babcock 1996) in northeastern New Zealand. Pilchard die-offs were attributed to a

herpes virus (Whittington et al. 1997) and climatic influences were eliminated as a

direct cause (Griffin et al. 1997). Viruses were also implicated in kelp die-offs (Easton

et al. 1997), but other factors, including light limitation from algal blooms and grazing

by epifaunal amphipods (Haggitt & Babcock 2003), were not eliminated as possible

explanations (Cole & Syms 1999).



Changes in currents and SST are likely to bring about changes that may be felt

throughout entire marine ecosystems, from primary productivity through to apex

predators like sharks, marine mammals (Trites et al. 2007; Simmonds & Issac 2007),

and seabirds (Frederiksen et al. 2006). All elements of the system may therefore be

regarded as vulnerable to change, although in some cases a warming scenario will

have beneficial effects.

It is generally accepted that there are links between ocean climate and the productivity

of many fisheries (Roessig et al. 2004; Ottersen et al. 2006; Brunel & Boucher 2007)

although the exact mechanisms for these links are not always clear. Francis (1993)

discovered a positive correlation between SST and the year class strength of snapper

Pagrus auratus in northern New Zealand, which further investigation has attributed to

larval competence in a superior feeding environment (Zeldis et al. 2005), whereas

Beentjes & Renwick (2001) have correlated recruitment of red cod (Pseudophycis

bachus) with cooler water temperatures.

There has been some research on the possible impacts of warming through the 1990s

on the New Zealand hoki (Macruronus novaezelandiae) fishery (Francis et al. 2006).

This research showed no definitive link between the ocean warming and the declining

hoki stocks, but did illustrate one of the main difficulties in this type of analysis: a

lack of intermediate connecting data between the physical conditions and the fish (e.g.

nutrient data, data about intermediate steps in the food chain). This point was

reinforced by Willis et al. (2007) whose analysis of southern blue whiting

(Micromesistius australis) recruitment on the Campbell Plateau found no link with

SST, but predicted that “good” recruitment years should be expected where sea

conditions were rough in winter, followed by a relatively calm spring. Similarly, and

ten years earlier, Renwick et al. (1998) had found correlations between the

survivorship of pre-recruit southern gemfish (Rexea solandri) and SST along with

increases in south-westerly winds. As with subsequent studies, causal mechanisms

could only be inferred. Potential solutions are to either continue to increase the time

series of data available for analysis, or seek to obtain data at spatial scales likely to

reflect biological influences on recruitment and survivorship. Useful (but currently

unavailable) information might include detailed data on mixing or stratification of the

water column, distributions and relative availability of major prey species through

early development, or the ways in which conditions affect the distribution of

predators.


6. Indirect effects

6.1 Primary production

The production of organic matter by marine phytoplankton is the driving force behind

ocean ecosystems in New Zealand as throughout the world. The process is termed

“Net Primary Production” (NPP), and measured as milligrams of organic carbon

produced by photosynthesis per square metre per day (mgC/m2/d). Net Primary

Production can be measured accurately from ships, but they cannot adequately map

NPP over areas the size of the New Zealand EEZ. Over the last decade, methods have

been developed to estimate NPP using satellite observations of the ocean which

observe the whole world every 2 days. More than ten different approaches have been

tried and there are significant differences in their results. None of the methods has

been adequately validated in New Zealand waters but work to date suggests that the

model based on Behrenfeld & Falkowski (1997) best fits the measurements made at

sea.

6.1.1 Carrying capacity

Average NPP places an upper limit on the carrying capacity of marine ecosystems: the

amount of production by predators such as fish, shellfish, marine mammals, and

seabirds that can be sustained in the long term. There is significant complexity in the

relationship between NPP and predator abundance. Organic matter produced by

phytoplankton is not directly consumed by these higher predators. Instead, a range of

organisms, including zooplankton, link phytoplankton to higher predators through the

ocean food-web. These linking organisms have varied life histories which affect the

number and type of predators that can be supported by a given amount of NPP.

Nevertheless, large scale changes in NPP due to oceanographic regime shifts would

significantly affect New Zealand’s marine ecosystems and fisheries, so that

monitoring NPP is an important component in ecosystem-aware fisheries

management.

6.1.2 Primary production around New Zealand

Net primary production is high close to the New Zealand shore (within 80 km in

Figure 6). Results using satellite methods can be inaccurate near land so these

production rates should be treated with caution. In the open ocean, NPP is highest to

the east of New Zealand in the Subtropical Front where subantarctic and subtropical

waters mix together. There is a clear seasonal cycle in NPP for the New Zealand

region (Figure 7). Highest production rates occur in spring when warming stabilises


the surface layer of the ocean. Long-term changes in average PP over the New

Zealand region are small and variable. There is a suggestion of a 1% per year decrease

on average, with a realignment occurring in mid-2002.

Figure 6. Primary Production (PP) for the New Zealand region estimated from the Vertically Generalized Production Model of Behrenfeld & Falkowski (1997) and based on MODIS satellite ocean colour data. Data shown are the log-average values for July 2002 – October 2006.

6.1.3 Global primary production

On a global scale, high NPP and high fisheries yields go together (see Figure 8). The

central oceans are comparative deserts. Most of the world’s fisheries yield comes from

ocean less than 500 km from land. Conspicuous areas of high NPP (and high fisheries

yields) include the Benguela upwelling system off the west coast of South Africa, the

Chilean upwelling system, European shelf seas, and the Canary upwelling system off

West Africa. Australasian waters generally have low productivity – there are no

extensive shallow continental shelves or upwelling systems, the two features

responsible for the highest productivities around the world. New Zealand sits astride

the Subtropical Front which boosts primary production in the New Zealand region.


100

200

300

400

500

600

700

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

Date

NP

P (

mgC

m-2

d-1

)

-20

-10

0

10

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

Date

Res

idu

al (

%)

Figure 7. Top: Average Net Primary Production (NPP) over the New Zealand region estimated from the Vertically Generalized Production Model of Behrenfeld & Falkowski (1997) and based on two sets of satellite ocean colour data (MODIS: red, and SeaWiFS: blue). Bottom: Change from the average monthly condition.

Sixty-two “Large Marine Ecosystems” have been recognised by a number of

international organisations (Figure 8). NPP in the New Zealand region, as estimated

from satellite data, is just above the global average for these ecosystems, at 24th out of

62. Globally, there are about the same number of increasing trends as decreasing

trends in NPP in the 62 large marine ecosystems over the last decade, with New

Zealand in the middle of the decreasing half.


Figure 8. Global Net Primary Production (NPP) estimated from the Vertically Generalized Production Model of Behrenfeld & Falkowski (1997) and based on MODIS satellite ocean colour data. Data shown are the log-average values for July 2002 – October 2006. White lines indicate boundaries of the 64 “Large Marine Ecosystems” of the world as used by organisations including World Conservation Union (IUCN), Intergovernmental Oceanographic Commission of UNESCO (IOC), and US National Oceanic and Atmospheric Administration (NOAA), and publications including Duda & Sherman (2002).

6.1.4 General conclusions

Net primary production in New Zealand is close to the global average for marine

ecosystems which support significant fisheries. Our ocean productivity is generally

high within Australasia, but low compared with upwelling or shelf-sea ecosystems.

Changes in NPP over the world show a range of (generally small and variable)

changes over the last decade. The suggestion of a small decrease in NPP in the New

Zealand EEZ on average (1%/y) is within the global envelope. The high interannual

variability in the data, lack of validation to date, and relatively short length of the time

series means that these changes should not be considered definitive or likely to

continue. The changes are extremely unlikely to be affected by local New Zealand

human activities, and more likely to be connected to variability in climate-related

processes (see discussion of processes affecting algal blooms, Section 6.2). Validating

the satellite estimates of NPP, monitoring medium and long-term changes in NPP, and

continuing to investigate the climate-ocean-ecosystem processes which may affect

NPP are important to determine if the changes are genuine, and to understand why the

changes may be occurring.


6.2 Algal blooms

Microalgae are tiny, free-floating marine plants. Physical conditions such as water

temperature, light, and nutrients are the main parameters which regulate their growth.

When the conditions are right (e.g., favourable temperatures, optimal light, plentiful

nutrients), these microscopic algae can grow rapidly and build up to very high

concentrations in a matter of days. This population explosion is commonly referred to

as an algal bloom. Most blooms are harmless and contribute to ocean primary

productivity, but a few algal species can be harmful. The build-up of these species,

known as a harmful algal bloom, can cause human illnesses and damage marine

ecosystems.

In New Zealand numerous blooms occur each year. Most happen either in spring or

autumn. Many of these probably go unnoticed. But from time to time some of them

become visible either through strong displays of surface discolouration (Chang 2000,

2003) or because of their direct impacts on marine life and the environment (e.g.,

Chang et al. 1995; Chang 1999; Chang & Ryan 2004).

6.2.1 Observations of short-term ‘climate change’ on algal blooms

In New Zealand there is now ample evidence that major, large-scale, alongshore algal

blooms occurred during periods of “unusual weather” (Chang and Uddstrom 2002).

Most notably these are shorter-term oscillations on scales from a few years such as El

Niño/Southern Oscillation (ENSO) to tens of years such as Interdecadal Pacific

Oscillation (IPO). The IPO has a positive (warm) and negative (cold) state. The

climatic shift to a new state of IPO (from positive to negative values) and interaction

of this with El Niño/La Niña events seems to influence the nature of algal blooms

(Chang and Mullan 2003). Generally, the shift from neutral to either the cold (El

Niño) or warm-phase (La Niña) with a temperature anomaly of 1 to 2°C (either

positive or negative) can occur short-term for a few months to over a year, which may

be exacerbated by a change of IPO state.

Typical El Niño conditions in New Zealand are accompanied by the general

strengthening of westerly winds, and also more frequent and stronger south-westerly

and/or north-westerly winds on the western coast of South Island and north-eastern

coast of North Island respectively. South-westerly winds may drive along-shelf

upwellings on the western coast of South Island (Heath and Gilmour 1987; Viner &

Wilkinson 1987; Shirtcliffe et al. 1990) and north-westerly winds on the north-eastern

coast of North Island (Sharples 1997; Zeldis et al. 1998; Black et al. 2000; Chang et

al. 2003b). Increases in frequency and strength of these winds in spring and summer

are expected not only to strengthen along-shelf upwelling particularly in these two


major coastal systems, but also to contribute to the general cooling of sea surface

temperature (SST) throughout New Zealand (Figure 9). Coastal currents (e.g.,

Westland, East Auckland Currents) might also play a part in driving along-shelf

upwelling (Stanton 1976; Shirtcliffe et al. 1990; Sharples 1997), but little is known

about their role during an El Niño event. Cold, nutrient-rich, upwelled water brought

to the surface from the deeper depth promotes phytoplankton growth and also

contributes to extensive blooms on west and north-east coasts of South and North

Island respectively (Bradford et al. 1986; Chang et al. 2001, 2003b).

Figure 9. January 1998 sea surface temperature (SST) anomaly relative to the 1993-1997 mean – general cooling of SST throughout New Zealand, with plumes of cold-upwelled waters (marked by arrows) detected both on the north-eastern coast of North Island and north-western coast of South Island.

It appears that in the last 20 years or so (in the positive phase of IPO, from 1978-99)

New Zealand experienced stronger and more frequent El Niño conditions than the

previous 30 years (Chang and Mullan 2003). During this period a disproportionately

high number of algal blooms were reported throughout New Zealand (e.g., Cassie

1981; Taylor et al. 1985; Chang 1988, 1999; Chang & Ryan 1985, 2004; Chang et al.

1989, 1995, 2001, 2003a; Rhodes et al. 1993; MacKenzie et al. 1996, 2002). Most

notably a large number of these blooms were either associated with outbreaks of

marine life kills (Taylor et al. 1985; Chang & Ryan 1985, 2004) or shellfish poisoning

(Chang et al. 1995, 1996; MacKenzie et al. 1996) on the northeast coast (Figure 10).

With the exception of the 1983 blooms which were dominated by diatoms, the rest

were dominated by dinoflagellates. In the 1998 toxic outbreaks, increased transports in


the East Auckland Current and East Cape Current were observed (P. Sutton, pers.

comm.) and these were suggested to have contributed to the spread of a marine life

killing dinoflagellate species further south along the central east coast of New Zealand

(Chang et al. 2001).

Figure 10. Major nuisance/harmful algal blooms reported from 1950 to 2002: s, nuisance ‘slime’ events; A-I, other major HAB events. IPO phases (both negative and positive) are marked. (see The Climate Update, May 2000, October 2000, and November 2003 for discussion of the IPO)

Typically, La Niña conditions are accompanied by more frequent and stronger north-

easterly winds and result in warmer than usual surface waters around New Zealand

(Fig. 11). From 1950 to 1980, the warmer than usual conditions during La Niña

appeared to strengthen in the negative phase of IPO (Figure 10) (Chang and Mullan

2003). Warming also leads to thermal stratification and hence water-column stability.

The warmer than usual conditions in coastal waters during La Niña events are

expected to decrease nutrient fluxes from deeper waters into the euphotic zone and

thus slow down phytoplankton growth. These cause phytoplankton biomass

(chlorophyll a) to be drastically reduced around New Zealand, particularly in the two

major coastal upwelling systems in summer (Chang unpubl. data). North-easterlies

could conceivably enhance upwelling on the North Island east coast south of East

Cape, but no data exist to verify this.

Elevated water temperature would affect both the seasonal composition of the

phytoplankton and probably bring the spring/summer-blooming species (e.g.,

favouring dinoflagellates) forward to form blooms in winter/spring. In the past 50

years or so, the most notable outbreaks associated with massive build-up of slime


occurred in late winter and spring, and sometimes in summer during La Niña events

(Chang & Mullan 2003). Some of these outbreaks were associated with a slime-

producing dinoflagellate (MacKenzie et al. 2002) (Figure 10). Another major

dinoflagellate species which was associated with harmful algal blooms (PSP) during

the La Niña event started in winter, extended through spring and ended in early

summer (MacKenzie & Adamson 2000; Chang et al. 2003).

Figure 11. January 1999 sea surface temperature (SST) anomaly relative to the 1993-1997 mean. Warming (marked in arrows) occurred during the 1999 La Niña event in most parts of New Zealand, in particular on the northeast and central east coast of the country.

6.2.2 Projected climate effects on algal blooms in New Zealand

The predicted changes in the New Zealand region are: a temperature rise of approx.

1°C, an increase of westerly winds at higher latitude, south of New Zealand

particularly in winter/spring, and strengthening of north-easterly winds in summer. It

is anticipated that a more “La Niña-like” condition will prevail (Mullan pers. comm.).

As temperature is just one of several factors that regulate growth, temperature as such

may not be the dominant factor in phytoplankton response, in particular if the

magnitude of the rise is predicted to be about 1°C (Roemmich et al. 2007).


Since 2000 the IPO index has continued its downward trend, from positive to negative

(Mullan pers. comm.). It is anticipated that in the next decade or so La Niña events

will become stronger and more frequent if the IPO stays negative. Thus nuisance

‘slime’ outbreaks are expected to occur more frequently in some parts of the country,

especially when the warm “La Niña-like” conditions experienced in the future are

exacerbated by more frequent, stronger, ‘true La Niña’ events. In summer the

predominant north-easterly winds will reduce upwelling and result in warmer than

normal temperature over much of New Zealand. This in turn results in decreased

nutrient fluxes from the deep into the upper water column. Hence in summer very few

algal blooms are expected, in particular in the two major coastal systems on both the

north-eastern and western coast of North Island and South Island respectively.

In the last 50 years or so only one toxic outbreak, dominated by Gymnodinium

catenatum was reported during the 2000 La Niña event (MacKenzie & Adamson

2000; Chang et al. 2003). Given that cysts produced by G. catenatum are now found

virtually in all ports and harbours of the entire North Island (Chang et al. in press), in

the La Niña-like condition PSP blooms dominated by this species are expected to

become more common. Besides the direct effect of elevated temperatures, in La Niña-

like conditions PSP-producing dinoflagellate might bloom earlier (changes in seasonal

succession) and migrate faster to new areas as coastal currents are expected to

strengthen in some parts of the country. It is also likely that this species might spread

to higher latitudes in some parts of South Island (change of biogeographical

boundaries). As increased temperatures often cause increased stratification in the

upper water column which favours dinoflagellates (Chang et al. 2003), it is anticipated

that this group of flagellated phytoplankton could dominate in most of the blooms.

Another common feature accompanied by La Niña is wetter conditions in the north.

Cyst beds and low salinities are probably necessary to initiate the PSP-producing

Alexandrium minutum bloom (Cannon 1989). It is anticipated that in the future La

Niña-like conditions, freshening of nearshore waters might increase germination rate

of cysts of A. minutum, and thus initiate blooms a little more often on the northeast

coast (Chang et al. 1996).

6.3 Vulnerability to invasive species

New Zealand is subject to a continuous influx of foreign marine species arriving

through international shipping (Coutts & Dodgshun 2007), several of which have

already become established in our coastal waters (Cranfield et al. 1998; Willis et al.

1999; Francis et al. 2003). Between 2005 and 2007, more than 430 marine species

(many non-indigenous) were collected from merchant, fishing, cruise and recreational


vessel hulls in NZ ports. These originate from a variety of geographic areas and

climates, and thus it is likely that changing climate conditions will not alter the general

level of vulnerability to bioinvasions. It has recently been suggested that the greatest

effects of climate change on biological communities may be due to differences in

summer temperature maxima and winter minima (Stachowicz et al. 2002). If earlier

projections in this report (Section 5) are reasonable, we may expect an increase in the

number of invasive taxa of tropical and subtropical origin in northern New Zealand.

The corollary of this phenomenon is that the range of cold-temperate invasive species

such as the laminarian kelp Undaria pinnatifida should contract southward (Thornber

et al. 2004).

6.4 Vulnerability to disease and parasites

Warming SST may introduce the possibility of new parasites, diseases and vectors of

disease arriving in New Zealand waters, which may have implications for the fishing

and aquaculture industries as well as the structure of natural systems. In an acidifying

ocean, calcifying organisms will have to devote increasing amounts of energy and

metabolic activity to maintenance of their calcium carbonate shells, making them

more vulnerable to disease and parasites.

Recent reviews indicate trends towards increased frequencies of outbreaks in

invertebrate taxa (Ward & Lafferty 2004). Disease dynamics of marine organisms and

their consequences on population dynamics are not well understood, and in New

Zealand research effort has been focussed primarily on commercially exploited

species and those cultured in the aquaculture industry. Little knowledge is available to

predict the effects of pathogens on habitat-forming taxa.

7. Potential indicators

The following suggestions are given bearing in mind that effective indicators are those

taxa or habitats that exhibit sensitivity to changes over measurable time scales. A

recurring theme in this report is that climate trends are detectable over decadal time

scales or more, whereas natural variability over shorter time scales is high (e.g.

through ENSO events, Pacific interdecadal oscillations, or natural variability between

years). Selecting suitable indicators is an exercise constrained by understanding of the

tolerance of individual taxa to natural variability, and the likelihood of climate-

induced shifts occurring that exceed those tolerance levels. If the rate of climate

change accelerates (as has been predicted), this task will become easier, but a long-


term commitment to consistent monitoring programmes is required if changes are to

be detected and quantified.

7.1 Sea level

Indicators of the impacts of SLR are likely to be localised vertical zonation range

reductions of ephemeral short lived species. These may be most evident at locations

where species are already physiologically stressed due to anthropogenic impacts

derived from for example deforestation, erosion, industrial developments and

agriculture runoff. Determining the magnitude of the effects of SLR in such locations

may however be futile or prohibitively expensive to test because of the difficulty in

establishing relevant controls for valid comparisons.

Seagrass beds are likely to become more fragmented leading to their decline in some

areas. This will be due to a range of potential impacts arising from climate change

including: SLR (as above); reduced light levels resulting from SLR, increased

turbidity (greater wind/wave forces); competition from mangroves; increased

eutrophication from increased runoff leading to increased competition with

phytoplankton and synergistic reductions in light levels; and increased physical

disturbance (Turner & Schwarz 2006, Kemp et al. 2005, Short & Neckles 1999). This

fragmentation will have wider ecosystem impacts leading to changes in macro-

invertebrate abundance and diversity which differ between dense and sparse Zostera

beds (Mills 2006) and also reduced secondary production (Hailes 2006).

7.2 Wind and rainfall

Physical indicators of climate change are likely to be increases in sedimentation and

wave climates (west coast), and decreases in water clarity and salinity (freshwater

flux). These are likely to lead to increased frequency and duration of stratification

events, especially those driven by freshwater flux. Biotic indicators are likely to be

sudden sharp regime shifts (Folke et al. 2004). For example, in Chesapeake Bay, USA,

a benthic primary production system shifted to phytoplankton-dominated primary

production (Kemp et al. 2005). This change can, in extreme cases, lead to anaerobic

dead zones developing adjacent to highly eutrophied discharge points during periods

of stratification (Kemp et al. 2005). Impacts on a few leverage species or ecosystem

engineers (Coleman & Williams 2002) could also lead to trophic cascades. Episodic

sedimentation events have the potential to cause large changes in reef systems with

increasing frequency and intensity, and key structuring organisms such as kina may be

directly impacted at local scales (Walker 2007).


Storms can also affect seaweeds like Carpophyllum flexuosum which prefers more

sheltered conditions. This seaweed has become more abundant in north-eastern New

Zealand in the last 30 years correlated with significant decrease in storm frequency

over that period (Cole et al. 2001; de Lange & Gibb 2000). Increasing severity of

storms could therefore lead to localised reductions of this species in locales

susceptible to the effects of climate change.

7.3 CO2 and acidification

Carbon dioxide increases and consequent lowering of pH will be strongly felt in

surface waters of the Southern Ocean. It is therefore most likely that any effects of

acidification will be felt in calcareous organisms in southern New Zealand, especially

those that utilise aragonite. Potential biological indicators may include coralline algae

on shallow reefs, planktonic pteropod molluscs in the Southern Ocean, and

brachiopods and red corals in Fiordland.

Baseline surveys of calcifying organisms in NZ waters are urgently required. These

should be added to existing time-series studies and, where possible, augmented by

remote-sensing technologies. For example, remote sensing of coccolithophores is now

practical in the surface ocean which offers a mechanism for hind-casting and future

monitoring of spatial and temporal abundance in NZ waters.

Over long timeframes many organisms might be expected to be affected by sustained

changes in pH. Metabolic efficiency and growth will be impaired even in species that

use calcite rather than aragonite. Recent work has shown that pH levels below 7.5 may

be fatal for marine bivalves (Michealidis et al. 2005), so monitoring the health and

shell structure of the cultured mussel Perna canaliculus may provide a simple means

of signalling biological changes brought about by increasing acidity.

However, manganese and iron in the periostracum of a mollusc can act as a defensive

buffer against degradation from acid conditions (Swinehart & Smith 1979). It is

conceivable that increasing seawater acidity may prompt the uptake of these metals by

marine molluscs. However lower pH does also mobilise potentially toxic trace metals

such as aluminium.

In sub-tropical waters (which occupy > 40% of the NZ EEZ) the positive response of

Trichodesmium may be monitored using remote-sensing algorithms tuned to this

species (Trichodesmium is positively buoyant and forms large surface blooms).


7.4 Ocean warming and currents

Although overall ocean warming effects are, according to model runs, less likely to be

strongly felt in northern New Zealand relative to more southern latitudes, the reef fish

fauna of the northland east coast and offshore islands have been demonstrated to be

sensitive to incursions of subtropical water masses (Choat et al. 1988; Francis &

Evans 1993; Denny et al. 2003). Monitoring of these assemblages can give a clear

signal of the relative strength and longevity of these events, which can then be used to

examine effects on habitat-forming components of reef assemblages.

Little is known about reef fish assemblage dynamics in the South Island. The best

sources of information may be available from as yet unpublished marine reserve

monitoring reports that provide a time series of observations at certain locations.

It is well known that the distributions of tunas and large game fish are determined by

the position of warm water masses, although the position of upwellings that

presumably increase productivity and other variables also play a part (e.g. Holdsworth

et al. 2003; Willis & Hobday 2007). Examination of annual and seasonal trends in

catch rates of large pelagic predators from commercial and game fishing records may

provide an overview of large-scale changes in productivity in New Zealand shelf

waters.

Other sentinel species that may prove useful for monitoring purposes for detecting

consistent temperature effects might include cool-water algae such as Macrocystis

pyrifera, which would be expected to disappear from the northern limits of its range.

Long-lived sessile invertebrate species such as corals may provide long-term records

(through growth patterns and chemical analyses) of historical changes in temperature

that may partially mitigate the dearth of long-term monitoring data.

8. Research gaps and priorities

8.1 Summary of future work needed to improve climate modelling predictions at varying spatial and temporal scales

With every new IPCC Assessment Report comes a suite of new GCM output datasets

generated by the latest generation of climate models. The frequency of Assessment

Reports is approximately every 6 years, thus we can expect to update the AR4-derived


projections for New Zealand around 2013. There is still quite a lot of inter-model

variability, particularly at the New Zealand scale. With refinements to and increased

resolution of GCMs this variability is likely to reduce.

The statistical down-scaling methodology (Mullan 2001a) has not changed over the

last 7 years. However, the resolution of the down-scaled data has changed. The

resolution is now 0.05° lat/long (approximately every 5 km), matching the interpolated

“virtual climate station data” resolution (these virtual station data are now used for the

down-scaling compared with a set of 58 temperature and 92 rainfall stations in the

2001 analysis).

A significant development at NIWA is the recent capability to run a regional (as

opposed to global) scale climate model (RCM) for New Zealand. Modern climate

models represent as accurately as possible the conditions and forces which influence

the climate. Our regional model is ‘nested’ inside the UK Met Office’s global model,

but produces much more detailed results over New Zealand. The resolution of the

model is 30 km and the model domain covers most of the EEZ. Recently NIWA used

the model to simulate New Zealand's climate from 1970 to 2000 and found it

accurately reproduced the average regional distributions of temperature and rainfall of

that time.

This year, NIWA produced the first climate change simulations using the RCM for

New Zealand. One of the advantages of a regional climate model (over statistical

downscaling) is that it provides daily or even hourly data – essential for looking at

short, sharp events like intense downpours where we want to know how the return

periods may be changing.

We used a moderately high and a moderately low greenhouse gas emission scenario to

span a reasonable range of possible futures, and ran the model for the 30-year period

2071–2100 inclusive. The results are still being analysed but temperatures rise, heavy

rain increases, and snow cover shrinks under both scenarios. We can feed climate

change model results into riverflow models, notably NIWA’s TopNet, to look at the

downstream implications including flood frequency and intensity, and the effect of

climate change on sedimentation and water quality.


8.2 Ocean warming and currents

8.2.1 Models

The coupled atmosphere-ocean global climate models do not include enough detail to

show the narrow ocean currents that flow around New Zealand. This means that no

quantitative statements about these climatic features can be made at this stage.

However, the model technology is now maturing to the level where the models are

sufficiently accurate and have high enough resolution that detailed examinations of the

predictions around New Zealand would be useful.

8.2.2 Observations

There are a very limited number of time series of ocean data; this is particularly true of

the subsurface. The two longest subsurface time series around New Zealand are

temperature measurements between the surface and 800m along commercial ship

tracks between Auckland and Suva/Honolulu (1987-present) and Sydney-Wellington

(1991-present). It should be noted that neither of these programmes are NZ instigated

nor led, although NIWA has been collaborating since the mid-1990s.

Apart from that, there are sea surface temperature (SST) measurements at two

locations: Leigh Marine Laboratory (University of Auckland) and Portobello (Otago

University) since 1967 and 1953 respectively. High resolution satellite measurements

of SST have been archived in the NZ region since 1989.

Satellite measurements of sea surface height, which are very useful for circulation and

heat content analyses began in 1992. A limitation of these measurements is that they

lack resolution on the continental shelf.

The global programme of drifting profiling floats (Argo) is now providing very

valuable information about the upper 1000-2000 m of the world’s oceans, but

significant coverage in the South Pacific dates back to only 2002, and it is only since

2004 that there has been adequate coverage for detailed analyses. Argo is a blue-water

programme and will not provide information in shelf/coastal regions, but will help to

assess variability and change in oceanic events which drive coastal processes.

There is an even worse lack of chemical and biological time series. There have been

moorings maintained and measurements made at two locations north and south of

Chatham Rise (in subtropical and subantarctic water) since 2000. There has been an


ongoing study of the Hauraki Gulf since 1996 that is starting to provide insights into

the function of shelf systems in that region (Zeldis 2004; Zeldis et al. 2004).

It is almost impossible to fund and maintain time series observations in the current

funding regime. Note that our four longest time series are either supported by student

volunteers or overseas funding. Without collecting time series it is impossible to

assess past changes or make future predictions in anything but the broadest sense.

Unfortunately at least a decade of data is normally necessary to interpret variability

and there is no sign of any commitment to supporting such long-term measurements.

Remotely-sensed data will become more useful (SST, SSH and Ocean Colour).

Unfortunately these data alone are normally not adequate to understand key processes.

The Argo programme will provide much-needed subsurface information (although not

over the continental shelf: i.e. much of the region of interest for ecology, and to date at

least, not chemical or biological).

There is also a total lack of supporting and linking information. As an example, the

warming conditions in the Tasman in the late 1990s provoked interest as to what

impact they could have on the food chain and, in particular, on the hoki stocks which

declined through that time period (Francis et al. 2006). Unfortunately, there were no

data collected on nutrients or biology (e.g. the food chain) through that time period

making any impacts of the physical changes very hard to gauge.

8.3 Mitigation of anthropogenic impacts to build resilience to climate change

Given that most of the changes due to climate change are likely to be exacerbated by

anthropogenic impacts, restoration efforts of keystone species and important habitats

should be given highest priority to build more resilience into ecosystems (Folke et al.

2004) to cope with the effects of climate change. To illustrate the complexities of this

task, we give an example of restoration of seagrass beds in Chesapeake Bay in the

U.S. Restoration of seagrass there, has been hampered by a range of non-linear

ecological feedback mechanisms (Kemp et al. 2005). In an unmodified benthos,

enhanced particle trapping and sediment binding associated with benthic plants

(seagrass, microalgae) help to maintain relatively clear water columns, allowing more

light to support more benthic photosynthesis. Restoration or degradation can be driven

either way by positive-feedback mechanisms. Enrichment creates turbidity, leading to

the decline of benthic plants, allowing more resuspension, decreasing light further

stressing benthic plants. Also, nutrient-enhancement stimulates phytoplankton growth

and their subsequent sinking supports increased benthic respiration leading to anoxia,

which causes more efficient benthic recycling of nitrogen and phosphorus which


supports further algal blooms and so on. Initial seagrass restoration efforts failed

without parallel oyster population restoration. Oysters are reported to provide negative

feedback control on eutrophication by reducing phytoplankton biomass and increasing

water quality, allowing the seagrass beds to recover (Fulford et al. 2007).

These efforts to manage and reverse areas of anoxic conditions and ecosystem

collapse not yet evident in New Zealand, have shown that removal of nutrient and

sediment contamination is not enough to restore communities. Rather, concomitant re-

introduction of keystone species is necessary to provide bio-feedback mechanisms to

reverse the effects of eutrophication and sedimentation to restore biodiversity,

community functions and processes. This will be essential for building ecosystem

resilience to cope with climate change effects. The trophic role of suspension-feeding

bivalves in shallow ecosystems cannot be underestimated, as they can exert both

bottom-up (algal grazing) and top-down (zooplankton grazing) control on the pelagic

food web (Nielsen & Maar 2007).

Soft sediments account for a significant portion (>70%) of shallow (<60 m depth)

continental shelf New Zealand habitats, and these euphotic depths are highly

productive in terms of supporting shellfish and fin-fisheries. After more than a century

of increasingly detrimental fishing practices and ever-increasing anthropogenic

growth, large areas of these soft sediment communities have been severely modified

(e.g. homogenised), by dredging and fishing (Thrush et al. 1995), physical

disturbance, sedimentation (MacKenzie & Adamson 2004) and eutrophication. These

impacts have been so pervasive that there are very few refuges remaining offering

glimpses of these communities in their unmodified state (Pauly 1995; Kirby 2004).

The impact on dependant fisheries is manifest in the cyclical boom and bust of

shellfisheries like oysters (Nell 2001) and scallops, and likely long-term changes in

finfish community compositions and flow-on food chain effects (Handley 2006).

Notwithstanding the general lack of knowledge of marine biodiversity, assemblages,

species biology, and species interactions in New Zealand waters, our confidence in

being able to predict the impacts of climate change is severely limited. For example,

we know very little in New Zealand about the processes structuring rocky reef

communities. One view is that top-down predatory and grazers structure reef

communities which in turn affect fish and invertebrate recruitment and survival. The

alternative hypothesis is that bottom-up processes via nutrient supply and primary

production pathways structure these communities, which in turn are affected by

anthropogenic eutrophication in some catchments. Overseas studies, as illustrated

above, have shown that eutrophication of coastal ecosystems can lead to trophic shifts

away from benthic primary production towards pelagic primary productivity, which in


extreme situations can lead to algal blooms and anoxia especially if the water column

is stratified (Kemp et al. 2005). The antithesis of this model is that predators are

controlling grazers which in turn structure rocky reef communities (Babcock et al.

1999; Valiela et al. 2004). For example, the sea urchin Evechinus chloroticus plays a

disproportionate role in structuring New Zealand reefs (Andrew 1988; Shears &

Babcock 2002) by removing macroalgae (Schiel 1982), which in turn influence

grazing by fishes (Andrew & Choat 1982; Choat & Ayling 1987). Until we know

more about these fundamental processes in New Zealand, we cannot predict the

impacts of climate change.

8.4 Prediction of the effects of climate change – key questions

Understanding and predicting the biological effects of climate change in the marine

environment are to some extent hamstrung by the high degree of uncertainty

surrounding predictions of the variability in primary drivers: sea level, acidification,

wind, current, and temperature. Even so, a series of scenarios based on changes in

these variables would be possible to generate if relationships between them and

specific biological processes were known. Although large-scale correlations have been

identified (e.g. between sea surface temperature and the recruitment of exploited fish

stocks), it is still uncertain which processes operate on which life history stages to

produce the correlations. The only exception is that of snapper Pagrus auratus

recruitment, which Zeldis et al. (2005) have tied (with very strong correlations) to

better food supplies in warm years, leading to more competent larvae that are less

subject to predation.

Part of the problem is a lack of significant time series data that can be used to monitor

biodiversity and map population dynamics of indicator species to environmental

conditions. Estimates of demography generally exist only for commercially-exploited

species that must be monitored for stock assessment purposes. Marine reserves may

have a key role in monitoring as the only environments not potentially directly

impacted by fishing activities, although at the present time they represent only coastal

habitats at small spatial scales. To be really effective tools they must be implemented

at appropriate spatial scales and represent all habitat types (Willis & Millar 2005).

Fundamental research to building resilience and managing and restoring of inshore

habitats includes addressing:

1. Determining key species and their ecosystem services required to restore or

build resilience into ecosystems to better cope with climate change in a New

Zealand context, by comparing impact and non-impact sites


2. What are the thresholds of stress for direct/indirect effects (tolerance ranges)

that tip the balance for keystone species?

3. Determine the requisite recovery timescales and size of reserve/fishing closure

areas needed to effectively restore key species/ecosystems to manage effective

restoration.

This knowledge will provide managers with better tools to manage inshore coastal

communities and dependent fisheries to ensure appropriate use whilst preserving

community stability to cope with climate change.

In terms of making predictions and constructing scenarios that can assist risk

assessment and environmental management in the face of climate change over the next

century, the following research questions should be addressed:

• Which species are most at risk, and consequently, which functional groups

and ecosystems are most sensitive?

• What is the baseline against which any changes can be assessed? That is,

what is the range of natural variability in physical and biogeochemical

systems at the present time?

• What are the natural tolerances of key species and/or major taxonomic

groups to changes in various predicted stressors to provide scenarios in

impact prediction?

• What are the rates of change in key ecosystems and what is the adaptive

potential key groups have to varying rates of change?

• How do the expected changes impact on the diversity, species mix,

population dynamics and functionality of large scale biogeochemical

processes, including primary productivity?

• What interactions might occur between climate-related stressors and the

energetic budgets of marine species and ecosystems?

• How might existing sources of anthropogenic disturbance interact with

projected climate changes to exacerbate problems?


• How vulnerable are New Zealand’s economic activities in the marine

environment – especially wild fisheries, aquaculture, and tourism – to

climate change in the short to medium term?

• Can local anthropogenic impacts be meaningfully separated from the

direct effects of climate change? And if not, should resilience

building/mitigation of potential impacts be more important priorities?

Although climate change is a gradual process that occurs on decadal time-scales, one

of the likely effects is an increase in the frequency of extreme events: abrupt changes

in weather systems that have immediately measurable consequences (Jentsch et al.

2007). These are evident on land, but may not be quite so apparent in marine systems.

At large scales, sudden shifts in marine current systems can alter whole ecosystems

(Francis et al. 1998; Anderson & Piatt 1999). Possibly one of the most rewarding

approaches to obtaining empirical estimates of the potential effects of warming New

Zealand seas may be to institute a monitoring programme aimed at quantifying the

variability brought about by La Niña events. Although the effects of ENSO

oscillations tend to be short term (one to two years), changes seen in present day La

Niña conditions may represent mean conditions in 50-80 years. Key systems for

monitoring purposes might include, for temperature change: east Northland and the

Hauraki Gulf in the north, and Tasman/Golden Bay in the south; for acidification:

Fiordland and Stewart Island systems, with emphasis on calcareous organisms; for

sedimentation: representative rocky reefs throughout the country, shallow soft

sediment systems in enclosed waters subject to high anthropogenic inputs, soft

sediment systems on the exposed west coasts of both North and South Islands; for sea

level effects: mangrove and seagrass dynamics. Over shorter time frames,

experimental manipulations of sediment influx events on reef fauna (e.g. Schiel et al.

2006), mechanical stress on algae and sessile animals expected under severe storm

conditions (Hurd 2000; Harder et al. 2006), and varying light regimes on productivity

of algal assemblages may prove fruitful. These experiments need to examine the

cumulative effects of varying frequencies of extreme events to determine the resilience

of our systems.

Our success in mapping biological mechanisms to large-scale correlations will

probably improve by refining the spatial resolution of individual environmental

studies. This means that detailed environmental data must be collected at local scales,

including sea temperature, wave heights, tidal heights, current patterns and interannual

or seasonal variability in current strength, upwelling systems, and primary and

secondary productivity. Detailed monitoring effort spread throughout the New

Zealand EEZ will give much more confidence in our ability to face future change and


deal with its consequences. We need to keep in mind the extent to which coastal

processes and events are driven by large scale oceanic influences, and maintain studies

which enable a better understanding of these surrounding oceanic drivers.

Research priority should be given to initiating long-term monitoring studies for those

oceanographic features for which data are currently lacking, and for characterising

biological assemblages and their natural variability at a national scale. Such a

programme is open-ended by nature and does not have specific goals, and thus will

not meet the criteria usually imposed for short-term research funding. It is, however,

imperative to possess such data if shorter-term experimental work is to be validated,

and to interpret the changes brought about by climate change so that effective

management interventions can be implemented, where warranted. Time series data in

the natural environment usually do not begin to have predictive power before at least

ten years have elapsed, but do provide information that forms the basis of more

specific experiments of shorter duration. Predicted climate changes over the next few

decades are relatively small, and thus are difficult to simulate effectively in

manipulative experiments. A first step would be to collate and coordinate existing

monitoring and measurement programmes with a view to identifying critical gaps.

Priority for short-term experimental work is likely to be driven by feasibility, but

should be concentrated on determining the effects of likely known impacts (e.g.,

temperature, pH, sedimentation) on influential taxa within different biomes.

Identification of these taxa is critical to progress in determining future ecosystem-wide

effects of incremental changes in climate.

9. Conclusions

There is considerable uncertainty not only in the direct consequences of

anthropogenically-induced (or anthropogenically-accelerated) climate change in the

marine environment, but also in the range of biological responses and tolerance to the

predicted changes. We are constrained to a large extent by limited knowledge of the

responses and tolerances of key species to changing environmental conditions as well

as a poor understanding of existing ecosystem dynamics. The dynamics of relatively

well-studied species are still not predictable with regard to changing climatic

conditions. For example, evidence linking the population dynamics of commercially

exploited fish species with large scale climate variability is generally still indicative,

rather than predictive in the New Zealand region (e.g. Francis et al. 2006; Willis et al.

2007). This situation arises partly because of strong interannual variability between

variables (e.g. in recruitment strength, weather patterns), meaning that correlations

often only appear on decadal time-scales for which time-series of suitable data are


rare. This variability is added to by unmeasured variance – many of the drivers of a

species population dynamics operate on smaller spatial scales than can be easily

measured. For example, a fish population may have a strong year class at the

population level because of a chance encounter between larvae and a patch of plankton

sustained by a short-term, local upwelling event. Temperature per se may be

positively correlated with many biological phenomena only indirectly.

In some cases, negative effects of climate change caused by one factor may be

counterbalanced by changes in another. For example, drowning of mangrove forests

by rising sea levels may be offset by increased rates of sediment accretion brought

about by terrestrial flood events. The likelihood of local extirpation of a particular

species will therefore vary at local scales that are much smaller than the limits of

current climate models. It is thus difficult to suggest whether particular areas are likely

to be more or less prone to major ecosystem shifts.

Some general predictions can be made at larger scales, however. The increasing

likelihood of drought in eastern regions along with a higher incidence of extreme

weather events indicates that eastern coasts are likely to be subject to episodic inputs

of terrestrial sediments. These will smother coastal shelf habitats. Whilst work in

Northland has shown that episodic sediment influxes can have large effects on

estuarine systems (Thrush et al. 2003, 2004), little experimental work has dealt with

sedimentation effects on coastal reefs or deeper soft-sediment systems (Airoldi 2003),

and less still is known about recovery rates.

Northern New Zealand is likely to be subject to a strengthening of the East Auckland

Current that should establish a greater number of tropical or subtropical species in the

region. Many of these species currently occur as vagrants in La Niña years or recruit

seasonally but do not form breeding populations. This area will also become more

vulnerable to human-mediated invasions of exotic species from warm biomes, but will

become less vulnerable to invasion from colder-water invasives such as the kelp

Undaria pinnatifida.

General southward shifts in species ranges are expected. Species with cooler water

affinities will become locally rare or extinct in the north. Major oceanographic

features are not expected to change position, but will strengthen or weaken depending

on large-scale ocean climate.

The general and limited nature of these predictions highlights not only the paucity of

climate change-directed research on marine organisms, but also the lack of

understanding of ecological processes and systems at the present time. Experimental


work on key organisms is needed to make long-term predictions of how marine

ecosystems are likely to change in the medium to long-term. Indications are however

that warming scenarios will induce stressors that in the short term (ie the next 50

years) may not have large effects on their own, but may act in synergy with those

existing at the present time to exacerbate current impacts on the marine environment.

These include:

• fishing, which acts directly through removal of biomass, and indirectly

through modifications to habitats (Jennings & Kaiser 1998),

• pollution, including terrestrial inputs of nutrients (especially from farming) or

point sources of contamination (e.g. from heavy industry),

• sedimentation from terrestrial sources brought about primarily by changes in

land use (especially deforestation) and landscape modification through urban

development, agriculture, mining, or road construction.

• modification of coastal morphology through construction of structures such as

piers, or anti-erosion measures like breakwaters and seawalls.

• introduction of exotic species through human vectors such as shipping.

• The southern spread of more warm water invasive species including disease

causing species.

The most effective measures that can be taken at the present time to mitigate the

potential effects of climate change are to minimise those impacts that might reduce the

resilience of existing ecosystems. Following the above categories, immediate actions

may include:

• Reducing total allowable catches in fisheries to diminish the risk of stock

collapse due to recruitment failure3, improving the selectivity of fishing gear

to reduce bycatch, and seeking alternatives to contact fishing gears,

• Taking measures to reduce nutrient and sediment inputs to coastal ecosystems

via terrestrial watersheds,

3 Note that some exploited stocks may benefit from climate change and may not require precautionary management intervention.


• Stabilisation of erosion-prone catchments through reforestation, appropriate

land use, and ensuring the effectiveness of sediment traps put in place

downstream of earthworks,

• Limiting coastal development, and ensuring that coastal protection measures

do not simply displace wave energy to other vulnerable locations,

• Maintaining vigilance in biosecurity: including increased surveillance, efforts

to predict likely invasive taxa, and understanding of likely ecosystem

consequences of new introductions.

Many of these measures will have economic and social consequences, and cost/benefit

analyses are required to determine their likely efficacy under changing environmental

and economic scenarios.

In this report we have put forward some of the possible changes to the New Zealand

marine environment expected under current climate change scenarios. At the same

time, it is apparent that we lack much of the knowledge needed to make specific

predictions at scales at which appropriate management measures can be taken. This

stems from three main gaps in marine ecological research: 1) the lack of long-term

time series of data with which to establish correlations with past environmental

fluctuations; 2) a limited understanding of the way ecosystems are structured by

interactions between species and their environment; and 3) little information on the

tolerances of habitat-forming species to variability in the environmental factors that

may be affected by climate change. Recent efforts to construct a geographically

explicit marine classification in the New Zealand region (Snelder et al. 2007) may,

with model refinement and more data input, provide a basis for assessing large-scale

biogeographical shifts associated with climate change.


10. Acknowledgements

For the Primary Productivity section (6.1): Data used courtesy of Oregon State

University “Ocean Productivity” project. SeaWiFS data used courtesy of NASA and

Geoeye Inc. MODIS data used courtesy of NASA. This work relies significantly on

funding from the Foundation for Research, Science and Technology project

(capability fund project CRCM063: “Bio-optical properties and productivity

algorithms”, and “Ocean Ecosystems: Their Contribution to New Zealand Marine

Productivity” C01X0223).

We thank Dr Richard Feely (NOAA, Seattle, USA) for permission to reproduce

Figures 3 and 4.

We thank Kim Currie, Janet Grieve, Caroline Hart, Rosie Hurst, and Alison

MacDiarmid for contributing materials and discussion. Helpful comments on the draft

report were provided by Russell Cole, Ken Grange, Clive Howard-Williams, Alison

MacDiarmid and Don Robertson.


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12. Appendix 1: Projected climate change over the New Zealand landmass

Figure A1. Projected changes in annual mean temperature (in °C) relative to 1990.


Figure A2. Projected changes in seasonal mean temperature (in °C), for the 2030s relative to 1990: middle of IPCC range


Figure A3. Projected changes in seasonal mean temperature (in °C), for the 2080s relative to 1990: middle of IPCC range


Figure A4. Projected changes in annual precipitation (in %) relative to 1990


Figure A5. Projected changes in seasonal precipitation (in %), for the 2030s relative to 1990: middle of IPCC range


Figure A6. Projected changes in seasonal precipitation (in %), for the 2080s relative to 1990: middle of IPCC range

Documents

Climate change and the New Zealand marine environment · Climate change and the New Zealand marine environment 1 1. Introduction 1.1 Preamble This report forms a summary of the likely