INBAR Working Paper No. 85

Juan Carlos Camargo García Trinh Thang Long

Assessment of Ecosystem Services from Bamboo-dominated Natural Forests in the Coffee Region, Colombia

International Bamboo and Rattan Organisation The International Bamboo and Rattan Organisation, INBAR, is an intergovernmental organisation dedicated

to the promotion of bamboo and rattan for sustainable development.

About this report This research was carried out by INBAR as part of the CGIAR Research Program on Forests, Trees and

Agroforestry (FTA). FTA is the world’s largest research for development program to enhance the role of

forests, trees and agroforestry in sustainable development and food security and to address climate change.

CIFOR leads FTA in partnership with Bioversity International, CATIE, CIRAD, INBAR, ICRAF and TBI. FTA’s work is supported by the CGIAR Trust Fund: cgiar.org/funders/

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Acknowledgements

We want to thank the stakeholders who provided information throughout the interviews, as well

as the Universidad Tecnológica de Pereira (UTP) and the research group on Gestión de

agroecosistemas tropicales andinos (GATA) for sharing information from unpublished project

reports—first, the project "Innovación Tecnológica para la optimización de procesos y

estandarización de productos en empresas rurales con base en la guadua” (Code 1110452-

21121; Contract 442-1-2008), funded by Colciencias, Yarima Guadua EU and Universidad

Tecnológica de Pereira), and second, the project “Servicios ecosistémicos, adaptación al cambio

climático y planificación del territorio: estrategias para el manejo de sistemas socio-ecológicos en

la zona cafetera de Colombia” (Code 111074558624, Contract No. 048-2017), financed by

Colciencias, the Asociacion de productores de café de alta calidad de la Cuchilla de San Juan

and Universidad Tecnológica de Pereira Data from these projects permitted the adaptation of the

indicators used for assessing ecosystem services in this work.

Thanks to Liliana Bueno, Juliana Muñoz and Tatiana Carmona for their contributions to

conducting interviews and the literature review.

.

Authors

Table of Contents List of Figures ........................................................................................................................... i

List of Tables .............................................................................................................................ii

List of Abbreviations ...............................................................................................................iii

Executive Summary ..................................................................................................................v

1. Introduction ........................................................................................................................1

2. Methods ..............................................................................................................................3

3. Results ................................................................................................................................7

4. Discussion ........................................................................................................................16

5. Conclusions .....................................................................................................................18

5. Recommendations ...........................................................................................................19

6. References .......................................................................................................................20

Appendix .................................................................................................................................28

i

List of Figures Figure 1. Contribution of variables (rescaled) to the definition of ES among different land uses

------------------------------------------------------------------------------------------------------------------------------ 12

Figure 2. PCs and variables representing ES. Land uses are also integrated. Values in

parentheses explain the variability. ------------------------------------------------------------------------------- 13

Figure 3. Dendrogram after cluster analysis using the Ward method and Euclidian distance.

Clusters (1 = blue lines, 2 = red lines) represent groups of land uses associated with ESs. ----- 14

Figure 4. Representation of the perception of ESs by rural and urban inhabitants of the coffee

region of Colombia. --------------------------------------------------------------------------------------------------- 15

ii

List of Tables

Table 1. Values of variables associated with the assessed ESs. Case of study 1. Yarima farm.

Pereira, Colombia. ......................................................................................................................9

Table 2. Values of variables associated with the assessed ES. Case of study 2. Coffee farms,

Belen de Umbria, Colombia ......................................................................................................10

Table 3. Values of variables associated with the assessed ES. Case of study 3. Lucerna farm,

Bugalagrande, Colombia and bamboo stands along Cauca river valley ....................................11 Table 4. List of ESs assessed and the respective indicators according to availability of common

data among the three cases of study………………………………………………………………….28 Table 5. List of ESs assessed and the respective indicators according to availability of common

data among the three cases of study ........................................................................................31

iii

List of Abbreviations

AGC

BD

Bio

BGC

Co

CoP

CoPT

CP

ES

Fo

GATA

GMD

INBAR

masl

MEA

OM

OM 25 cm

OM 50 cm

PC

PCA

PHDT

Aboveground carbon

Soil bulk density

Biodiversity index

Belowground carbon

Coffee in full sun exposure

Coffee associated with plantain

Coffee associated with plantain and trees

Citric plantation

Ecosystem services

Natural forest

Grupo de investigación en gestion de agroecosistemas tropicales andinos

Geometric mean diameter of soil aggregates

International Bamboo and Rattan Organisation

Metres above sea level

Millennium Ecosystem Assessment

Soil organic matter

Soil organic matter at 25 cm depth

Soil organic matter at 50 cm depth

Principal component

Principal components analysis

Pasture with high density of trees

PLDT

PP

PWT

SD

SE

SF

SOC

Pasture with low density of trees

Pineapple plantation

Pastures without trees

Standard deviation

Degree of physical soil degradation

Soil fertility

Soil organic carbon

iv

SSI

SSPPAI

TEEB

TM

TP

UTP

WMD

Structural stability soil index Intensive silvopastoral systems with Leucaena leucocephala

The Economics of Ecosystem and Biodiversity

Total soil mesopores

Total soil porosity

Universidad Tecnológica de Pereira

Weighted mean diameter of soil aggregates

v

Executive Summary In the coffee region of Colombia, natural forest (Fo) dominated by the bamboo species Guadua

angustifolia represents remnants of natural habitat and provides key ecosystem services (ESs).

However, these forests are highly fragmented due to agricultural and urban expansion and threats

to the benefits provided by them. In order to elucidate the importance of ESs and how they might

be affected by different land uses and management, in this work, data from three cases of study

and the perceptions of rural and urban stakeholders are assessed. The results show that natural

ecosystems (including bamboo) and highly diversified land uses (e.g. agroforestry) are important

for the provision of habitat for biodiversity, soil protection and climate regulation. As the intensity

of labour and human activities increases for conducting agricultural undertakings, other ESs, such

as the supply of raw material, feed foods or soil fertility (SF) may become more relevant. The

perceptions of stakeholders on ESs change according to their location. For rural inhabitants,

priority ESs relate to provisions where local benefits are more evident, whereas for urban people,

global ESs like climate regulation and cleaner air have more relevance. Thus, assessment of ESs

should be carried out according to the socio-economic context and considering that the assigned

value of a determined ES might change depending on the perception of who receives the benefits.

Although it is feasible that ESs can be simultaneously perceived according to different land uses,

an integrated assessment may result in more adequate information. In this context, bamboo

forests have been assessed as an excellent alternative among land uses, always providing those

ESs for which other land uses have a reduced capacity (e.g. regulation ESs), and they have the

potential of supplying goods for improving livelihoods in rural areas, as well as contributing to a

better environment in urban areas.

1

1. Introduction

The coffee region of Colombia is located along the Andean mountains at 900–2000 metres above

sea level (masl). Landscape in this area is shaped by a complex mix of land uses, mainly involving

a transformation from natural ecosystems to pastures or coffee plantations, and consequently,

becoming highly fragmented forests (Camargo and Cardona, 2005, p. 14). In this altitudinal gradient, fragmented forests are dominated by the bamboo species Guadua angustifolia (guadua;

Camargo, 2006, p. 13).

Although guadua forests represent one of the principal natural ecosystems in this region of

Colombia, there is no information on inventories that have recently been carried out. In 2006,

Kleinn and Morales-Hidalgo (2006, p. 366) estimated that the forests cover 2800 ha; however, the

pressure due to expansion of agricultural cropland and urban areas (Aguirre, 2017, pp. 34-35;

Muñoz, 2017, p. 13) and the increasing of land value when rural land comes under sub-urban use

(Giraldo et al, 2015, p. 215) are reasons to believe that the guadua forest area has decreased.

This tendency is opposite to that of other countries, where bamboo areas are increasing (e.g.

Buckingham et al, 2014, p. 770); apparently, Colombia is going against the trend.

In Colombia, and especially in the coffee region, raw material from guadua forests has been

obtained for different uses over the years (García and Camargo, 2010, p. 65, 75), most of which

relate to structural applications (Takeuchi et al, 2009, p. 43-44; Correal and Arbelaez, 2010,

p.105). Raw material is considered as a ‘provisioning’ ES,1 which is indeed acknowledged by the

beneficiaries (Muñoz-López, Camargo and Romero-Ladino, 2017, p. 230). Furthermore, other

benefits have been registered, especially those associated with the ES related to habitat for plant

biodiversity (e.g. Ospina, 2002, pp. 23–25; Ramírez-Díaz and Camargo, 2019, pp. 3–4), habitat

for birds (Sanchez and Camargo, 2012, pp. 86–87), soil conservation and protection (Camargo

et al, 2010, p. 59), water purification (Chará et al, 2010, p. 66), landscape restoration (Camargo

et al, 2018, p. 56), climate change regulation throughout carbon sequestration (Camargo,

Rodríguez and Arango, 2010, p. 93) and bioenergy (Daza Montaño et al, 2013, p. 142). In addition,

1 Ecosystem services are divided by the Millennium Ecosystem Assessment into four groups: regulatory, supporting, provisioning and cultural ecosystem services.

2

ESs of guadua forests have been assessed through an integrated approach that simultaneously

looks at both the ecological functions and economic benefits (Muñoz-López, 2017, p. 6). Likewise,

considering the equivalent energy employed in different processes when harvesting, the

sustainability of guadua forests has been evaluated under the emergy approach (Arango,

Camargo and Castaño, 2017, p. 536).

In order to present a case study of ESs provided by bamboo in the coffee region of Colombia and

make comparisons with other land uses, in this work, a literature review focussing on local studies

on ES was conducted. Then, by using existing data related to ES and different land uses, as well

as the perception of urban and rural stakeholders, an assessment of the ES was carried out.

3

1. Methods

1.1 Literature review From the available electronic resources, such as Science Direct, Scopus, Elsevier and Web of

Science, a search of information related to ESs, with a focus on studies carried out in the coffee

region of Colombia, was conducted. In addition, the repositories of local universities were

reviewed to find theses or academic documents conducted on topics related to ESs. The search

included studies with different aims but related to factors or functions that might be associated

with ES.

Studies were grouped according to the classification suggested in the framework document

created by the Center for International Forestry Research and International Bamboo and Rattan

Organisation (INBAR) (Paudyal et al, 2019, pp. 7–10) into provisioning, regulating, cultural and

habitat services based on The Economics of Ecosystem and Biodiversity (TEEB, 2010, p. 34). In

addition, a category of integrated approach was included when the focus of the work was a set of

ESs or it was carried out from different perspectives (e.g. ecological and economic).

1.2 Data collection and sites of study ES was assessed using two approaches. For the first, a quantitative approach was applied using

variables that were previously collected in prior projects. The second involved a qualitative

approach and was carried out with information gathered throughout interviews applied to rural

and urban stakeholders.

Three datasets from different projects were used for obtaining the variables used in the

quantitative approach to assess ESs. Information on the three cases comes from the coffee region

of Colombia and states of Risaralda and Valle del Cauca, which exhibit different ecological

conditions, land uses and socioeconomic contexts.

The first case was carried out in Yarima farm, in Pereira, Risaralda at 1150 masl with an annual

rainfall of 2262 mm per year on average and mean temperature of 24°C. From the total area of

4

80 ha, 20 ha are occupied by guadua forests (bamboo), and the remaining area is used for pasture

with a high density of trees (PHDT) and pasture with a low density of trees (PLDT), citric

plantations (CPs) and pineapple plantations (PPs). The density of trees per hectare for was

100/ha, and that for PLDTs was 30/ha. The data used came from the project carried out by UTP

through GATA (UTP-GATA, 2012).

For the second case, data from two sources were used. The first dataset came from 15 coffee

farms located in the municipality of Belén de Umbría, Risaralda. These farms belong to a famers

association and are distributed along the altitudinal gradient from 1012 to 1944 masl. The average

rainfall is 2217 mm/year, and the temperature is 23°C on average. The land uses included

correspond to coffee in full sun exposure (Co), coffee associated with plantain (CoP), coffee

associated with plantain and trees (CoPT) and Fo. The data were collected in the UTP-GATA

(2016) project framework. The second dataset is from the guadua forests (bamboo). Plots for

collecting data were established by Camargo (2006, pp. 69, 199, 200) in places located also in

the same municipality (Belen de Umbria) and with the same ecological conditions as the above

mentioned coffee farms. Although these data were collected a long time ago, the bamboo forest

continues to have the same conditions in terms of area, structure, management and ecological

factors. Thus, attributes used for comparisons with other land uses may be employed, always

keeping in mind that the times when data on land uses were collected are different.

In the third case, data came from two projects. Data on silvopastoral systems, pastures and Fo

came from Bueno López (2014, pp. 47–50), while those on guadua forests (bamboo) came from

Camargo (2006, pp. 69, 199, 200). The land uses included were intensive silvopastoral systems with Leucaena leucocephala (SSPPAI), pastures without trees (PWTs), Fo and guadua (bamboo).

Fo, SSPPAI and PWT were found in Lucerna farm, at 950 masl and with an average rainfall of

1100 mm and average temperature of 24°C. Information of guadua corresponds to places located

in the same ecological conditions along the Cauca River Valley. As mentioned above, guadua

forests have not changed in recent years.

The information on ES to be assessed was chosen by considering common or coincident

variables among the three cases of study. Thus, variables from soil and biomass associated with

the ESs of regulation and provisioning of habitat were selected for comparisons among land uses

5

in each case and for a multivariate analysis, including information of the three cases together.

Table 2 presents the ESs and variables associated with them. Soil variables were evaluated by

land use and coverages up to 50 cm in depth. Chemical and physical analyses were conducted

at a soil analysis lab. Values of biomass carbon for bamboo were calculated with information on

culm volume, culm density and a biomass expansion factor obtained from carbon data in Arango's

(2011, p. 40) study.

In case 1, soil organic carbon (SOC) represents the values of carbon for PPs because the

biomass does not have woody components, it is not a permanent crop and it is harvested and

renovated every 18 months. In addition, it is considered a crop with an important level of

greenhouse gas emissions (Graefe, Tapasco and Gonzalez, 2013, p. 8). For CPs, considering

the density of trees per hectare and average diameter, the allometric model proposed by Segura

and Andrade (2008, p. 8) was used. For pastures with trees, a pasture biomass value was

assigned according to Arias et al (2009, pp. 35–37), and for trees, considering the diameter and

total density of trees per hectare, the model proposed by Segura and Andrade (2008, p. 8) was

used for estimating biomass.

In case 2, values for carbon in different coffee farms came from UTP-GATA (2016). In case 3,

information on carbon in silvopastoral systems and pastures came from Arias et al (2009, pp. 35–

37). Carbon storing in Fo in cases 2 and 3 was assigned according to the values registered by

Gibbs et al (2007, p. 5) for tropical forest, considering the more conservative values.

For the qualitative approach, individual interviews were conducted with two groups of

stakeholders. A total of 10 ESs, including all categories of classification (Paudyal et al, 2019, pp.

7–10), were prioritised. Then, according to the context, the ES perception of rural and urban

inhabitants was assessed. Rural stakeholders were farmers from the coffee region who had

previously participated in the above-mentioned projects, and after being contacted, agreed to

attend the interview. Urban stakeholders were persons who usually visited the botanical garden

of UTP who agreed to be interviewed.

For rural stakeholders, the provisioning ESs assessed were wood, firewood, feed and food. The

regulation ESs were temperature regulation, soil protection and water regulation. The habitat

6

provisioning ES was biodiversity, and the cultural ESs were scenic beauty and recreation. For

urban stakeholders, the provisioning ESs assessed were wood and feeding. The regulation ESs

were temperature regulation, soil protection, air quality, climate regulation and water regulation.

The habitat provisioning ESs were biodiversity and connectivity of forests for conservation, and

finally, the cultural ES was scenic beauty.

1.3 Analyses For the quantitative approach, descriptive statistics of all variables were calculated within the land

uses of each case of study. Then, a non-parametric Kruskal–Wallis test was performed in order to see significant (p < 0.05) changes between land uses. The original values of variables that

represent ESs were rescaled to a range of 0.1–1 using the transformation proposed by Kearney

et al (2017, p. 169) and suggested by De Leijster et al (2019, p. 5):

𝑌𝑌𝑖𝑖 = 0.1 + �𝑋𝑋𝑖𝑖 −𝑀𝑀𝑀𝑀𝑀𝑀𝑖𝑖

𝑀𝑀𝑀𝑀𝑀𝑀𝑖𝑖 − 𝑀𝑀𝑀𝑀𝑀𝑀𝑖𝑖� 𝑀𝑀 0.9,

where i is the ES indicator index, Y is the response index value of i and Max and Min represent

the maximum and minimum of i. For soil bulk density (BD), the reverse transformation was applied

because high values of bulk density are related to limiting conditions of soil. Thus, Y is subtracted

from 1.1, as proposed by Kearney et al (2017, p. 169) and recommended by De Leijster et al

(2019, p. 5). The values of ES were averaged and then plotted to show the contribution of each

land use or coverage.

With the original values of ES indicators, a principal components analysis (PCA) was performed

to show those with higher influence on data variability. The first two components were then plotted

to see the variables with higher correlations with them. Thereafter, to define probable levels of

association between land uses or coverages concerning the capacity to provide ESs, a cluster

analysis was performed. All analyses were carried out with InfoStat/Free 2019d (Di Rienzo et al,

2019).

For the qualitative approach, data collected in interviews for rural and urban stakeholders were

averaged by land use and plotted in radar figures in order to elucidate those ESs that represent

a high perceived importance.

7

2. Results

2.1 Literature review Local studies on ESs were not abundant. Most of the references found focussed on those land

uses representing changes towards a better condition (e.g. monocrop to agroforestry) or natural

ecosystems (e.g. guadua or forest). Within these studies were included some carried out for urban

habitats, where guadua forests played an important role.

Twenty-four studies were found, eight of them related to regulating services where climate

regulation represented the topic of higher interest. Most of the studies were related to guadua

forests and only one (Daza Montaño et al, 2013, p. 22) included other bamboo species. Only two

studies were written in English and the others in Spanish, which might be a restriction for being

referred to at the global level.

An integrated approach was used in eight studies, where the focus was a set of ESs and not a

specific ES. In addition, these studies integrated ecological, economic and sociocultural factors

(e.g. Muñoz-López, 2017, p. 6) for the assessment of ESs. Thus, the perception of the benefits

received from a specific land use might be acknowledged more easily by stakeholders. Methods

applied in these cases are usually qualitative because require rescale variables for being

compared (e.g. Muñoz-López, 2017, p. 21) or valuated with an integrated indicator (e.g. Dossman,

2009, pp. 35–36).

Due to the distribution of guadua forests, surrounding urban areas or even within them, studies

have included these ecosystems. In fact, these bamboo forests are associated with ecological

quality or the possibility of obtaining raw material for different uses (García Sierra and Giraldo

Gómez, 2018, p. 110). Unfortunately, urban expansion has been seen to have a negative effect

on guadua forests (Aguirre, 2017, pp. 34– 35; Muñoz, 2017, p. 13), and therefore, the associated

ES might also be lost.

8

The studies listed below were carried out with academic purposes (Table 5, Appendix). Therefore,

the possibility of being included as an input for standards (local or international) will depend on

the information requirements of each standard and its quality when the studies were carried out.

2.2 The quantitative approach In all cases, a better state of ESs was associated with land uses with more complexity in structure,

such as bamboo forest or Fo. However, more restricted conditions for ESs were related to land

uses with a simple structure and composition, such as PPs or PWTs (Table 1, Table 2, Table 3).

According to the indicators considered to assess ESs, natural and bamboo forests were mainly

important for ESs of climate regulation and habitat for biodiversity. In cases 1 and 2, values of

indicators for both ESs were significantly higher (p < 0.05) than those of other land uses (Table 1

and Table 2). In case 3, although the total ecosystem carbon (below-ground carbon and above-

ground carbon) showed values less than those of SSPIA and PWT, the above-ground carbon represented by biomass was significantly higher (p < 0.05) for bamboo and forest (Table 3).

For indicators associated with the ESs of soil protection and water regulation, natural and bamboo

forests showed similarities with land uses that include woody species as a component (e.g.

agroforestry systems). BD was always lower in bamboo (Table 1, Table 2, Table 3), showing

proper conditions of aeration and water flow.

In case 3, where clayey soils are predominant, high values for indicators of structural stability

(weighted mean diameter of soil aggregates [WMD] and geometric mean diameter of soil

aggregates [GMD]) do not necessarily represent better soil conditions. Big soil aggregates do not

provide the proper conditions, whereas middle size soil aggregates found in soils under bamboo

are better for maintaining soil stability (Table 3).

In cases 1 and 3, SF was lower in bamboo, but values were moderate even though fertiliser is

never supplied under this land use. In fact, the values of SF in case 1 were not significantly

different (p > 0.05). In case 2, SF was higher as the complexity of land use and vegetal

composition increased. For cases 1 and 2, soil organic matter (OM) values were always higher

9

for bamboo, while in case 3, the value was slightly lower in bamboo (Table 1, Table 2, Table 3).

Thus, the results show that the ESs of nutrient cycling were also important under bamboo.

Table 1: Values of variables associated with the assessed ESs. Case of study 1. Yarima farm.

Pereira, Colombia.

ES Indicator Bamboo CP PHDT PLDT PP

Mean SD Mean SD Mean SD Mean SD Mean SD

Nutrient cycling

OM 25 cm 7.9 1.5 5.3 2.4 5.3 0.4 4.3 0.6 4.1 0.6

OM 50 cm 6.1 1.7 3.2 1.3 2.4 0.3 2.4 0.4 2.7 0.4

SF 5.5 0.2 6.2 0.9 6.1 0.4 5.6 0.2 6.1 0.9

Soil Protection

WMD (mm) 2.6 0.2 2.7 0.5 3.1 0.7 2.9 0.3 3.1 0.8

GMD (mm) 1.4 0.1 1.5 0.3 1.8 0.5 1.7 0.2 1.9 0.6

SSI mean 1.6 1.0 157.6 139.9 307.8 45.9 287.4 118.1 464.1 279.7

SSI high 1.8 1.1 304.6 332.4 671.1 245.8 407.2 152.8 1215.5 904.8

SSI low 27.6 12.1 1202.2 518.7 2171.2 1091.9 2176.7 1081.9 2690.1 2441.1

SE 11.2 2.4 8.0 4.5 6.8 0.5 5.5 0.6 5.4 0.7

Water regulation

TP (%) 64.2 3.8 56.6 6.2 49.3 0.3 51.4 2.3 58.2 2.9

TM (%) 11.2 0.8 11.4 1.6 14.6 1.7 13.7 2.6 10.3 1.8

BD (g/ m3) 0.8 0.1 1.0 0.2 1.2 0.01 1.1 0.1 1.0 0.1

Climate regulation

BGC (Mg/ha)

167.3 21.2 115.0 33.7 131.7 7.1 110.0 11.1 93.5 7.4

AGC (Mg/ha)

26.5 9.3 9.2 0.0 28.5 0.0 11.0 0.0 0.0 0.0

AGC + BGC (Mg/ha)

193.8 22.9 124.2 33.7 160.2 7.1 121.0 11.1 93.5 7.4

Habitat provisioning

Bio 0.5 0.3 0.5 0.3 0

Bamboo = natural bamboo forest with Guadua angustifolia, SSI = Structural stability index, SE= Degree of soil physical degradation, TP = soil total porosity, TM= soil mesopores, BGC = belowground carbon, AGC=

aboveground carbon. Bio = biodiversity index, SD = standard deviation, OM 25 cm = soil organic matter at 25 cm depth, OM 50 cm = soil organic matter at 50 cm depth.

10

Table 2. Values of variables associated with the assessed ES. Case of study 2. Coffee farms, Belen de Umbria, Colombia

ES Indicator Bamboo Fo Co CoP CoPT

Mean SD Mean SD Mean SD Mean SD Mean SD

Nutrient cycling

OM 25 cm 10.4 4.0 4.2 0.6 4.5 0.6 4.3 0.9 3.3 0.8

OM 50 cm 6.8 2.8 3.9 1.1 4.3 0.8 3.7 1.1 2.8 0.7

SF 5.8 0.6 5.4 0.4 4.9 0.1 5.0 0.7 5.1 0.6

Soil Protection

WMD (mm)

3.1 0.6 3.3 1.0 2.7 0.3 3.2 0.9 3.4 0.9

GMD (mm)

2.0 0.7 2.4 0.8 2.0 0.2 2.4 0.7 2.6 0.7

SSI mean 24.7 22.6 8.8 0.3 11.3 0.3 11.0 1.2 10.8 1.9

SSI high 35.1 43.1 9.0 0.3 11.5 0.3 11.2 1.2 11.0 1.9

SSI low 112.9 65.4 560.9 80.9 800.3 157.8 755.3 208.1 827.2 276.8

SE 20.3 8.8 6.7 1.7 6.5 1.1 5.8 1.4 4.3 1.0

Water regulation

TP (%) 53.0 4.4 61.2 6.8 66.2 1.2 62.5 5.6 61.5 3.2

TM (%) 14.1 9.5 12.4 2.3 21.8 1.3 20.6 3.1 21.2 3.3

BD (g/ m3)

0.7 0.1 0.9 0.2 0.8 0.0 0.9 0.1 0.9 0.1

Climate regulation

BGC (Mg/ha)

168.0 40.3 103.7 3.8 99.7 16.7 98.5 21.7 77.9 15.6

AGC (Mg/ha)

180.9 107.2 180.0 0.0 5.5 0.6 7.6 3.5 8.5 4.6

AGC + BGC (Mg/ha)

348.9 112.1 283.7 3.8 105.1 16.1 106.1 21.9 86.4 16.9

Habitat provisioning

Bio 0.5 0.9 0.3 0.4 0.6

11

Table 3. Values of variables associated with the assessed ES. Case of study 3. Lucerna farm, Bugalagrande, Colombia and bamboo stands along Cauca river valley

ES Indicator Bamboo Fo SSPPAI PWT

Mean SD Mean SD Mean SD Mean SD

Nutrient cycling

OM 25 cm 6.7 2.8 8.6 1.4 8.8 0.7 8.2 0.9

OM 50 cm 2.4 1.0 5.0 0.6 4.5 1.9 4.2 0.4

SF 6.8 0.6 8.0 0.7 9.4 0.5 8.5 0.7

Soil Protection

WMD (mm)

3.7 0.9 5.0 0.2 4.9 0.1 4.4 0.2

GMD (mm)

2.8 1.1 3.5 0.3 3.2 0.1 2.8 0.2

SSI mean 58.6 40.7 57.7 24.2 23.6 1.3 10.7 2.0

SSI high 724.3 1101.8 105.6 59.7 27.8 2.4 12.4 2.7

SSI low 169.6 92.9 201.6 21.3 310.0 141.8 333.7 392.9

SE 8.8 3.9 8.1 1.4 8.8 1.2 11.5 0.9

Water regulation

TP (%) 44.0 5.9 50.3 3.9 47.2 4.0 40.1 2.3

TM (%) 29.0 11.3 11.8 0.8 12.0 1.0 11.9 0.1

BD (g/ m3)

1.1 0.2 1.2 0.1 1.3 0.1 1.4 0.0

Climate regulation

BGC (Mg/ha)

136.8 35.2 227.6 21.6 248.5 36.7 252.9 25.2

AGC (Mg/ha)

94.7 43.7 180.0 0.0 8.4 0.0 3.6 0.0

AGC + BGC (Mg/ha)

231.5 52.0 407.6 21.6 256.9 36.7 256.5 25.2

Habitat provisioning

Bio 0.5 0.0 0.9 0.0 0.6 0.0 0.1 0.0

When values of variables or indicators are rescaled to the ES index, the tendency is the same as

observed with original data. Under this approach, the ES expressed by a set of variables where

each one contributes to the definition of ES, with interesting results concerning the contribution of

each land use or coverage to ES. Thus, if a farm is a unit of analysis, it might be feasible to define trade-offs among land uses and coverages and ES (Figure 1).

12

a)

b)

c) Figure 1. Contribution of variables (rescaled) to the definition of ES among different land uses

The area in the pie portion represents the number of variables used for defining the ES. a) Case of study 1. Yarima farm, Pereira, Colombia. b) Coffee farms, Belén de Umbría, Colombia c) Lucerna farm,

Bugalagrande, Colombia, and bamboo stands along Cauca River Valley.

0

0.2

0.4

0.6

0.8

1OM 25 cm

OM 50 cm

SF

WMD

GMD

SSI mean

SSI high

SSI lowSE

TP

TM

BD

BGC

AGC

Bio

CP Bamboo PHDT PLDT PP

0

0.2

0.4

0.6

0.8

1OM 25 cm

OM 50 cm

SF

WMD

GMD

SSI mean

SSI high

SSI lowSE

TP

TM

BD

BGC

AGC

Bio

Co CoP CoPT Bamboo Fo

0

0.2

0.4

0.6

0.8

1OM 25 cm

OM 50 cm

SF

WMD

GMD

SSI mean

SSI high

SSI lowSE

TP

TM

BD

BGC

AGC

Bio

PWT SSPPAI Bamboo Fo

13

After the PCA, two components explained 74% of the total data variability. The first component

had a higher influence of variables, representing the ESs of nutrient cycling (OM, SF), climate

regulation (AGC, BGC) and habitat for Bio. The second component correlated well with variables

associated with the ES of water regulation (TP, TM, BD). Land uses integrated into the analysis

permit associations between the principal components (PCs), ES and land uses to be elucidated.

Figure 2 depicts the contribution of variables (length of the line) to the value of components 1 and

2. As the line becomes longer in relation to each axis, the contribution of each variable is greater.

Likewise, the land uses in Figure 2 represent the value of each component by land use.

Figure 2. PCs and variables representing ES. Land uses are also integrated. Values in parentheses

explain the variability.

The association between components, ESs and land uses was confirmed after the cluster

analysis. Land uses were grouped into two clusters (Figure 3). Thus, land uses of PPs, PHDTs,

PLDTs, CPs, Co, CoP and CoPT are included in cluster 1 (Figure 3), representing low values of

component 1 (ESs of climate regulation, nutrient cycling and habitat for bio), although Co, CoP

and CoPT positively contribute to component 2 (ES of water regulation; Figure 2). Cluster 2 (Figure

3) includes land uses of SSPPAI, PWT, bamboo and Fo, which related to high values of

14

component 1 (ESs of climate regulation, nutrient cycling and habitat for bio). In addition, bamboo

and Fo, with positive values regarding component 2, also show a proper association with the ESs

of soil protection and water regulation (Figure 2).

Figure 3. Dendrogram after cluster analysis using the Ward method and Euclidian distance. Clusters (1

= blue lines, 2 = red lines) represent groups of land uses associated with ESs.

Individually, the PP has the least desirable conditions, with the lowest values regarding

component 1 and component 2, whereas bamboo and Fo represent better capacity for providing

ESs.

2.3 The qualitative approach For rural areas, it was feasible to compare bamboo with four land uses (Figure 4a), while in urban

areas, bamboo was compared with trees (urban) and forest fragments (within the city; Figure 4b).

Compared with other land uses, in rural areas, bamboo always had a higher capacity to provide

regulation, habitat and cultural ES. Meanwhile, provision of ESs was perceived to be higher for

other land uses. Regarding Fo, bamboo was perceived as better (Figure 4a).

15

In urban areas, bamboo was also perceived as better than other land uses for regulating ES. In

addition, it was reported to be easier for ES regulation in the interviews. In this case, the people

interviewed belonged to UTP, and most had an academic profile. Bamboo in urban areas was

perceived as having almost the same capacity for providing ESs as forest (Figure 4b).

a)

b)

Figure 4. Representation of the perception of ESs by rural and urban inhabitants of the coffee region of Colombia. ESs are expressed using Likert scales of 1 to 10, where 1 represents the lowest level of ES supply and 10

represents the highest level. Results of interviews conducted with a) rural stakeholders, b) urban stakeholders.

0

2

4

6

8

10Wood

Firewood

Feed

Food

Temperature regulation

Soil Protection

Water regulation

Habitat

Scenic beauty

Recreation

Bamboo Coffee Pasture Pineapple Forest

0

2

4

6

8

10Wood

Feed

Temperatureregulation

Soil Protection

Air quality

Climate regulation

Water regulation

Habitat

Conectivity

Scenic beauty

Bamboo Trees Forest

16

3. Discussion

Local information on ES is still scarce, although the concept has been used for almost two

decades (e.g. De Groot, Wilson and Boumans, 2002, p. 394; Millennium Ecosystem Assessment

[MEA], 2005, p. V). However, information on studies with different aims might be used to assess

ESs. For example, studies in productivity might be associated with provision services, while those

related to bio usually have indexes useful for describing functions that represent regulation ES.

All land uses can provide ESs; however, this cannot always be done with the same capacity (Baral,

Guariguata and Keenan, 2016, p. 261). In this study, land uses with higher similarities with natural

ecosystems (Fo, bamboo and agroforestry) showed more important results for providing ESs of

regulation, while simple arrangement showed contributions with provision. This is consistent with

studies where ESs are compared according to the level of management intensity, diversity and

complexity of the arrangements (Cerda et al, 2017, pp. 313–316; De Leijster et al, 2019, p. 10).

However, other land uses might be perceived as much more efficient in terms of their benefits

when economic profit is considered.

Since the base of ecological functions, and therefore ESs, is supported by biophysical processes

(Kangas et al, 2018, p. 7), if restrictions naturally exist, it is feasible that the ESs will not improve

even under the better management practices or conservation strategies. Muñoz-López (2017, p.

23) found that guadua bamboo forests were located in marginal areas where the soil had some

restrictions. When bamboo shows values of ES indicators similar or lesser than other land uses,

this condition should be considered.

If natural and bamboo forest coexist with other land uses, ESs provided by them might be a trade-

off, considering the limitations associated with some of the land uses assessed. These

relationships are called synergistic by Dai et al (2017, p. 7808), and they might be useful for

promoting proper, integrated land use management. However, sometimes, trade-off occurs in

association with a negative ES condition (Rodríguez et al, 2006, p. 2,7), especially when an ES

is enhanced at the detriment of others. This was not the situation here, and with the proposed

approach, land uses with limited or deteriorated conditions may be identified and prioritised for

better management strategies.

17

Bamboo is considered a forest ecosystem. This is probably related to the abundance of guadua

forests in comparison with areas under Fo. Indeed, along the coffee region and specifically

between 900 and 2000 masl, guadua bamboo forests are abundant (Camargo, 2006, p. 13).

According to the information collected in interviews, dividing stakeholders into two groups was a

proper way to obtain better and reliable information on the perception of ESs. In rural areas

stakeholders had more possibilities of comparing ESs among different land uses. Given the

current situation, in which the market for bamboo products has some limitations (Muñoz-López,

2017, p. 26), bamboo had less importance for provisioning ESs when it was considered as a

commercial product; however, the domestic uses still have a significant role for rural people.

As in other studies, it was confirmed here that perceptions of SE from bamboo was an important

result due to the diversity and knowledge of guadua among farmers and urban people. This was

also describe by Paudyal et al 2019, pp. 11–12), as bamboo offers higher amounts of ES. In fact,

different groups of consumers have demanded raw material for different applications (García and

Camargo, 2010, p. 69,75). Currently, the possibilities of using bamboo raw material obtained even

from urban bamboo forest has increased, since an inventory of guadua bamboo forest carried out

in the city of Pereira (coffee region of Colombia) made it possible to identify a potential area to be

managed and harvested (García Sierra and Giraldo Gómez, 2018, p. 110).

Because of urban expansion (Giraldo, Osorio and Tobón, 2015, p. 245; Muñoz, 2017, p. 13),

which will probably increase the land price associated with this process, the ES perception of

bamboo forest by farmers living close to cities may be negatively biased. Therefore, the

perception of ES should always be analysed by considering the possibilities when it comes to

interpreting the answers. Usually, responses of ordinary people are less understood or depend

on the motivation of persons related to an ES (Asah et al, 2014, pp. 181, 182, 185). Hence,

information from interviews should be carefully managed and interpreted, and definitive

conclusions should be avoided.

18

5. Conclusions

Certainly, bamboo is fulfilling an important role in the provision of ES in the coffee region of

Colombia. Advantages were evidenced here under both approaches used for assessing ES.

Bamboo has an important potential to provide ESs of regulation and provisioning habitat.

According to the economic context, the domestic uses and possibilities of a market for bamboo

products, provisioning ESs will also become important. This is a real advantage regarding other

land uses, where there is not the same capacity to provide different kinds of ES.

The set of ESs assessed by the quantitative approach always tended to be better in natural and

bamboo forests. In contrast, the capacity of provisioning ESs tends to decrease as the uniformity

of land uses increases. However, in this region of Colombia, bamboo is often part of farming

systems where other land uses are present. Hence, if ES assessment is done for farming systems,

bamboo contributes by trading off those ESs of regulation and provisioning habitat, which are

weakly provided by other land uses.

The qualitative approach confirmed the importance of bamboo for providing ESs. Although the

context was different (rural and urban), its capacity was always recognised. In the coffee region

of Colombia, bamboo forests have traditionally provided raw material for different applications. In

addition, they represent the remnants of natural ecosystems along the ecological conditions of

this region.

Rescaling variables used as indicators for describing ESs was useful for comparisons on the

same scale. In addition, multivariate analyses permitted a general overview of ES. It was useful

to see the trade-off between ES and land uses. Nevertheless, the ES valuation of each land use

is relevant for avoiding negative trade-offs. This means that those land uses with a low valuation

of ES should be considered for improvements, as it certainly represents degradation problems.

19

6. Recommendations

Maximising the benefits of bamboo forests in the coffee region of Colombia requires increasing

areas that create the connectivity of the existing fragmented bamboo areas. A complementary

measure is increasing the control of those areas with high pressure on forests where bamboo is

being removed. Both challenges absolutely require the support of government institutions and the

participation of farmers.

Considering that ecological functions become ESs only when benefits are perceived,

stakeholders are the main source of information on ESs. Therefore, researchers or those who

analyse information should have the capacity to understand the meaning of the perceptions

expressed.

When the approach requires the perception of stakeholders, before gathering them, tools for

collecting information should be adjusted or addressed to the context. Different questions and

ways of collecting information might be used depending on the specific characteristics of the

population being assessed.

Studies related to the economic benefits of bamboo should be carried out. Such research can

include consideration of the domestic uses—which are frequently ignored—as a part of these

benefits.

20

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28

Appendix

Table 4. List of ESs assessed and the respective indicators according to availability of common data among the three cases of study

ES Indicator Description References

Nutrient cycling

OM 25 cm and OM 50 cm

OM of soils up to 50 cm depth, represents the possibility of nutrient cycling and carbon content.

(Malagón et al,

1995, pp. 303, 427) (Laiho et al,

2003, p. 10)

Soil fertility (SF)

SF is qualification of the nutrient availability as a result of biochemical processes. This approach assigns scores to eight chemical parameters

(pH, Al saturation, total bases, bases saturation, cation exchange capacity, soil organic carbon [SOC], K and P) between 0 cm and 25 cm depth

(F1) and then between 25 cm and 50 cm depth (F2). Scores values are computed proportionally according to the depth (F1 70% and F2 30%) and an only value of SF is obtained (e.g. >8.4 is a

very high fertility, while >3.6 is very low fertility).

(Ortega, 1995, p. 424)

Soil protection

WMD

Soil structure represents level of aggregation. A proper soil structure reduces the susceptibility of

soil to being eroded. Soil aggregates with diameters smaller than 0.5 mm increase susceptibility to erosion (e.g. WMD > 5 mm is a highly stable soil structure, while WMD < 0.5 is

an unstable soil structure).

(Cortés and Malagón, 1984,

p. 252,253) (Montenegro and Malagón, 1990,

pp. 297–306)

GMD Complementary to WMD and represents better the dominant diameter soil aggregates.

(Jaramillo, 2002, p. 110)

SSI mean

Represents the relationship between stable mean soil aggregates (0.25 mm and 2 mm) and the extreme values (> 3 mm and >0.125 mm).

Higher values represent the dominance of mean soil aggregates, and therefore, a better condition of the soil structure, since a high proportion of aggregates bigger than 2 mm in diameter might

(Jaramillo, 2002,

p. 111)

29

be associated with cemented soils; when aggregates smaller than 0.25 mm are

predominant, soil aeration decreases.

SSI high Complementary to SSI mean representing the proportion of aggregates > 3 mm regarding to

mean size soil aggregates

(Jaramillo, 2002, p. 112)

SSI low Complementary to SSI mean representing the proportion of aggregates < 0.25 mm regarding to mean size soil aggregates

(Jaramillo, 2002, p. 112)

SE

This is the relation between the OM regarding clay and silt and represents the risk of soil physical degradation. Higher values (>9) are

associated with stable soil, whereas low values (<3) are associated with degraded soils. Soil structure is affected by management when some practices damage the relining of soil peds,

provided by OM, clay and oxides of Fe and Al.

(Zilio, 2015, pp. 24–25)

Water regulation

TP

Represents the total porous space (%) of soil,

and therefore, the availability for liquids and gases. Higher values (e.g. >50%) result in proper air and water dynamics.

(Montenegro and Malagón, 1990,

pp. 278–279), (Jaramillo, 2002, p. 193),

TM Represents the proportion of soil pores where water may be stored and is available for plants. Therefore, also fulfils functions of regulation.

(Montenegro and Malagón, 1990, pp. 278–279), (Jaramillo, 2002,

p. 192)

BD

Relationship between the soil dry mass and total soil volume. Higher values (e.g. > 1.2 g/cm3)

would be associated with compacting problems, whereas low values (<0.8 g /cm3) represent proper conditions of aeration and water flow.

(Montenegro and Malagón, 1990,

p. 74), (Jaramillo, 2002, p. 160)

Climate regulation

Belowground carbon (BGC)

Carbon stored in soil, roots and rhizome (for bamboo). It represents the capacity of the ecosystems to store CO2 and contributes to

reducing global warming.

(Yiping et al, 2010, pp. 26, 27, 40)

30

(Yuen, Fung and Ziegler, 2017,

pp. 15, 24)

Aboveground carbon (AGC)

Carbon stored in plant biomass. It represents the capacity of the aerial compartments to store CO2 and contributes to reducing global warming.

(Yiping et al, 2010, pp. 26, 27,

40) (Yuen, Fung and Ziegler, 2017,

pp. 15, 24)

BGC + AGC

Total carbon of the ecosystems, represents the

capacity of the ecosystems (land use, coverage) to store CO2 and contributes to reduce global warming.

(Yuen, (Yiping et al, 2010, pp. 26,

27, 40) Fung and Ziegler, 2017, pp. 15, 24)

Habitat provisioning

Bio

This index was developed for 28 land uses more frequently found in the coffee region of Colombia. Assigned values range from 0 for short cycle

crops (annuals, grains and tubers) to 1 for mature Fo. This value depends on the composition and structure of agroecosystems and natural ecosystems assessed. The value

represents the capacity to offer habitat for biodiversity.

(Murgueitio et al, 2004, pp. 44–45)

31

Table 5. List of ESs assessed in local studies with bamboo forests and other land uses lES Description of ES Indicators of ESs (unit

of measurement) References

Provisioning services

Coffee, plantain and

meat production

Changes in coffee, plantain and meat

production according to territory transforming

Productivity, land-use change, population

growth

(Molina-Rico, Correa-Valencia and Feijoo-

Martínez, 2018, pp. 105–108)

Bioenergy Assessment of residues after harvesting of

guadua forest

Available tonnes of biomass residues

(Camargo, Arango and Angel, 2012, pp. 91–93)

Bioenergy Assessment of five bamboo species for

provision of bamboo pellets for being torrefied

Total biomass and properties to define

suitability of bamboo species for making torrified pellets

(Daza Montaño et al, 2013, pp. 45–54)

Provision of raw material Urban guadua forests of Pereira city were assessed and productivity of culms was

defined.

Maps, volume of culms available for being harvested

(García Sierra and Giraldo Gómez, 2018, pp. 39,10,113)

Provision of raw material Properties of guadua culms were assessed

according to requirements of different users

Culm properties (dendrometric and

physical-mechanical)

(García and Camargo, 2010, pp. 71–73)

Provision of raw material Zoning of Colombia

coffee region, definition of productivity levels and quality of guadua forests

Maps with zones

according to the productivity of guadua forests, quality of guadua

culms and available land for planting guadua

(Camargo et al, 2007, pp.

125–128)

Regulation services Landscape restoration Evaluation of changes in

soil properties and carbon after the

Changes in soils properties, changes in carbon stock

(Camargo et al, 2018, pp. 56–60)

32

establishment of guadua plantation

Climate regulation Evaluation of carbon stock in guadua forests and possibilities to

include these forests in the ‘reduce emissions from deforestation and forest degradation in

developing countries’, or REDD+, initiative

Carbon stored per hectare

(Arango, Amézquita and Camargo, 2012, pp. 28–30)

Climate regulation Estimation of biomass

and carbon in natural guadua forests

Carbon stored per

hectare

(Arango, 2011, p. 34)

Climate regulation Estimation of carbon sequestration and carbon

stored in a guadua plantation

Rate of carbon fixed per hectare and carbon

stored per hectare

(Camargo, Rodríguez and Arango, 2010, p. 92)

Climate regulation Estimation of carbon

sequestration in three guadua plantations

Carbon stored and the

rate of carbon fixed per hectare

(Riaño et al, 2002, p. 49)

Water regulation and soil

protection

Soil properties related

with water flow and structural stability were compared among guadua and pastures

TP, bulk density, soil

water store capacity and distribution of soil aggregates by size and stability

(Camargo et al, 2010, pp.

55–58)

Water purification and

soil protection

Nutrient retention and runoff were compared among guadua and

pastures

Concentration of nitrates and runoff volume

(Chará et al, 2010, pp. 64–65)

Nutrient cycling Nitrogen fixation by plants and soil and presence of rhizobium

nodes within intensive silvopastoral systems

% of soil and foliar nitrogen content and number of nodes

(Bueno López and Camargo Garcia, 2015, pp. 338–340)

Habitat services

33

Habitat for plant diversity

Floristic composition was assessed in guadua

forests under different level of management

Bio (Ramírez-Díaz and

Camargo, 2019, p. 4)

Habitat for birds

Birds’ biodiversity was

assessed in guadua forests under different levels of management

Bio (Sanchez and Camargo, 2012, pp. 86–87)

Habitat for plan diversity

Floristic composition was

assessed in guadua forests under different levels of management,

locations and topographic conditions

Bio (Ospina, 2002, pp. 23–32)

Integrated approaches for assessing ES

Provisioning, regulation

and cultural ES in farms

with plantain cropping

Within farms with plantain cropping systems, interactions between ESs of provision

and regulation were assessed through biomass and plantain

production, chemical SF, physical support, erosion control, biological activity of macroinvertebrates

and social representations.

Productivity of plantain and biomass were measured and associated with

provisioning ES and soil macroinvertebrates; data on physical and chemical soil properties obtained

by sampling were related to ES of regulation and data on management

practices. Time of permanence gathered from 50 farmers using ethnographic

approaches were related with social representations. Then,

descriptive statistics, correlation and canonical analyses were used to

(Molina-Rico, 2018, pp. 74–83)

34

elucidate trade-offs between ESs

Water regulation, soil

protection, carbon stock

and raw materials supply

Valuation of guadua ES, assessing soil properties, carbon stored and

economic analysis

Values of ES rescaled, then an integrated indicator was

constructed; also, financial indicators

(Muñoz-López, 2017, pp. 21, 25)

Wood, soil protection,

water regulation,

pollination, habitat for

biodiversity

Qualifying ES of guadua,

Valuation was carried out by expert consultation

Ranking and rating approach: Scores of 0–

100 when ranking and 1–9 when rating.

(Muñoz-López, Camargo

and Romero-Ladino, 2017, pp. 245–249)

Habitat for biodiversity,

water supply

Changes in natural coverages associated with provision of ESs

Mapping, geographic

information system and expert consultation; land coverage

(Giraldo, Osorio and Tobón, 2015, pp. 245–249)

Recreation, education,

soil protection, sediment

retention, water

purification, water supply

ESs of a small watershed assessed; literature review and expert consultation carried out

Indicators from the existing literature and ranking and rating approach

(Valencia et al, 2017, pp. 25–31)

Soil protection, diversity,

and ecological

restoration

ES in silvopastoral systems

Indicators of soils properties, carbon stock and connectivity

(Chará et al, 2015, pp. 335–339)

Habitat for biodiversity,

pest control, water

regulation and climate

regulation

ES in silvopastoral systems assessed throughout of identification and

monitoring of biodiversity, soil properties and tree

mensuration

Bio, soil properties, tree

biomass

(Zuluaga, Giraldo and

Chará, 2011, pp. 11–28)

ESs of soils, such as

nutrient cycling, carbon

stock, water regulation

and provision of support

to plants

Soil properties assessed among different land

uses and values rescaled for comparison

ESs scored between 1 and 5 and an integrated indicator used to define

when characteristics of soils should be kept, improve or restored

(Dossman, 2009, pp. 35–

36)

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