1

APPENDIX

Record-low primary productivity and high plant damage in the Nordic

Arctic Region in 2012 caused by multiple weather events and pest

outbreaks

A1. Supplementary data and methods

Meteorological observations from Norwegian weather stations were retrieved from the Norwegian

Meteorological Institute’s online database Eklima. Temperature data in figure 2b are means from the

stations Bardufoss, Skibotn, Dividalen and Tromsø (all Troms County), and snow data are from

Bardufoss, Ura in Lyngen and Tromsø (snow data not recorded at the stations Skibotn and Dividalen,

but Ura is close to Skibotn and representative for this part of Troms). Filled circles in figure 2e are

from the weather station Čouvdatmohkki (Finnmark County). The regional meteorological data

presented in figure A.1 were developed by the Norwegian Meteorological Institute (Hanssen-Bauer

2005).

A1.A. Modelled snow profiles

We used the SURFEX/ISBA-Crocus multilayer snow model (Vikhamar-Schuler et al 2013, Vionnet et al

2012) to assess the development of the snowpack for two selected sites in the NAR during the

2011/12 winter season. The sites are Holt (Troms County) and Kautokeino (Finnmark County).

Multilayer snowpack diagrams of the liquid water content (percentage) in the snow and snow density

(kg m-3) are presented for both stations. Forcing data for these simulations were observations from

the weather stations at the two sites: temperature (Holt, Kautokeino), precipitation (Holt,

Kautokeino), relative air humidity (Holt, Kautokeino), surface pressure (Kautokeino), wind speed

(Kautokeino) and wind direction (Kautokeino). The remaining variables not observed at the stations,

2

but needed for the model simulations, were extracted from the numerical weather prediction model

Harmonie cycle 36 h1.1. This includes incoming short- and long-wave radiation for both stations, in

addition to surface pressure, wind speed and wind direction for Holt. The Harmonie model includes

Arome physics and the forecasts are produced at 2.5 km spatial resolution (Seity et al 2011).

A1.B. Field surveys of vegetation damage

Winter freeze injuries

Surveys made shortly after snowmelt indicated extensive winter damage to evergreen plants,

especially in areas that had a shallow snow cover during the preceding winter. These injuries were of

fresh origin, as they had all the leaf characters intact, except the colour, and some leaves were still

partly green. Literature descriptions of leaf injuries (Bokhorst et al 2009, Sakai and Larcher 1987,

Sinclair and Lyon 2005, Gunthardt-Goerg and Volleweider 2007, Bjerke and Tømmervik 2006, Rixen

et al 2012) were used to validate these as winter freeze injuries. Detailed field analyses were made in

areas dominated by evergreen plants along a coast-inland gradient in Storfjord, Troms County,

Norway. At each location, damage on stand or plant level was assessed every 50 m along transects

from the coast or valley floor to the valley slopes. The length of the transect depended on the width

of the valley, but typically covered 500 m. Damage was estimated to the nearest 10% for all observed

evergreen species. At two locations in Storfjord, permanent plots were marked out to be used in

monitoring the recovery of crowberry-dominated heath.

In addition to the detailed analyses within this area, damage ratios were also assessed at

numerous other sites in the NAR that were visited during the growing season of 2012; see filled

triangles in figure 1. These are widely scattered sites that were visited primarily for other purposes,

but contribute to explaining the geographical range and severity of winter freeze. NDVI values were

retrieved from most of these sites. The size of each site varied with time available and the uniformity

of the landscape. The range was from 100 m2 to 1.5 km2.

3

Some sites with winter damage were assessed in 2013. This was possible, because wilted

evergreen leaves remain on the branches for years, and differ from freshly-wilted leaves by

becoming greyish and wrinkled. Thus, placement on the branch, colour and micromorphology prove

useful to state which year the damage took place.

Summer frost damage

Preliminary surveys suggested that summer frost had damaged plants with new leaves in lowland

valleys and open sites both in oceanic and inland areas, but mostly so in inland valleys. A double-

gradient design was applied to cover the regional variation (coast-inland) and the local variation

(lowland-upland). Four locations along the coast-inland gradient were studied. At each location,

injury rate was assessed from the valley floor and up along the valley slopes until no more damage

was observed or none of the focal species were present. Focus was on the two fern species ostrich

fern (Matteuccia struthiopteris) and lady fern (Athyrium filix-femina), which are dominant species on

the forest floor on eutrophic mull soil in the western parts of the NAR, but becoming sporadic further

inland (Hultén and Fries 1986, Tigerschiöld 2000). On the valley floor and for every 20-30 m elevation

along the slope, plots of 2 m × 2 m were selected including one or both ferns. Each individual consists

of a high number of fronds which grow from the same base. The degree of damage of each frond was

characterized according to the following categories:

A. Healthy. Frond is green without any bleached (yellowish) or wilted (brownish) parts.

B. Partly affected. Frond is yellowish, especially at the tips, while greener towards the base.

Some tips might be slightly wilted.

C. Strongly affected. Frond is yellowish to pale green along the stem, while tips are mostly

wilted and brown.

D. Severely affected. Most of the frond is wilted and brown, with hardly any chlorophyll left, not

even towards the base.

4

In figure 5a, the categories B, C and D for both species are summed. Results for all four categories

are presented below. Each plot was photographed from above for documentation. Damage to

accompanying plants in or near the plots was also estimated.

The four locations studied were Tønsvikdalen (69°44’8’’ N 19°10’39’’ E; site 1 in figure 5a),

Lavangsdalen (69°24’15’’ N 19°16’46’’ E; site 2 in figure 5a), Takelvdalen (69°6’48’’ N 18°51’33’’ E; site

3 in figure 5a), and Dividalen (68°54’11’’ N 19°32’3’’ E; site 4 in figure 5a).

In addition to the detailed analyses along this coast-inland gradient, damage ratios were also

assessed at numerous other sites in the NAR that were visited during the growing season of 2012.

These are widely scattered sites that we visited primarily for other purposes, but which contribute to

explaining the geographical range and severity of summer frost damage. From these sites NDVI

values were retrieved.

Flood damage to natural ecosystems and agroecosystems

The extreme flood of major watercourses in the NAR in mid-July 2012 (figure 2f) caused damage to

an estimated area of 16 km2 (i.e. 160 km of watercourses with an average width of 100 m). After

return to normal water levels, vegetation along the watercourses was investigated. At four sites

detailed analyses were made along transects from the riverbank at normal water level to unaffected

ecosystems above the flood level. The sites are Divielva (68°50’46’’ N 19°34’27’’ E), Øverbygd

(69°0’53’’ N 19°18’58’’ E), Kirkesjord (68°53’18’’ N 19°3’11’’ E) and Riva (68°58’34’’ N 18°55’24’’ E). At

every 10 m distance from the riverbank the relative damage to the dominant trees was assessed.

Damage assessments focused on leaves of remaining trees. Hence, uprooted trees or branches that

had been broken off and transported away with the water were not part of the assessment. In most

cases, there were few or no signs of uprooted trees. The dominant trees are grey alder (Alnus

incana), bay willow (Salix pentandra) and dark-leaved willow (S. myrsinifolia). Damage was estimated

to the nearest 10%. Damage was manifested as discoloured leaves, often on bent trees and snapped

5

branches, which were often completely defoliated. Data on the two Salix species were pooled,

because it was challenging to identify severely damaged individuals to species rank. In addition, the

height of flotsam in the trees was noted, indicating how much of the trees were submerged during

the flood. Notes were also made on damage to other plants.

Much of the flooded area was agricultural fields, and farmers reported in national media on

complete loss of harvests, because the flood either uprooted the crops or deposited large amounts

of flotsam rendering the grass useless as forage for sheep and cattle. Time series on agricultural

yields were retrieved from publicly available statistics (Statistics Norway 2014). As data are on county

level, reductions from the average yield to 2012 are not only due to flood damage, but also due to

the other disturbance events reported here. Time series on claim settlements to farmers were

retrieved from publicly available statistics (The Norwegian Agricultural Authority 2014). Data relevant

for the Norwegian part of the NAR are summarized below.

NDVI values presented in figure 6b were retrieved from an area of 37 km2 comprising the rivers

Divielva, Målselva, Rostaelva and Kirkeselva, including the four field sites.

Biogenic damage to willow trees

At some sites in the NAR extensive damage to willow trees (Salix caprea, S. myrsinifolia) were

recorded. We observed three types of injuries. Willow rust (Melampsora epitea) had large outbreaks

in inland valleys causing premature autumn coloration of willow trees. The bud-mining

microlepidopteran Argyresthia retinella had a large outbreak, probably the largest in the region since

1995 (Tenow et al 1999), also attacking willow, causing wilting of branch tips and leaves, as described

in the literature (Tenow et al 1999, Robbins 1992, Elverum et al 2003). It also had strong negative

impacts on birch in the region, but birch was even more affected by leaf-defoliating moths; see figure

7a. The leaf-defoliating larvae of the beetle Chrysomela lapponica were observed attacking dark-

leaved willow (S. myrsinifolia), in particular. The injury rates of willow green parts caused by these

6

three pests were assessed in the field on selected sites in Troms County. Damage was assessed to the

nearest 10%. Results are presented below.

Wind-borne salt spray damage

Extensive wilting of birch leaves was observed in two widely dispersed coastal areas in the NAR

(figure 1). Leaves were completely brown, crumpled and had visible accumulation of salt crystals and

had no signs of attacks from fungi or insects. Using available literature (Sinclair and Lyon 2005, Dirr

1976, Appleton et al 1999, Griffiths and Orians 2003, Griffiths 2006, Beckerman and Lerner 2009),

salt spray was validated as the agent for this damage.

Damage was observed shortly after a storm event. Wind data from the meteorological station at

Honningsvåg (71°0’38’’ N 25°58’41’’ E) show that 21 July 2012 was the summer day (June-August)

after 2000 with the strongest mean wind speed with a value of 18.4 m s-1. The strongest wind gust

that day had a speed of 28.7 m s-1. Wind direction was towards the land area where crumpled birch

leaves were recorded. This station is ca. 38 km from the nearest site of observed salt spray-damaged

birch and is representative of this region. Other stations along the coast also recorded strong winds

in the second half of July as seen from data retreiced from eKlima (Norwegian Meteorological

Institute 2014). Thus, it is likely that much seawater was transported to coastal terrestrial sites.

We assessed the extent of damage from salt spray in the field and correlated these data with

NDVI from the affected area. Data are presented below.

A1.C. Field monitoring of geometrid moth outbreaks and effects on plants

Densities of geometrid moth larvae belonging to the species Epirrita autumnata (autumnal moth),

Operophtera brumata (winter moth) and Agriopis aurantiaria (scarce umber moth) are monitored

annually at 244 sampling stations distributed over 15 different mature birch forest localities in

7

coastal Troms (Ims et al 2004, Jepsen et al 2008, Vindstad et al 2013). All three moth species have

spring feeding larvae that emerge in approximate synchrony with budburst. Birch is the main host

tree for all three species in this region, although other deciduous tree species are affected when

present, in particular during mass outbreaks (Jepsen et al 2013). At three localities (Skogsfjord,

Reinøy, and Storelva) monitoring is done along four approximately 2-km long transects running

parallel at four altitudes from the coast to the tree line. Each transect contains 10-12 sampling

stations (40-44 stations per locality). At the remaining 12 localities monitoring is restricted to a single

transect at approx. 100 m altitude (10 stations per locality). Density estimates are timed to match

larval phenology (3rd-4th instar) to ensure comparability between localities and years. At each station,

the total number of larvae of each species is counted on 10 arm-length branches selected from 10

different trees. Density estimates given in the analysis are sampling station totals (e.g. per 10

branches). See Ims et al (2004) and Vindstad et al (2013) for further details on sampling design and

methodology.

Special attention was also given to an upland outbreak area in Swedish Lapland (Rikgsgränsen-

Abisko area). This outbreak was briefly described recently (Callaghan et al 2013, Olofsson et al 2013).

Near-ground NDVI retrieved from images of affected and unaffected plants were compared. Images

were taken with a handheld passive proximal sensor, viz. a Maxmax-modified Canon camera (LDP

LLC, Carlstadt, NJ, USA) where an infrared sensor replaced the normal sensor, the blue channel

recording the visible light and the red channel the near infrared (Bokhorst et al 2012b).

The MODIS-NDVI time series data presented in figures 7b-c were retrieved from the intensively

studied coastal and upland sites described above.

8

A2. Supplementary results and discussion

A2.A. Recorded climate extremes

Several extreme values were recorded during the water year from October 2011 to September 2012.

Here follows a chronological summary of these extreme records.

Warm autumn

Figure A.1. Mean autumn temperatures in North Norway from 1900 to 2011.

As E-OBS data show, October-December 2011 was the warmest Oct-Dec period in the NAR after the

turn of the millennium (figure 2a). The Norwegian Meteorological Institute (2013) and the Swedish

Meteorological and Hydrological Institute (2013) report that October was unusually warm and wet in

the NAR; that November had the highest mean monthly temperature ever recorded for Norway as a

whole; and for North Norway (figure A.1); that Sweden also had record warm temperatures; and that

December in the NAR was also much warmer than the norm.

9

Vardø Station, situated in the eastern parts of the NAR, experienced the warmest mean monthly

December temperature ever recorded since the start of meteorological observations in 1866

(Norwegian Meteorological Institute 2013).

Winter extremes

In the NAR, January was dry, with numerous stations receiving the lowest amount of precipitation

ever recorded (Norwegian Meteorological Institute 2013, Swedish Meteorological and Hydrological

Institute 2013). This led to extremely shallow snow depths (figures 2b, A.2), at the end of the month

most parts of North Norway having less than 50% of normal snow depth, and some coastal areas

having less than 10% of normal snow depth (Norwegian Water Resources and Energy Directorate

2013). The dry and snow-poor conditions continued in February (figures 2b, A.2). On 3 February,

−42.7 °C was recorded at the station Kvikkjok-Årrenjarka, Swedish Lapland, which is the coldest

temperature ever recorded at this station with observations starting in 1888 (Swedish

Meteorological and Hydrological Institute 2013). At a period with very shallow snow depths (6

February), extreme low temperatures were recorded in large parts of the NAR (figure 2b), with at

least two stations on the Norwegian side with new February minimum records (Norwegian

Meteorological Institute 2013), Sweden experiencing the coldest temperature recorded since 2000

(Naimakka: −42.8 °C; Swedish Meteorological and Hydrological Institute 2013). Several other stations

also experienced one of the coldest February days ever recorded, as evidenced by searching the

extreme statistics database at eKlima.

10

a b

c d

Date Date

Figure A.2. Modelled snowpack development at two selected sites in the NAR during the winter of

2011-12. (a-b) Liquid water content (%). (c-d) Snow density (kg m-3). a and c: Holt, Troms County

(coastal); b and d: Kautokeino, Finnmark County (continental). Black line: Average snow depth based

on daily observations from 2000 to 2011. Grey line: Snow depth in 2011-12. Discrepancies between

modeled and observed snow depth are possibly due to deviations between the snow characteristics

at the observation point and the larger surrounding area; the modeled depth being representative

for the latter. Note that snow depth was much lower than the average at the coastal site (observed

depth declining to zero in late January-early February) than at the continental site. At the end of the

winter season the situation was opposite with larger snow amounts than the 2000-2011 average at

both sites.

Only a few days later (11 February), south-westerly winds brought warm weather to the NAR

(Swedish Meteorological and Hydrological Institute 2013), with many of the same stations

experiencing extreme cold temperatures on 6 February having one of the warmest February days on

record (Norwegian Meteorological Institute 2013, 2014). For example, the meteorological station

11

Dividalen (continental parts of Troms County, Norway) experienced a temperature increase from

−34.0 °C on 6 February (the coldest February temperature in an observations series starting in 1939)

to +7.6 °C on 11 February (27th warmest February temperature), viz. a temperature increase of 41.6

°C. Such extreme temperature increase over a few days was not found for any other periods at any

inland stations available at eKlima, but an extensive analysis involving all stations in the NAR was not

made. At coastal stations, minimum and maximum temperatures were also extreme, but the range

was much lower. For example, at the station Vågønes (Nordland County, Norway) temperature

increased by 20.2 °C from −13.6 °C (third coldest February record since 2002) to +6.6 °C (seventh

warmest February record since 2002). The warm spell caused a further reduction of the already

shallow snow cover (figures 2b, A.2), and the remaining snow became very hard after refreezing

(figure A.2).

From 11 February until the end of March temperatures continued to fluctuate widely, causing

many freeze-thaw cycles and fluctuations in snow depth (figure 2b). At the end of the month, snow

depth was still less than 50% of the norm in most parts of North Norway and less than 10% of the

norm at coastal sites (Norwegian Water Resources and Energy Directorate 2014).

Spring and summer temperatures and snow cover

While the area of the NAR covered by snow was less-than-normal until March, much precipitation in

April led to a higher-than-normal SCF in mid-April (figure A.3). A warm period in late May and early

June led to increased snow melt, but return to unusual cool temperatures from mid-June again led to

extremely high SCF (figures 2e, A.3).

12

Figure A.3. Evolution of snow cover fraction from April to August 2012 (black line) and compared

with average snow cover fraction for the period 2000-2011 (stippled line) and minimum and

maximum for the same years (grey shading).

Only a few meteorological stations within the area have long observation series of hourly

minimum temperatures. Thus, it is challenging to evaluate how extreme the observed frost nights

were, especially since the cool night temperatures are often associated with clear sky and hence

warm noon temperatures, thereby masking the cool night temperatures in daily mean temperature

records. Summer frost occurs during clear nights due to radiational cooling, causing a layer of cold air

to form at ground level and often not accumulating to more than a meter (Sinclair and Lyon 2005).

Hence, sensors at 2 m above ground, which is the standard height for meteorological stations, give

less extreme readings than sensors closer to the ground. The frost event from 15-19 June gave

13

record-low minimum temperatures in the western parts of the NAR; for example the minimum

temperature at the coastal station Evenes (Nordland County, Norway) was +2.2 °C on 16 June, which

is the lowest midsummer temperature (15 June-15 July) recorded in the observation series starting in

1985. A station slightly south of the NAR (Meråker, Nord-Trøndelag County, Norway) had a minimum

temperature of −0.2 °C on 15 June, which is the coldest midsummer temperature ever recorded

there (observations since 1958). With an inversion gradient of 2-3 °C m-1 elevation, it could imply a

ground temperature between −4 and −6 °C.

The next frost event took place around 28-29 June (figure 2d). Several meteorological stations

recorded frost temperatures during this event, for example Dividalen with −2.4 °C (minimum record

for midsummer, but short observation series), Skibotn (Troms County) with −1.6 °C, and Namsskogan

(Nord-Trøndelag County) with −1.4 °C. Land Surface Temperature showed minimum temperature of

−8.5 °C during this event (figure 2d). This temperature was recorded at four different pixels of 1 km2

along a 12-km stretch in the southern parts of Troms County (Masterbakkelva 68°51’ N 18°1’ E;

Steinsund 68°51’ N 18°3’ E; Frivoll 68°51’ N 18°5’ E; Sætervatn 68°51’ N 18°18’ E). Minimum

temperature records from E-OBS show that this event was first most evident at high altitudes and

latitudes from the mountain plateau Hardangervidda in southern Norway and north-eastwards to the

Norwegian-Russian border area (figure A.4a). On the second day the cold spot had moved north- and

eastwards becoming very striking in central and northern parts of Sweden, Norway and Finland, and

with a tail quite far into southern parts of Finland (figure A.4b). Shortly after this event, severe wilting

of plants became visible (figure 5a).

The strong temperature inversion during these cold nights was evident from observations of

hourly minimum temperatures at 2 m above ground (meteorological code TAN) and 5 cm above the

ground (“grass minimum temperature”, code TGN) at two coastal weather stations; Holt (Troms

County, Norway) and Kvithamar (Nord-Trøndelag County, Norway). Maximum difference at Holt was

7.4 ° at midnight between 29 and 30 June (TAN = 7.6 °C; TGN = 0.2 °C). The night before the

14

temperature difference was almost the same (7.1 °; TAN: 5.4 °C; TGN = −1.7 °C). At Kvithamar the

largest difference was 7.5 °C (29 June, 2 AM: TAN = 7.4 °C; TGN = −0.1 °C).

a b

Figure A.4. E-OBS minimum temperature in northern Europe, including the NAR. (a) 28 June 2012. (b)

29 June 2012. Scale shows surface temperature from −5 °C (black) to 20 °C (white). Sea surfaces are

also shown in black.

The third event took place around 4 July as shown by E-OBS (figure 2d), but freezing temperatures

during this event were recorded at only a few meteorological stations. The fourth event, however,

which occurred around 10 July, led to very low temperatures in the northern continental part of the

NAR, with minimum temperature of −4.1 °C (Čuovdatmohkki, Finnmark County). This was the fifth

coldest midsummer (15 June-15 July) temperature recorded on this station with observations

starting in 1969, the four colder records all from dates in June. The last event around 21 July also

rendered temperatures slightly below freezing (figure 2d), primarily in the northern continental part

of the NAR.

A2.B. Recorded damage to plants in natural ecosystems

The injuries reported in the main article were in most cases visible as distinctive features in the

landscape. Injuries are portrayed in figure A.5. A more detailed summary of the injuries is given here.

15

The NAR NDVI data for 2000-2012 (figure 3) were uncorrelated with E-OBS growing season

precipitation data (linear regression R² = 0.01, p = 0.76). A model selection analysis shows that adding

precipitation rates to the model (in addition to temperature) does not improve fit (r2 change from

0.17 to 0.14). Hence, drought (or excess water) is not a limiting factor for NDVI within the NAR, in

contrast to more continental regions at high northern latitudes (Angert et al 2005, Groisman et al

2007, Zhao and Running 2010, Beck and Goetz 2011, Xu et al 2013).

Browning due to winter weather events

In figure 4a, browning ratios from winter desiccation of all recorded evergreen species are pooled. In

figure A.6, ratios are shown for each species. Of the many evergreen dwarf shrub plants in the NAR,

lingonberry (Vaccinium vitis-idaea) is a species showing high tolerance to winter warming (Bokhorst

et al 2009, 2012a, Callaghan et al 2013). This partly explains the relatively low damage ratio to this

species. Massive winter browning of juniper (Juniperus communis) has occasionally been observed in

Scandinavia (Printz 1933, Kullman 1989, Norwegian Forest and Landscape Institute 2014). This

species is declining in most parts of western Europe (Gruwez et al 2012).

Figure A.5. Reported plant injuries (next page). (a) Winter freeze injury to crowberry heath and

young pine. (b) Winter freeze injury to juniper. (c) Summer frost damage to ostrich fern. (d) Summer

frost damage to aspen. (e) Birch defoliated and crowberry leaves punctured by geometrid moth

larvae. (f) Goat willow defoliated by the bud-mining microlepidopteran Argyresthia retinella. (g) Birch

and pine trees damaged by flooding. (h) Birch damaged by sea salt spray. (i) Dark-leaved willow

defoliated by the beetle Chrysomela lapponica. (j) Goat willow infested by rust.

16

17

Figure A.6. Mean winter desiccation injury to evergreen plants from 50 sites along a winter-freeze

damage gradient. Black columns: high-damage sites; grey columns: low-damage sites. Error bars are

± 1 s.e.m.

Mean growing season NDVI trends from 2000 to 2012 for the sites with much visible damage and

sites with minor to moderate visible damage are shown in figure 5a along with two example sites,

one with much visible damage and one with minor to moderate visible damage in 2012. Winter-

related damage to northern ecosystems are projected to increase as winters are becoming warmer

(Crawford 2000, Bokhorst et al 2009, 2012a, Kreyling 2010, Bjerke 2011, Bjerke et al 2011, Riseth et

al 2011, Callaghan et al 2013). The injuries we report here may therefore become a normal landscape

feature in the near future.

Summer frost damage

Summer frost damage to ostrich fern (Matteuccia sthrutheriopsis) and lady fern (Athyrium filix-

femina) were most severe in valley bottoms (figures 5a, A.7). Numerous other species than the two

ferns reported in the main text, primarily herbs, horsetails and other ferns (figure A.8), and also trees

such as aspen (figures A.5d, A.9), were visibly frost-damaged. Thin-leaved plants such as ostrich fern,

18

lady fern (figures 5a, A.5c), common oak fern (Gymnocarpium dryopteris), beech fern (Phegopteris

connectilis) and wood stitchwort (Stellaria nemorum) were more damaged than species with slightly

thicker leaves, such as stone bramble (Rubus saxatilis) and wood cranesbill (Geranium sylvaticum)

(figure A.7).

Tall aspen trees were only modestly affected (figure A.9), because of the strong inversion effects

during the clear summer nights, which led to warmer air further from the ground. The strong

negative impact on young trees, however, may affect recruitment. Other plants than those

mentioned here also showed signs of summer frost response. This includes bilberry (Vaccinium

myrtillus), whose leaves became reddish in July (figure A.10a) and bog sedges, which became pale

yellow-green in upper parts of leaves (figure A.10b). Intra-season NDVI development of fern-rich sites

known to have been affected by summer frost is shown in figure A.11. These sites are open forests

where the understorey vegetation contributes much to the signal detected by the satellites.

19

Figure A.7. Variation in frost injury to ostrich fern (Matteuccia sthrutheriopsis) and lady fern

(Athyrium filix-femina) with altitude along a coast-inland gradient. (a) Oceanic site (Tønsvikdalen). (b)

Intermediate site (Lavangsdalen). (c) Inland site (Takelvdalen). (d) Continental site (Dividalen). The

lowest altitude for each site represents the valley bottom, while the highest altitudes represent the

uppermost occurrence of these ferns.

20

Figure A.8. Mean summer frost injury to deciduous plants from five sites along a summer ground

frost gradient. Study sites are the four sites studied for summer frost and described in S1.D, and

Skibotndalen, which was a focal area for winter damage surveys, but where also summer frost

injuries were surveyed. The species are the ferns Gymoncarpium dryopteris and Phegopteris

conncetilis (black bars), the horsetail Equisetum sylvaticum (grey bar), and the herbs Stellaria

nemorum, Cornus suecica, Rubus saxatilis, and Geranium sylvaticum (white bars). Error bars are ± 1

s.e.m.

Figure A.9. Variation in summer frost injury to aspen (Populus tremula) with height above ground.

Black bars: Skibotndalen, Storfjord, Troms County (69°19’37’’ N 20°20’54’’ E). Grey bars: Ulveskaret,

Sør-Varanger, Finnmark County (69°39’50’’ N 30°14’59’’ E).

0

10

20

30

40

50

60

70

80

90In

jury

rat

e (%

)

Species

0 20 40 60 80 100

5-6

4-5

3-4

2-3

1-2

0-1

Proportion of wilted leaves (%)

Hei

ght

abo

ve g

rou

nd

(m

)

21

a b

Figure A.10. Premature autumn coloration of plants during July 2012 probably caused by summer

frost events. (a) Reddened bilberry (Vaccinium myrtillus) leaves while berries are still unripe. Also

note the red-spotted leaves of dwarf cornel (Cornus suecica). (b) Tip yellowing of slender sedge

(Carex lasciocarpa).

Figure A.11. NDVI development during the growing season of sites known to have been affected by

summer frost in 2012. Circles: 2012; triangles: maximum greenness observed for 2000-2011; squares:

average for 2000-2011. Error bars are ± 1 s.e.m. where larger than symbols.

0.450.500.550.600.650.700.750.800.850.90

10-25June

26June-3

July

4-11July

12-19July

20-27July

ND

VI

Period

22

Pest outbreaks and sea salt spray damage

Willow rust had a severe outbreak at least in one area in Troms County, the valley Skibotndalen. The

proportion of trees studied that were attacked by willow rust in this valley from the lowland upwards

to the subalpine belt is shown in figure A.12. While up to 30% of the buds of individual willow trees

were infested by the bud-mining microlepidopteran Argyresthia retinella, the worst affected birch

trees had ca. 80 % of their buds infested (data not shown). The overall infestation rate of willow trees

along a transect from Kvaløya to Ramfjorden in Tromsø, Troms County, is shown in figure A.12.

The leaf-defoliating larvae of the beetle Chrysomela lapponica reached high population densities

and consumed large amounts of dark-leaved willow leaves, at least in the Tromsø area, during the

growing season of 2012 (figure A.12). This species is known as a pest on willow in the eastern parts of

the NAR and neighbouring Russian areas (Zvereva et al 1995, Gross et al 2007), but to our knowledge

major outbreaks have not been described from the western part of the NAR previously.

Figure A.12. Infestation rate of the three pests Argyresthia retinella, Chrysomela lapponica and

Melampsora epitea on willow. Error bars are ± 1 s.e.m.

Intra-season NDVI development from the upland site in Swedish Lapland with high densities of

leaf-defoliating moths shows that NDVI declined abruptly during the outbreak (figure A.13). Later in

0

10

20

30

40

50

60

70

Argyresthia Chrysomela Melampsora

Infe

stat

ion

rat

e (%

)

Pest

23

the growing season, NDVI increased again reaching the same level as in a normal year. As discussed

in the main text, this increase is probably due to increased growth of understory grass and herb

vegetation, which was boosted by moth-induced nutrient release and increasing light availability

(Karlsen et al 2013). Growth of new birch leaves, which was observed after the outbreak, may also

have played a minor role for the NDVI increase. This upland site was also affected by night

temperatures close to or below 0 °C (figure A.4). Thus, parts of the decline in NDVI for this area may

be due to frost damage.

The effects of sea salt spray on wilting of birch leaves and NDVI are shown in figures A.14-A.16.

Figure A.13. NDVI during the growing season at the 162 km2 upland site in Swedish Lapland affected

by leaf-defoliating moths. Circles: 2012; triangles: maximum greenness observed; squares: average

for 2000-2011. Arrow indicates approximate start of outbreak.

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

18-25June

26 June-3 July

4-11July

12-19July

20-27July

28 July-4

August

4-12August

13-20August

ND

VI

Period

24

Figure A.14. Injury rate (proportion of wilted leaves) of birch with altitude at two sites affected by

sea salt spray. The sites are Alkeberget, Finnmark County (black bars; 70°32’48’’ N 25°9’21’’ E) and

Sortvik, Finnmark County (grey bars; 70°39’1’’ N 25°23’30’’ E).

Figure A.15. NDVI trend for Sortvik during the growing season of 2012. Only periods not affected by

clouds are included. Arrow indicates time of storm activity.

0 50 100

0-40

40-80

>80

Injury rate (%)

Alt

itu

de

(m)

0.30

0.35

0.40

0.45

0.50

0.55

0.60

0.65

25May-1June

2-9June

10-17June

26June-3

July

20-27July

28 July-4

August

ND

VI

Period

25

Figure A.16. Maximum NDVI at Sortvik for the 8-day period 28 July-4 August during the years from

2000 to 2012. Years much affected by noise from clouds (2002, 2004, 2005 and 2010) during this 8-

day period were omitted.

A2.C. Agricultural yields and claim settlements

Claim settlements paid to farmers in the Norwegian part of the NAR in 2012 were the second highest

during the period from which data are publicly available (figure A.17). One year, 2010, stands out as

exceptional. Long-lasting ground-ice caused much anoxia damage to grasslands in 2010 (table A.1),

and a cold and wet growing season accentuated the problems caused by ice (Norwegian Ministry of

Agriculture and Food 2010). Compared with all others years except 2010, claim settlements in 2012

were 2.4 times higher than the average. Potato yield in 2012 was the second lowest during the

period from which data are publicly available (figure A.18). Only 2010 had lower yields. 2012-yields

were 40% lower than the average yield. Northern agriculture is considered to be positively affected

by climate change, as the temperature sum during a prolonged growing season is projected to

increase (Uleberg et al 2014). However, winter-related damage to farmlands is also projected to

increase (Kvalvik et al 2011, Uleberg et al 2014), and we have reported here how rainstorms and

flooding can influence northern agriculture (figure 6). Thus, farming in the NAR is facing an uncertain

future.

0.30

0.35

0.40

0.45

0.50

0.55

0.60

0.65

0.70

2000 2001 2003 2006 2007 2008 2009 2011 2012

MO

DIS

-ND

VI

Year

26

Figure A.17. Claim settlements paid to farmers in the Norwegian counties Nordland, Troms and

Finnmark. Values are in Norwegian kroner (NOK) and not inflation-adjusted.

Figure A.18. Potato yields in the Norwegian counties Nordland, Troms and Finnmark from 2000 to

2012.

S2.D. Documented disturbance events 2000-2011

Disturbance events known to have occurred within the focal period of this study (2000-2012) are

summarized in table A.1. The water year 2011-12 is not included, as this year is described in detail in

the main text and elsewhere in this supplement.

0

10

20

30

40

50

60

70

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Cla

im s

ettl

emen

ts (

mill

. NO

K)

Year

0

1 000

2 000

3 000

4 000

5 000

6 000

2000200120022003200420052006200720082009201020112012

Po

tato

yie

ld (

t km

-2)

Year

27

Table A.1. Disturbance events known to have occurred in the NAR from 2000 to 2011.

Water

year

Documented disturbance events

1999-

2000

Cold season - Extreme snow depths with very hard snow layers in the snowpack and ground-ice. Hard layers produced during warming events (Norwegian Meteorological Institute 2014, Johansson et al 2011). Warm season - Cool early growing season (Lie et al 2008). Plant responses - Delayed phenology due to cool spring and late snow thaw (figures 2e, 4c).

2000-01 Cold season - Several warming events causing extensive snow thaw leading to ground-ice and hard layers in the snowpack (Johansson et al 2011, Norwegian Institute for Agricultural and Environmental Research 2014). Warm season - A very cool second half of May (Norwegian Meteorological Institute 2014, Lie et al 2008). - Outbreak of lemmings and voles (Callaghan et al 2013, Olofsson et al 2013). Plant responses - The highest MODIS-NDVI recorded for the NAR, despite some known disturbance events (figure 3).

2001-02 Cold season - Very hard snow layers on the ground. An extreme warming event with heavy rainfall in January formed an ice crust in the snowpack (Callaghan et al 2013, Lie et al 2008, Norwegian Institute for Agricultural and Environmental Research 2014). Warm season - None reported. Plant responses - The berry yields of bilberry (Vaccinium myrtillus) and crowberry (Empetrum nigrum) were among the lowest during the period from 1997 to 2008 studied by Finnish researchers (Turtiainen et al 2011). This may be due to winter dieback. - However, second highest MODIS-NDVI recorded for the NAR (figure 3).

2002-03 No known events.

2003-04 Cold season - None reported. Warm season - Spring backlash with frost events as well as rainy and windy weather conditions (Turtiainen et al 2011). - Major outbreaks of geometrid moths in interior birch-dominated valleys (Ims et al 2004, Jepsen et al 2008, 2011). - Outbreak of vole (Olofsson et al 2013). - July rain storm damage to vegetation (Callaghan et al 2013). Plant responses - Bilberry and crowberry yields were low, probably due to unsuccessful pollination (Turtiainen et al 2011). - Large areas of birch forest severely defoliated by moths (Ims et al 2004, Jepsen et al 2008, 2011).

28

2004-05 Cold season - Warming event in mid-December causing ground-ice and rain-on snow in March (Lie et al 2008, Norwegian Institute for Agricultural and Environmental Research 2014). Warm season - Cool May with spring backlash (Bårdsen and Tveraa 2012). - Major outbreaks of geometrid moths, mostly north-east of last year’s core outbreak area (Jepsen et al 2009). Plant responses - Decline in vegetation greenness in parts of the NAR (Jepsen et al 2009, Bårdsen and Tveraa 2012). - Delayed phenology due to cool spring (figure 4c). - High claim settlements to farmers with anoxia-damaged agricultural lands (figure A.17), especially to farmers in Nordland County who had much lower yields in 2005 than normal (Statistics Norway 2014, Norwegian Agricultural Authority 2014).

2005-06 Cold season - Midwinter warming events causing full or partial snow melt and resulting in ground-ice and hard layers in the snowpack (Bjerke and Tømmervik 2006, Jørgensen et al 2010, Johansson et al 2011, Bokhorst et al 2012a). - Very cold late winter, potentially causing high light stress and winter desiccation (Bjerke and Tømmervik 2006, Bokhorst et al 2012a, Norwegian Meteorological Institute 2014). - The storm “Narve” raged along the coast from 17 January to 23 January (Eng 2012). Warm season - A wave of long-range air pollution originating from biomass burning in Central Europe, transporting large amounts of ammonia and ozone to the NAR (Stohl et al 2007, Manninen et al 2009, Karlsson et al 2013). - A warm period in April-May led to a very early start to the growing season (figure 4c) and early snow melt (figure 2f), but was followed by a cool period in mid-May causing snow to accumulate on newly emerged leaves. - Outbreak of geometrid moths in north-easternmost part and along coast of the NAR, including first outbreak of Operophtera brumata (Jepsen et al 2009, 2011, 2013, Vindstad et al 2013). Plant responses - Extensive browning, especially of crowberry heath due to winter damage. Damage confirmed by MODIS-NDVI. Damage mostly restricted to wind-exposed coastal sites (Bjerke and Tømmervik 2006, Bokhorst et al 2012a). - Damage to grasslands due to hypoxic conditions under melting ice in spring, resulting in low hay yields and high claim settlements (figure A.17) (Jørgensen et al 2010, Statistics Norway 2014, Norwegian Agricultural Authority 2014). - Locally, visible leaf damage from exposure to pollutants (Manninen et al 2009, Karlsson et al 2013). - Numerous reports of frost desiccation of Norway spruce (Picea abies), Scots pine (Pinus sylvestris), juniper (Juniperinus communis), birch (Betula pubescens), heather (Calluna vulgaris) and crowberry (Empetrum nigrum), especially in Nordland County, Norway (Norwegian Forest and Landscape Institute 2014). Injuries caused by “Narve”, at some exposed coastal sites probably accentuated by sea salt spray. At some sites also considerable windfelling. - Despite these injuries, this summer had the third highest MODIS-NDVI recorded in the NAR (figure 3).

29

2006-07 Cold season - Mild and wet autumn and early winter with rain falling on snow leading to ground-ice (Riseth et al 2009, Bokhorst et al 2012). Warm season - Outbreaks of geometrid moths and rodents at several sites (Jepsen et al 2008, 2009, 2013, Vindstad et al 2013, Olofsson et al 2013, Ims et al 2013). Plant responses - Unusually strong snow mould outbreaks during snow melt, which probably were triggered by the warm and wet autumn conditions (Bokhorst et al 2012a, unpublished observations).

2007-08 Cold season - Long-lasting warming event in December followed by a long period in January with freezing temperatures and very shallow snow depths, especially at higher altitudes, due to strong winds which removed fresh snow (Bokhorst et al 2009, Norwegian Meteorological Institute 2014, Norwegian Water Resources and Energy Directorate 2014). Warm season - Very cool May and June leading to delayed snow melt (Norwegian Meteorological Institute 2014, Norwegian Water Resources and Energy Directorate 2013). Plant responses - Extensive browning, especially of crowberry heath due to winter damage (Bokhorst et al 2009). - Delayed phenology due to cool spring (figure 4c).

2008-09 Cold season - Many freeze-thaw events in southern parts of the NAR (Norwegian Meteorological Institute 2014). Warm season - Very warm May, but June colder than normal, potentially with spring backlash events (Norwegian Meteorological Institute 2013, 2014). Plant responses - Second-lowest mean MODIS-NDVI (figure 3). - Potato yields were much lower than normal in southern parts of the NAR (Nordland County; Statistics Norway 2014), which led to the third lowest potato yield for North Norway as a whole (Supplementary figure S18).

2009-10 Cold season - Several warming events causing partial snow melt and followed by frost and ice formation led to severe ground-icing, especially on grasslands, but probably also in natural ecosystems, and also extremely deep soil frost (to 150 cm at some sites and lasting until mid-July or even longer at some sites) (Norwegian Ministry of Agriculture and Food 2010, Norwegian Institute for Agricultural and Environmental Research 2014). - Steadily increasing reindeer populations peaked this winter, leading to high densities in winter grazing areas (Tømmervik et al 2011). Warm season - A warming event in mid-May, causing numerous slush torrents, was followed by an unusually cold and dry June (Turtiainen et al 2011, Callaghan et al 2013, Norwegian Meteorological Institute 2013, 2014). - Major outbreaks of the rodents lemming and vole (Olofsson et al 2012, 2013 Ims et al 2013). Plant responses

30

- Conifers experienced high dieback ratios and low crown densities, which was due to winter and spring desiccation due to frozen soil and sudden steep increases in temperatures both north and south of the Arctic Circle (Norwegian Forest and Landscape Institute 2014, Kullman 2014). - Other wintergreen plants also showed visible injuries due to winter desiccation (unpublished observations). - Vegetation damage along brooks impacted by slush torrents (Callaghan et al 2013, unpublished observations). - Very low hay (Statistics Norway 2014) and potato (figure A.18) yields, and record-high claims settlements paid to affected farmers for winter damage to their agricultural fields (figure A.17). - Reduced lichen cover due to overgrazing at Finnmarksvidda (Finnmark County, Norway), a process which developed over several years but which was accentuated in 2010 due to a combination of poor summer growth of preferred summer forage plants and high reindeer densities (Tømmervik et al 2011).

2010-11 Cold season - A warm start to the autumn, quickly being replaced by cold winter temperatures (Bokhorst et al 2012a, Norwegian Meteorological Institute 2013, 2014). - A cold winter from November to February (Norwegian Meteorological Institute 2013, 2014). Warm season - Major outbreaks of the rodents lemming and vole (Olofsson et al 2012, 2013, Ims et al 2013). Plant responses - Major outbreak of snow mould in a boreal pine forest recorded immediately after snow melt, which probably was instigated by the warm autumn weather (Bokhorst et al 2012a). - Decline in NDVI in an area in Swedish Lapland. Olofsson et al. (2012) interpret this decline as an effect of rodent activity, but their figures also show a decline in plant biomass in control plots without rodent activity. This indicates that one or more disturbance events (for example winter desiccation) also affected this area.

31

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