Forestry, Faculty of
DSpace
UBCV
Gonzalez Prieto, Catalina
Master of Science - MSc
University of British Columbia
The loss of tropical forest for agriculture is a principal cause of declines in species diversity in the Neotropics. Shade-grown coffee plantations, where coffee plants grow under a canopy of trees, have been found to support a higher diversity of both Neotropical migrant and tropical resident birds compared to agroecosystems without trees. However, how local and landscape factors interact to affect avian biodiversity remains poorly understood. I studied the influence and interaction of local and landscape attributes on bird richness and community completeness in 160 shade coffee plantations in two regions of Colombia differing in extent of regional forest: Antioquia, where forest covered 20% of the study area and Cauca, where only 1% of forest remained. By using generalized linear models, I determined how species richness and community completeness were influenced by the local scale structure and composition of shade-grown coffee plantations (i.e., tree richness, tree abundance, and coffee density) and landscape variables surrounding the plantation (i.e., plantation distance to forest, cover by intact forest, forest-agriculture mosaic, or the combination of the two). My findings suggest that the extent of regional forest cover affects the landscape-level contribution to bird richness and community completeness within plantations. In Antioquia, richness of bird communities increased with the proportion of all forest elements within the surrounding landscape. Community completeness was influenced by the interaction between the local and landscape scales; tree richness enhanced community completeness only when the forest-agriculture mosaic cover at the landscape scale was greater than 73%. In Cauca, higher richness and abundance of trees at the local scale were associated with greater bird richness and community completeness, while there were no landscape-scale effects. Within highly deforested regions, birds are most likely to benefit in the near-term from increasing the diversity of shade trees within farms. However, reforestation efforts at the landscape scale should be considered as a long-term strategy to provide critical resources that support more complete communities of birds in coffee plantations. In more forested regions, bird communities could benefit by protecting and/or increasing the forest cover in the landscape and increasing the diversity of trees within plantations.
EFFECT OF LOCAL HABITAT AND LANDSCAPE ATTRIBUTES ON BIRD SPECIES RICHNESS AND COMMUNITY COMPLETENESS IN SHADE COFFEE PLANTATIONS IN COLOMBIA by Catalina Gonzalez Prieto B.Sc., The University of Tolima, 2009 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in The Faculty of Graduate and Postdoctoral Studies (Forestry) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) December 2022 © Catalina Gonzalez Prieto, 2022 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the thesis entitled: Effect of local habitat and landscape attributes on bird species richness and community completeness in shade coffee plantations in Colombia submitted by Catalina Gonzalez Prieto in partial fulfilment of the requirements for the degree of Master of Science in Forestry Examining Committee: Dr. Scott Wilson, Forest and Conservation Sciences, UBC Co-supervisor Dr. Peter Arcese, Forest and Conservation Sciences, UBC Co-supervisor Dr. Amanda Rodewald, Cornell Lab of Ornithology and Dept. of Natural Resources Supervisory Committee Member Dr. Kai Chan, Institute for Resources, Environment, and Sustainability, UBC Additional Examiner Additional Supervisory Committee Members: Dr. Claire Kremen, Institute for Resources, Environment, and Sustainability, Zoology, UBC Supervisory Committee Member iii Abstract The loss of tropical forest for agriculture is a principal cause of declines in species diversity in the Neotropics. Shade-grown coffee plantations, where coffee plants grow under a canopy of trees, have been found to support a higher diversity of both Neotropical migrant and tropical resident birds compared to agroecosystems without trees. However, how local and landscape factors interact to affect avian biodiversity remains poorly understood. I studied the influence and interaction of local and landscape attributes on bird richness and community completeness in 160 shade coffee plantations in two regions of Colombia differing in extent of regional forest: Antioquia, where forest covered 20% of the study area and Cauca, where only 1% of forest remained. By using generalized linear models, I determined how species richness and community completeness were influenced by the local scale structure and composition of shade-grown coffee plantations (i.e., tree richness, tree abundance, and coffee density) and landscape variables surrounding the plantation (i.e., plantation distance to forest, cover by intact forest, forest-agriculture mosaic, or the combination of the two). My findings suggest that the extent of regional forest cover affects the landscape-level contribution to bird richness and community completeness within plantations. In Antioquia, richness of bird communities increased with the proportion of all forest elements within the surrounding landscape. Community completeness was influenced by the interaction between the local and landscape scales; tree richness enhanced community completeness only when the forest-agriculture mosaic cover at the landscape scale was greater than 73%. In Cauca, higher richness and abundance of trees at the local scale were associated with greater bird richness and community completeness, while there were no landscape-scale effects. Within highly deforested regions, birds are most iv likely to benefit in the near-term from increasing the diversity of shade trees within farms. However, reforestation efforts at the landscape scale should be considered as a long-term strategy to provide critical resources that support more complete communities of birds in coffee plantations. In more forested regions, bird communities could benefit by protecting and/or increasing the forest cover in the landscape and increasing the diversity of trees within plantations. v Lay Summary Agroforestry systems such as shade-grown coffee, where trees cover a proportion of the plantation, have received much attention for their value in supporting bird species, especially where forests have been lost. Little is known about how the attributes of shade-coffee plantations and the surrounding landscape interact to influence avian communities. I evaluated the influence and interaction of local (within plantations) and landscape (2km buffer around plantations) scales on bird richness and community completeness in two regions of Colombia with different extents of deforestation. Landscape variables had a greater effect on bird communities in the more forested region (Antioquia) than in the region with very low levels of forest cover (Cauca), while local variables were influential in both regions. My research will allow us to guide agroforestry management and conservation decisions, such as which components of coffee plantations and how much forest is needed in the landscape to support bird communities. vi Preface This thesis was based on previously collected data from a study in Colombia by Cornell University and Los Andes Universities in 2014 and 2016 that examined how attributes of coffee plantations affected the economic value of shade coffee. The fieldwork was carried out in 2014 and 2016 in two regions of the Colombian Andes: Antioquia and Cauca. The variables I used from that dataset include: region, number and species of birds, number and species of trees, number of coffee plants and the georeferentiation of each coffee plantation. Publications arising from this dataset include: Hernandez-Aguilera, J. N., Gómez, M. I., Rodewald, A. D., Rueda, X., Anunu, C., Bennett, R., & van Es, H. M. (2018). Quality as a Driver of Sustainable Agricultural Value Chains: The Case of the Relationship Coffee Model. Business Strategy and the Environment, 27(2), 179–198. https://doi.org/10.1002/bse.2009 I was responsible for cleaning, transforming, merging, and reshaping the dataset. I also calculated the variables at the landscape scale and the community completeness index. The manuscript and the analysis were written by me, with guidance and editing provided by my main committee members Drs. Scott Wilson, Peter Arcese, and Amanda Rodewald. Dr. Claire Kremen and Dr. Kai Chan also provided advice and important feedback on this thesis. A version of this thesis will be submitted for publication as a peer reviewed journal article, co-authored with Scott Wilson, Peter Arcese, Amanda Rodewald, and the collaborators involved in the initial dataset collection. vii Table of Contents Abstract ......................................................................................................................................... iii Lay Summary .................................................................................................................................v Preface ........................................................................................................................................... vi Table of Contents ........................................................................................................................ vii List of Tables ..................................................................................................................................x List of Figures ............................................................................................................................... xi List of Abbreviations .................................................................................................................. xii Acknowledgements .................................................................................................................... xiii Dedication ................................................................................................................................... xiv Chapter 1: Introduction ................................................................................................................1 Chapter 2: Effect of local habitat and landscape attributes on bird communities in shade coffee plantations in Colombia .....................................................................................................5 2.1 Synopsis .......................................................................................................................... 5 2.2 Methods........................................................................................................................... 6 2.2.1 Study Area .................................................................................................................. 6 2.2.2 Bird surveys and local data ......................................................................................... 7 2.2.3 Regional and landscape data ....................................................................................... 8 2.2.4 Bird richness and community completeness ............................................................. 11 2.2.5 Statistical analysis ..................................................................................................... 12 2.3 Results ........................................................................................................................... 14 2.3.1 Bird community ........................................................................................................ 14 viii 2.3.2 Descriptive statistic of local and landscape attributes .............................................. 14 2.3.3 Bird richness and community completeness ............................................................. 15 2.4 Discussion ..................................................................................................................... 20 Chapter 3: Conclusion .................................................................................................................26 3.1 Caveats .......................................................................................................................... 26 3.2 Conservation implications ............................................................................................ 27 References .....................................................................................................................................29 Appendices ....................................................................................................................................44 Appendix A Scatterplot matrix for local and landscape variables ............................................ 44 A.1 Antioquia................................................................................................................... 44 A.2 Cauca......................................................................................................................... 45 Appendix B Pearson’s correlation coefficients for local and landscape variables ................... 46 B.1 Antioquia................................................................................................................... 46 B.2 Cauca......................................................................................................................... 46 Appendix C Selection of the most important variables at each spatial scale. ........................... 47 Appendix D Set of candidate models to identify variables at local and landscape scales as important predictors of species richness in Antioquia and Cauca. ........................................... 48 Appendix E Set of candidate models to test the effect of local and landscape features on CCI in Antioquia and Cauca. ............................................................................................................ 50 Appendix F Regional forest cover within the joined area of the 2 km buffer around each coffee plantation in Antioquia and Cauca according to the forest cover map from 2016. Minimum forest area= 1ha. ........................................................................................................................ 52 ix Appendix G Landscape composition in the 2km buffer of each coffee plantation in Antioquia and Cauca according to the data layer of Colombian Land Cover from 2010 to 2012. Minimum mappable unit= 25ha. ............................................................................................... 53 Appendix H Summary of local (within plantation) and landscape (2km buffer) variables in two regions of Colombia: Antioquia and Cauca .............................................................................. 54 Appendix I Coefficient and 95% confidence intervals for the effect of local and landscape attributes on a. bird richness and b. community completeness in Antioquia and Cauca. ......... 55 Appendix J Coefficient and standard error of local and landscape attributes on a. bird richness and b. community completeness in Antioquia and Cauca. I report the averaged estimates for all models and the unconditional standard error (SE) of each variable. ................................... 56 Appendix K Coefficient and standard error of local and landscape attributes on a. bird richness and b. community completeness in Antioquia and Cauca. I report the estimates from the top model of each response variable and the standard error (SE). .................................................. 57 x List of Tables Table 1. Local and landscape variables description...................................................................... 10 Table 2. Akaike’s Criterion (AICC) results for effect of local and landscape attributes on bird richness in coffee plantations of two Colombian regions. TreeAb= Tree abundance, TreeRich= Tree richness, Coffee= Coffee density, Forest= Forest, Forest_ag= Forest-agriculture mosaic, Fdist= Distance to 1 ha forest, Forest mosaic= sum of forest and forest-agriculture mosaic. ∆ AICC are the AICC differences, wi is the Akaike weight support for each model. Most parsimonious (∆AIC>4) models are in bold. ................................................................................ 17 Table 3. Akaike’s Criterion (AICC) results for effect of local and landscape attributes on Community Completeness Index (CCI) in coffee plantations of two Colombian regions. TreeAb= Tree abundance, TreeRich= Tree richness, Coffee= Coffee density, Forest= Forest, Forest_ag= Forest-agriculture mosaic, Fdist= Distance to 1 ha forest, Forest mosaic= sum of forest and forest-agriculture mosaics. ∆ AICC are the AICC differences, wi is the Akaike weight support for each model.................................................................................................................. 18 xi List of Figures Figure 1. Study area. a. Location of Colombia. b. Study regions: Antioquia in the north and Cauca in the south. c. and d. Location of study sites within each study region. Black dots indicate the location of coffee plantations. ................................................................................................... 7 Figure 2. Coefficient and 95% confidence intervals for the effect of local and landscape attributes on a. bird richness and b. community completeness in Antioquia and Cauca. I report the estimates from the top model of each response variable and the 95% confidence interval. Local variables in violet and landscape variables in green. .......................................................... 19 Figure 3. Relationship between community completeness, forest-agriculture mosaic (landscape variable) and tree richness (local scale) in Antioquia. Graph constructed using the top-ranked model simulating a gradient of forest-agriculture cover and two levels of tree richness (1 and 8 species). Bands represent 95% confidence intervals for each prediction line. ............................. 20 xii List of Abbreviations AICc Akaike Information Criterion corrected for small sample sizes CCI Community Completeness Index Fdist Distance to 1ha forest Forest_ag Forest-agriculture mosaic GLM Generalized Linear Models SE Standard Error TreeAb Tree abundance TreeRich Tree richness ∆AIC AICC differences xiii Acknowledgements I would like to thank Drs. Scott Wilson and Peter Arcese for providing me with the opportunity to work in their lab and conduct this research. I am highly grateful for their patience, constant support, and guidance and for creating a stimulating and safe workplace for the past two years. I am also grateful to Dr. Amanda Rodewald for providing advice and valuable feedback on this research. Thank you to Drs. Claire Kremer and Kai Chan for their feedback and offering their time as members of the Supervisory and Examining Committee, respectively. Thanks to my colleagues in the Arcese-Wilson lab for their support and feedback during this research. Thank you to the collaborators / co-PIs of the study from which data for this research were generated: Juan N. Hernandez-Aguilera, Miguel I. Gómez, Ximena Rueda, Ruth Bennett, Colleen Anunu, and Amanda Rodewald. To Gustavo Suarez, Fernando Ayerbe Quiñones, and Juan Nicolás Diago Muñoz for conducting bird surveys and to the many students who collected local environmental data. To Federación Campesina del Cauca and Cooperativa Andes, and the administrative staff that provided logistical support (Maricel Vivas, Yimara Martinez and Fernando Restrepo). I am indebted to the coffee smallholders who participated in this study, which would not have happened without them. Funding for data collection was provided by the Cornell Lab of Ornithology, the Cornell Atkinson Center for Sustainability, the Einaudi Center and the Graduate School at Cornell University, and the School of Management at Universidad de los Andes in Colombia. None of this work would have been possible without Simon and my family's unconditional love and support. Thanks to my family for giving me the strength to chase my dreams, even when those dreams take me far from home. xiv Dedication To my family 1 Chapter 1: Introduction The tropical Andes are a global biodiversity hotspot that supports high richness of endemic species (Orme et al., 2005; Hof et al., 2011; Pimm et al., 2014). However, the mid-elevation forests that support many of these species have declined, due primarily to agricultural expansion (González et al., 2011), causing the loss and fragmentation of intact forest habitats that supported many species historically (Garavito et al., 2012). In the Colombian Andes, 40% of forest-dependent bird species have already lost 40% of their historical habitat, and these numbers are predicted to rise to 54% by 2040 (Negret et al., 2021). In addition, these losses are thought to play a role in ongoing declines of Nearctic-Neotropical migratory birds (Kramer et al., 2018; Wilson et al., 2018), of which at least 159 species overwinter in the region (Davidson et al., 2020; Céspedes et al., 2022). Given such high rates of forest loss, agroforestry systems such as shade-grown coffee plantations have received much attention for their potential value in supporting tropical species (Perfecto et al., 1996; Rice, 2003; Bhagwat et al., 2008). Compared to agroecosystems without trees, shade-grown coffee plantations support on average a much higher diversity and abundance of insects (Perfecto et al., 1996; Philpott et al., 2008; Briggs et al., 2013), mammals (Caudill & Rice, 2016; Guzmán et al., 2016), and birds (Roberts et al., 2000; Tejeda-Cruz & Sutherland, 2004; De Beenhouwer et al., 2013; Díaz-Bohórquez et al., 2015). In fact, shade-grown coffee can provide high-quality habitat for Neotropical migrants (Harvey & González Villalobos, 2007; Philpott et al., 2008; Colorado Z. & Rodewald, 2017; Narango et al., 2019; González et al., 2020; Céspedes et al., 2022). However, coffee plantations tend to support different species than found in intact Andean forest (Perfecto & Armbrecht, 2002; Rappole et al., 2003; Harvey & González 2 Villalobos, 2007; Philpott et al., 2008; Bakermans et al., 2009; Tscharntke et al., 2012; Sánchez-Clavijo et al., 2019). Several studies suggest that the type and extent of tree cover at local (within plantations) and landscape scales (around plantations) can influence biodiversity value in agroforestry systems (Anand et al., 2008; Gonthier et al., 2014; Frishkoff & Karp, 2019). For example, higher structural complexity and floristic diversity at the local scale in agroforestry systems in the tropics was associated with higher diversity of migratory birds (Bakermans et al., 2012), supported more diverse flocks of neotropical migrant and forest specialists (McDermott & Rodewald, 2014; McDermott et al., 2015), and was positively associated with the abundance of species of conservation concern (e.g., Cerulean Warbler (Setophaga cerulea); Bakermans et al., 2012). Though resident generalists are often common in agroforestry systems, especially mixed into flocks of Neotropical migrants (Philpott et al., 2008; McDermott & Rodewald, 2014), endemics, insectivores and understory specialists are rare in such systems (Greenberg et al., 2000; Colorado Z. & Rodewald, 2015) and tend to decline with agricultural intensification (Philpott et al., 2008). The habitat value of agroforestry ecosystems for local biodiversity may also be influenced by the amount and quality of remnant forest patches in the landscape. For example, the allocation of trees adjacent to crop fields is expected to have a greater effect on biodiversity in simple landscapes with little surrounding natural or semi-natural habitat than in highly forested landscapes (Tscharntke et al., 2005, 2012; Concepción et al., 2012). Similarly, research in Andean, Atlantic and Indian forests shows that landscape condition can shape the richness, abundance, composition, and trophic structure of insects and bird communities in agricultural habitats (Anand et al., 2008, 2010; Clough et al., 2009; González-Chaves et al., 2020). For 3 example, the proximity of forest fragments to crops was positively related to higher local abundance and richness of moths (Ricketts et al., 2001), bees (Armbrecht & Perfecto, 2003; Ricketts, 2004; Caudill et al., 2017; González-Chaves et al., 2020), and twig-nesting ants (Armbrecht & Perfecto, 2003) in agricultural sites. Similarly, shade-grown coffee plantations that were close to forest edges harbored higher richness and abundance of restricted-range bird species than those further away from the forest (Roberts et al., 2000; Anand et al., 2008). Increasing forest cover around crop fields also had a positive influence on the biodiversity of vertebrates in agroecosystems (Anand et al., 2010) and increased species richness and size of mixed flocks in shade coffee plantations (Colorado Z. & Rodewald, 2015). Much research into the influence of agroforestry on biodiversity has focused on the local attributes of farms and characteristics of the surrounding agricultural landscape (Philpott et al., 2008; Clough et al., 2009; Bakermans et al., 2012; McDermott & Rodewald, 2014; González-Chaves et al., 2020), but the manner in which local and landscape factors interact to affect diversity in communities of migratory and resident birds remains poorly understood. In particular, research on ‘shade coffee’ has focused mainly on small spatial scales and achieved limited replication over the range of conditions experienced by coffee growers due to differences in region, land use history, and wildlife communities. Moreover, whereas species richness, abundance, and diversity metrics (e.g., Shannon’s index, Simpson’s index) are typically employed to characterize species or community responses, very little is known about differences in the species composition with respect to the species pool (Partel et al., 2013). Incorporating community completeness metrics that allow us to determine how complete local communities are relative to the local species pool, provides important information to prioritize restoration or conservation actions (Lewis et al., 2016). In this study, I evaluated how bird species richness and 4 community completeness within shade-grown coffee plantations vary in response to local and landscape level variation in vegetation cover in two regions of Colombia with differing intensities of agriculture and amount of forest cover. Specifically, I examined the importance of attributes at the local scale, such as tree richness, tree abundance and coffee density, and the landscape-scale, such as plantation distance to forest and percent forest cover, in determining bird richness and community completeness in Antioquia and Cauca regions, which have differed in both land use history and rates of deforestation. 5 Chapter 2: Effect of local habitat and landscape attributes on bird communities in shade coffee plantations in Colombia 2.1 Synopsis Characteristics at the local and landscape scales can influence the diversity of birds within agroforestry systems (Gonthier et al., 2014). Bakermans et al. (2012) noted that migratory bird diversity tended to increase with tree diversity, heterogeneity in canopy cover, tree size, and the vertical stratification of vegetation. In contrast, less complex shade coffee plantations supported smaller, less diverse flocks of birds with fewer Neotropical migrants or resident forest specialists (McDermott & Rodewald, 2014; McDermott et al., 2015). Results from studies assessing the role of forest remnants around agroforestry systems indicate that biodiversity within agroecosystems could be enhanced by protecting and restoring forest patches around farms (Philpott et al., 2008; Sánchez-Clavijo et al., 2019; Cabral et al., 2021). Garibaldi et al. (2020) proposed that working landscapes should maintain at least 20% native habitat cover in the landscape in order to enhance connectivity across landscapes and protected areas. To date, studies of agroforestry systems have focused mainly on the independent effects of local and landscape scales. However, few have examined how the interaction of these two scales influence bird biodiversity and if the influence varies between regions differing in the extent of forest cover. I examined the main effect and interaction of local and landscape attributes on bird richness and community completeness in 160 coffee plantations in two regions of Colombia: Antioquia, where plantations were located in areas with higher forest cover and forest is included in protected areas and connected to a conservation corridor, and Cauca, where most forest cover surrounding plantations has been lost, and the remnants are isolated from more 6 extensive forest areas. I used data from a project initiated by Cornell and Los Andes Universities in 2014 that examined how attributes of coffee plantations affect the economic value of shade coffee (Hernandez-Aguilera et al., 2018). By understanding the influence of local versus landscape scales and how they interact, my work provides information to guide management strategies within and surrounding coffee plantations and how they could best support bird richness and community completeness in coffee production areas. 2.2 Methods 2.2.1 Study Area Study sites were located in two regions of the Colombian Andes: Antioquia and Cauca (Fig 1). Both regions have a bimodal rainfall regime (two wet and two dry seasons per year) with rainy periods from March to May and from September to November. However, rainfall differs between the regions; the midyear dry season is considerably more prominent in Cauca and rainfall values are lower during the rainy season than in Antioquia. Cauca and Antioquia represent two of the three regions with the highest bird richness in Colombia with 1,409 bird species reported for Cauca and 1,125 reported for Antioquia (Vélez et al., 2021). The regions share 64.1% of bird species. Data were collected from 160 shade-grown coffee plantations in Antioquia located on the east slope of the West Andes and in Cauca located on the west slope of the Central Andes. Plantations were situated at slightly higher elevations in Antioquia (mean: 1,775 m asl ± 13.16 SE, n=76) than in Cauca (mean: 1,755 m ± 9.46 SE, n=84). The landscapes surrounding plantations and the nature of remnant forest in the two focal regions differ widely. For example, intact forests in Antioquia are located within two protected areas – Farrallones de Citará (30,872 ha) (Corantioquia, 2005) and Cuchilla Jardin Tamesis 7 (28,061 ha) (Corantioquia, 2009) (Fig 1) – that are connected to a floristically diverse conservation corridor extending from the southern end of the Chocó and Darién in Colombia to Western Ecuador (6,000,000 ha) (CEPF, 2001; Corantioquia, 2005). In contrast, remnant forests in the landscapes surrounding study sites in Cauca is dominated by riparian forests that are not connected with more extensive forest areas. Figure 1. Study area. a. Location of Colombia. b. Study regions: Antioquia in the north and Cauca in the south. c. and d. Location of study sites within each study region. Black dots indicate the location of coffee plantations. 2.2.2 Bird surveys and local data Bird and vegetation data were collected at the local scale using a random sampling design in each coffee plantation to demarcate a rectangular plot of 20x50m. Three trained observers 8 surveyed birds using point counts with distance sampling following the same protocol in each region; one observer in Antioquia for 2014 and 2016 and a different observer each year in Cauca. Surveys were conducted once a year between January and March during a 10 min period between 05h45 and 11h00 where the observer recorded the species and number of individuals detected within a 100 m radius using visual and auditory cues. Birds that were flying over the plot or detected outside the coffee plantation were not included. All species observed on surveys were classified by their use of forest habitat (i.e., forest exclusive, forest optional, non-forest; Betts et al., 2017). Vegetation data were collected in the same plots where bird surveys were performed. Records were made of the species and number of woody shade trees taller than 2m, number and varieties of coffee plants, soil cover (i.e., bare soil, leaf litter, weed, other), and a measure of vertical stratification by counting the number of structural levels (Table 1). The location and elevation of each plot were recorded at the southwestern-most point using a GPS. Bird surveys were conducted in 2014 and 2016, while local vegetation variables were collected during 2016. 2.2.3 Regional and landscape data I calculated the amount of forest in each region, the distance from each coffee plantation to the forest and the amount of four land cover types in the landscape surrounding each coffee plantation. The regional forest cover was estimated using a forest cover map from 2016 at 30 m resolution (IDEAM, 2016). To calculate this, I first created a 2 km radius buffer from the southwestern-most corner of each coffee plantation and then joined the buffers. The estimate of regional forest cover was then estimated as the percent of the total joined buffer area in each region that was covered by forest patches ≥ 1 ha. (Appendix F). I used forest cover maps from 9 2014 and 2016 at 30 m resolution (IDEAM, 2014a, 2016) to calculate the distance from each plantation to forest patches as a straight-line from the edge of the plantation to the nearest forest patch ≥ 1 ha in area. I also asked how the landscape composition influenced bird richness and community completeness using four variables defined in Table 1: 1. agriculture, 2. forest, 3. forest-agriculture mosaic and 4. forest mosaic. Each variable was calculated as the percentage of area in each class within a 2 km radius of the southwestern-most corner of each coffee plantation. To define the landscape variables, I used the data layer of Colombian Land Cover from 2010 to 2012, which has a minimum mappable unit of 25 ha (scale 1:100.000) and is composed of 54 land use categories (IDEAM, 2014b). This Land Cover classification is based on satellite images with a resolution of 30 m. Areas dominated by a single cover with an extension of 25 ha or more are classified in independent land use categories (e.g., dense forest, clean pastures). In contrast, areas that consisted of a mosaic of two or more cover types where the coverage of each individual cover type was less than 25 ha are classified as mosaic land covers (e.g., mosaic of pastures, crops and natural areas, mosaic of pastures and natural areas). Of the 54 land cover categories in the dataset, 14 were found in the study sites and 11 were used to define the landscape variables (table 1): permanent shrub crops, clean pastures, pastures and weeds, mixture of pastures and crops, dense forest, fragmented forest, riparian forest, mosaic of pastures, crops and natural areas, mosaic of pastures and natural areas, mosaic of crops and natural areas, and secondary or transitional vegetation. The three remaining lands covers were not evaluated (i.e., continuous and discontinuous urban fabric and forest plantations). The relationship between explanatory variables was inspected graphically (Appendix A), and then Pearson´s correlation coefficients were computed. Variables that were considered 10 highly correlated (Pearson’s r>0.6) were not included in the same model (Appendix B). The distance from the plantations to the 1ha forest (range: 0.0-0.60 km) in Antioquia, and the percent of forest cover (range 0-10.8%) in Cauca had low variability and were not included in the models. Table 1. Local and landscape variables description Variable Description Local Variables Tree richness Number of shade tree species >2m height Tree abundance Number of shade trees >2m height Coffee density Number of coffee plants in a 100m2 area plot Leaf litter Percent of soil covered by leaf litter Structural levels Number of structural levels Landscape Variables Distance to 1 ha forest Distance from coffee plantation to the nearest forest patch ≥1 ha. Agriculture Percent of the area covered by patches of permanent shrub crops, clean pastures, pastures and weeds, and mixture of pastures and crops patches ≥25 ha. Forest Percent of the area covered by dense, riparian, and fragmented forest patches ≥25 ha. Forest-agriculture mosaic Percent of the area covered by small patches (≤25 ha) of forest, groups of trees and crops. Forest mosaic Sum of forest and forest-agriculture mosaics. 11 2.2.4 Bird richness and community completeness I measured the response of bird species richness (hereafter “bird richness”) and community completeness to covariates at local and landscape scales. Bird richness was calculated as the number of species per coffee plantation by year. I calculated the Community Completeness Index for each coffee plantation employing the logistic expression ln(observed richness/dark diversity) based on Partel et al., (2013). Observed richness is the number of species observed at each coffee plantation in 2014 and 2016. Dark diversity represents the number of species that are absent from the plantation (i.e., were not recorded during surveys) but have the potential to establish in the community within the plantation. I estimated Dark Diversity for each coffee plantation by employing the species co-occurrence methodology proposed by Lewis et al. (2016) using the R package DarkDiv (Carmona & Partel, 2021). The species co-occurrence is estimated using the Beal Index of sociological favourability (Beals, 1984) which determines the probability of finding a species at a given site (values ranging from 0 to 1) (De Cáceres & Legendre, 2008) based on how often they co-occur with the species that are confirmed to be present in the site (Trindade et al., 2021). The probabilities predicted by the Beal index depend on the frequency of the species in the dataset and their co-occurrences with all other species (i.e., probabilities are higher for more frequent species and viceversa) (Noreika et al., 2020). This dependence is corrected first by computing a probability distribution curve for each species from sites where the target species is present and second by determining species-specific thresholds according to user-defined percentiles (Munzbergova & Herben, 2004; Botta-Dukát, 2012; Lewis, Szava-Kovats, et al., 2016; Noreika et al., 2020). The species-specific threshold is applied to transform the index into presence/absence data for each species that was not observed at each site. 12 A species is considered in the estimate of Dark Diversity for sites where it is absent, and when the Beal index is greater than the species-specific threshold. To exclude bias through outliers, which are common in co-occurrence probability distributions (Botta-Dukát, 2012), I modelled the first, fifth, and tenth percentile thresholds (Lewis, Szava-Kovats, et al., 2016). I included an offset of 0.05 to make CCI calculations possible when dark diversity was 0 and calculate the CCI for each coffee plantations under the different thresholds (i.e., the first, fifth, and tenth percentile). To ensure the robustness of my estimations, I averaged the CCI for each coffee plantation as previously proposed by Gaüzère & Devictor, (2021). Positive CCI values indicate that the communities are more complete, and that observed diversity is greater than dark diversity, while negative values indicate the opposite (Trindade et al., 2021). 2.2.5 Statistical analysis I used Generalized Linear Models (GLM) with a negative binomial distribution to estimate bird species richness within plantations and accommodate over-dispersion, and I used a Gaussian distribution to estimate CCI within plantations. All co-variates were standardized to mean = 0, standard deviation = 1 to remove the influence of measurement scale and facilitate the comparison of effect sizes. Because the two regions differed in terms of bird communities and landscape composition, regions were analyzed separately. In the modeling process, I first ran a set of models with the local and landscape scale variables separately (Appendix C). The influential variables at these two scales were then considered in a second set of models where I examined the additive and interaction effects when the two scales were considered together. I ran a set of models for Antioquia and Cauca to identify variables at local and landscape scales that are important predictors of species richness (Appendix D) and community 13 completeness (Appendix E). For models examining bird richness, “year” was also included as an additive effect to account for the variability between years (the calculation of CCI incorporates both years and therefore year was not needed as a covariate). I also included a null model containing only the intercept to quantify the support in favor of models containing the local and landscape variables relative to the null model. I ranked all models based on Akaike Information Criterion corrected for small sample sizes (AICC) using the R package AICcmodavg (Mazerolle, 2020) I used two methods for comparing the strength of the effect of local and landscape variables on bird richness and community completeness in both regions. First, for each variable, I extracted the coefficients from the best-ranked model that included the variable of interest. Second, all models were averaged employing the model.avg function from the R package MuMIn (Barton, 2020). For this latter approach, I used the conditional average, which averages only over the models that include the variable of interest (Burnham & Anderson, 2007). Model averaging cannot be performed for the main effects in a model with an interaction and therefore, the models with a local by landscape scale interaction were not used to calculate model-averaged main effects estimates. Inferences for the effect of local-landscape scale interactions were based on the estimates from the top-supported model containing the interaction. Best-ranked model and model-averaged regression coefficients were used to describe their effect (positive/negative), and confidence intervals were estimated to assess the strength of their effect. 14 2.3 Results 2.3.1 Bird community A total of 159 bird species were recorded across regions (117 in Antioquia and 120 in Cauca). Although only half of these observed species were shared between regions, communities were comparable in terms of habitat associations, with roughly one-quarter of species being forest obligates (29% in Antioquia vs. 22% in Cauca), two-thirds being facultative forest species (62% vs 67%, respectively), and the remainder non-forest species (9% vs 11% respectively). 2.3.2 Descriptive statistic of local and landscape attributes The diversity of trees within coffee plantations differed between regions. The mean richness and abundance of trees was higher in Cauca (richness= 4 ± 0.3 SE, abundance: 8.9 ± 0.6 SE, n= 84) than in Antioquia (richness= 1.6 ± 0.2 SE, abundance= 3.0 ± 0.4 SE, n= 76), and coffee density was higher in Antioquia (mean= 28 coffee plants per 100m2 ± 1.6 SE, n= 76) than in Cauca (mean: 23 coffee plants per 100m2 ± 0.9 SE, n= 84). Shade in 28% of the 76 coffee plantations of Antioquia and shade in 5% of the 84 coffee plantations of Cauca was not provided by trees (i.e., woody plants) but by herbaceous plants such as banana (Musa x paradisiaca) and plantains (Musa acuminata). The regional forest cover was low in both sites, although considerably higher in Antioquia (20%) than in Cauca (1%) (Appendix F). The average proportion of the forest cover within the landscape (within 2 km) of each coffee plantation was far higher in Antioquia (5.9%, ± 0.9 SE, n= 76) than in Cauca (0.7%, ± 0.2 SE, n= 84). In contrast, the average proportion of forest-agriculture mosaic and forest mosaic in the landscape was similar in Antioquia (67.65 ± 2.31 SE vs. 73.56 ± 1.82 SE, n= 76) and Cauca (68.11 ± 2.12 SE vs. 68.79 ± 2.17 SE, n= 84) (Appendix G and H). Plantations in Cauca were also much farther from 1ha forests (mean= 15 5.6km, ± 0.6 SE, n= 84), than they were in Antioquia (mean= 0.15km, ± 0.0 SE, n= 76) (Appendix H). 2.3.3 Bird richness and community completeness The ability of landscape versus local attributes to explain variation in bird richness and community completeness differed between the two regions (Table 2 and 3). Figure 2 shows the effect size of each variable based on the coefficients from the best-ranked model that included the variable of interest (for model averaged results refer to Appendix I and J). Landscape variables had a greater (i.e., confidence intervals do not overlap zero) influence than local variables on richness in Antioquia while local variables had a greater effect than landscape variables on richness in Cauca (Fig 2.a, Appendix K). Richness in Antioquia increased with greater amount of forest mosaic (β= 0.129 ± 0.046 SE) and forest-agriculture mosaic cover (β= 0.121 ± 0.047 SE) at the landscape scale surrounding plantations and with greater tree abundance (β= 0.077 ± 0.045 SE) at the local scale within plantations. Richness in Cauca increased with greater tree richness (β= 0.117 ± 0.041 SE) and tree abundance (β= 0.100 ± 0.042 SE) within the coffee plantation, while there were no significant landscape scale effects (Table 2). Distance to 1ha forest had a negative but non-significant effect on bird richness in Cauca (β= -0.014 ± 0.042 SE) and coffee density had a negative effect on bird richness in both regions (Antioquia: β= -0.050 ± 0.047 SE; Cauca: β= -0.066 ± 0.042 SE), however the confidence intervals overlapped zero in both cases. Forest cover (Antioquia: β= -0.049 ± 0.049 SE) was not included in the most parsimonious model of Antioquia (and was not tested in Cauca). Local and landscape scales had an influential effect on community completeness in Antioquia, while local attributes had a greater effect in Cauca. The top-ranked model for 16 community completeness in Antioquia included an interaction between tree richness at the local scale and amount of forest-agriculture mosaic cover at the landscape scale (Interaction term β= 0.412 ± 0.220 SE, Table 3, Fig. 3). Specifically, community completeness increased with greater tree richness within plantations located in landscapes with an extent of forest-agriculture mosaic cover greater than 73% (Fig 3). All parsimonious models (∆AIC>4) for community completeness in Antioquia included landscape variables. When considering only additive effects, community completeness increased with greater forest-agriculture mosaic cover (β= 0.509 ± 0.185 SE) and forest mosaic (β= 0.457 ± 0.187 SE) in the surrounding landscape but decreased as forest cover (β= -0.380 ± 0.189 SE) increased (Appendix K). In Antioquia, the confidence interval of local variables such as tree richness (β= -0.176 ± 0.185 SE) and coffee density (β= 0.040 ± 0.189 SE) overlapped zero. In Cauca, tree richness (β= 0.278 ± 0.176 SE) within the coffee plantations and forest mosaic (β= 0.174 ± 0.181 SE) and forest-agriculture mosaic cover (β= 0.173 ± 0.181 SE) in the surrounding landscape had a positive effect on community completeness, but the confidence intervals overlapped zero (Fig. 2.b). Though coffee density was higher in Antioquia than in Cauca, its effect on community completeness was higher in Cauca (β= -0.374 ± 0.176 SE). Results from model averaging were very similar (Appendix J). 17 Table 2. Akaike’s Criterion (AICC) results for effect of local and landscape attributes on bird richness in coffee plantations of two Colombian regions. TreeAb= Tree abundance, TreeRich= Tree richness, Coffee= Coffee density, Forest= Forest, Forest_ag= Forest-agriculture mosaic, Fdist= Distance to 1 ha forest, Forest mosaic= sum of forest and forest-agriculture mosaic. ∆ AICC are the AICC differences, wi is the Akaike weight support for each model. Most parsimonious (∆AIC>4) models are in bold. Bird richness Antioquia Cauca Model ∆ AIC wi Model ∆ AIC wi TreeAb + Forest mosaic 0.00 0.30 TreeRich + Coffee 0.00 0.31 Forest mosaic 0.80 0.20 TreeRich 0.17 0.28 TreeAb + Coffee + Forest mosaic 0.98 0.19 TreeRich + Coffee + Fdist 2.04 0.11 TreeAb * Forest mosaic 1.58 0.14 TreeRich + Fdist 2.20 0.10 Forest_ag 2.12 0.10 TreeAb 2.52 0.09 TreeAb 5.59 0.02 TreeRich * Fdist 3.66 0.05 TreeAb + Coffee 6.35 0.01 Coffee density 5.73 0.02 yr 6.77 0.01 yr 5.74 0.02 Intercept 7.57 0.01 Fdist 7.49 0.01 Coffee density 7.59 0.01 Forest mosaic 7.70 0.01 Forest 7.86 0.01 Forest_ag 7.74 0.01 TreeRich 8.83 0.00 Intercept 32.82 0.00 18 Table 3. Akaike’s Criterion (AICC) results for effect of local and landscape attributes on Community Completeness Index (CCI) in coffee plantations of two Colombian regions. TreeAb= Tree abundance, TreeRich= Tree richness, Coffee= Coffee density, Forest= Forest, Forest_ag= Forest-agriculture mosaic, Fdist= Distance to 1 ha forest, Forest mosaic= sum of forest and forest-agriculture mosaics. ∆ AICC are the AICC differences, wi is the Akaike weight support for each model. Community Completeness Index Antioquia Cauca Model ∆ AIC wi Model ∆ AIC wi TreeRich * Forest_ag 0.00 0.29 TreeRich + Coffee 0.00 0.26 Forest_ag 0.02 0.28 Coffee 0.35 0.21 TreeRich + Forest_ag 1.32 0.15 TreeRich + Coffee + Fdist 0.97 0.16 Forest mosaic 1.50 0.13 TreeRich 2.35 0.08 Forest 3.39 0.05 Intercept 2.79 0.06 TreeRich + Coffee + Forest_ag 3.57 0.05 TreeRich + Fdist 3.19 0.05 Intercept 5.26 0.02 Fdist 3.32 0.05 TreeRich 6.80 0.01 TreeRich * Fdist 3.89 0.04 TreeAb 7.37 0.01 Forest_ag 4.01 0.03 Coffee 7.43 0.01 Forest mosaic 4.01 0.03 TreeRich + Coffee 9.02 0.00 TreeAb 4.66 0.02 19 Figure 2. Coefficient and 95% confidence intervals for the effect of local and landscape attributes on a. bird richness and b. community completeness in Antioquia and Cauca. I report the estimates from the top model of each response variable and the 95% confidence interval. Local variables in violet and landscape variables in green. 20 Figure 3. Relationship between community completeness, forest-agriculture mosaic (landscape variable) and tree richness (local scale) in Antioquia. Graph constructed using the top-ranked model simulating a gradient of forest-agriculture cover and two levels of tree richness (1 and 8 species). Bands represent 95% confidence intervals for each prediction line. 2.4 Discussion My results show that the degree to which local agroforestry practices affected two key components of biodiversity – species richness and community completeness – depended, in part, upon regional and landscape context. When coffee plantations are embedded in regions that still retain some continuous forest cover, bird richness and community completeness are influenced by habitat amount at both local and landscape scales, but the landscape scale appears to be more influential. Moreover, local by landscape-scale interactions can influence the bird community using coffee plantations in such a way that bird communities are more complete in plantations that have greater tree richness within the plantation and forest amount in the surrounding landscape. In contrast, when coffee plantations are embedded in regions with very little 21 remaining forest cover, bird richness and community completeness are determined almost entirely by habitat amount within plantations even when there is still considerable mixed forest-agriculture mosaic land cover. My comparison of bird response to agroforestry between two regions differing in forest cover extent showed how the influence of the spatial scale on bird biodiversity varied under certain levels of deforestation. Specifically, the landscape scale was more influential in Antioquia where the regional forest cover was 20%, than in Cauca where the regional forest cover was only 1%. Both regions were primarily forested ecosystems prior to human impact and both have experienced considerable deforestation (Henderson et al., 1991), but the extent of deforestation has been greater in the landscape around the study sites in Cauca. The difference in which the landscape scale influenced both regions (Fig 2) suggests that at least 20% of forest cover in the region is needed to observe landscape influence on bird communities within plantations. There are several possible mechanisms for why the landscape was influential in the more forested Antioquia region compared to the less forested Cauca region. First, in regions with few remaining forest patches, it is likely that few sources of populations remain in the landscape to influence bird communities within plantations despite the presence of considerable forest-agriculture mosaic cover in the landscape. Second, higher amounts of forest or higher quality forest-mosaic cover may provide individuals with greater resources, such as for nesting, feeding or roosting (Sekercioglu et al., 2007). These resources may in turn encourage a richer and more abundant bird community to remain within and surrounding plantations. Third, the intervening agricultural matrix in regions with low forest cover may reduce corridors for movement between forest patches and shade coffee plantations. In support of this latter mechanisms, studies in 22 Australia showed how a structurally complex matrix facilitated the movement of birds from native eucalyptus forest to exotic pine plantations (Tubelis et al., 2004). A similar finding was also observed in the tropical Andes where more forested areas facilitated the movement of flocking birds (Colorado Z. & Rodewald, 2015) and butterflies (Muriel & Kattan, 2009) across the landscape. My work also supports previous findings in other regions showing how habitat quality at the local scale becomes increasingly important as natural and semi-natural habitat cover in the surrounding landscape is lost. Batáry et al. (2010) found that the length of hedge rows between farm fields influenced bird species richness but only in simple landscapes where there was little surrounding semi-natural habitat. Anand et al. (2008) also showed that the influence of local scale habitat quality (proportion of native trees) was higher in coffee plantations that were further from native forest in the Western Ghats, India. The influence of local variables on bird richness and community completeness in Cauca and Antioquia highlights the importance of tree richness and abundance of shade coffee plantations for supporting bird communities across regions differing in forest extent. This finding is consistent with previous studies showing increased migratory bird diversity in agroforestry systems with complex structural (Colorado Z. et al., 2018) and floristic compositions (Bakermans et al., 2012). In contrast, less complex shade coffee plantations supported smaller, less diverse flocks of birds with fewer Neotropical migrants or resident forest specialists (McDermott & Rodewald, 2014; McDermott et al., 2015). The local scale was more influential on bird richness and community completeness in the more deforested region. I suggest two reasons why within plantation attributes were especially important in Cauca. First, plantations with a greater richness or abundance of tree species and 23 less intensive agriculture may provide diverse resources for birds and be more likely to retain forest-associated species resulting in greater richness and community completeness. Coffee plantations in Cauca included shade tree species (e.g., Cecropia ssp, Inga ssp, Erythryna ssp, Cordia alliodora) known to be important in bird diets (Bakermans et al., 2012; Newell et al., 2014; Peters et al., 2016; Narango et al., 2019) and also encountered as native species in forests (Idarraga P. & Callejas, 2011), whereas in Antioquia, those species were less frequent. For example, fruits of Cecropia ssp supports a broad array of frugivorous birds in coffee plantations (Carlo et al., 2004; Peters et al., 2016), and in Andean cloud forests (Palacio et al., 2016). Inga-dominated coffee plantations harbor higher richness of birds common in forest patches than plantations with other species (Greenberg et al., 1997). Similarly, Inga trees support a high diversity of both generalist migrant and resident species of birds (Newell et al., 2014) by providing nectar and insects (Johnson, 2000). Second, higher quality shade coffee plantations with greater tree richness and abundance may also be used more often by mobile flocks as they pass through a fragmented landscape even if they do not remain in those plantations (e.g., Fahrig 2007). In contrast, shade coffee plantations with low tree diversity may contrast with forest patches and reduce the movement of species from natural habitats to agroforestry systems with low floristic structure. Previous studies show that for forest-dependent bird species, higher amounts and greater structure complexity of natural and semi-natural habitats in the landscape reduce the contrast between forest habitats and coffee plantations, encouraging species movement to coffee plantations (Boesing et al., 2018). Several studies have also documented the importance of the landscape matrix for the dispersal (Perfecto & Vandermeer, 2008; Boesing et al., 2018), assemblages (Sánchez-de-Jesús et al., 24 2016), activity (Rodríguez-San Pedro & Simonetti, 2015), and biodiversity (Anand et al., 2010) of different taxa. Simple species richness statistics may obscure important differences in species composition across plantations (Partel et al., 2013). For example, although agroforestry systems maintain similar bird species richness in comparison with native forests (Tejeda-Cruz & Sutherland, 2004; Harvey & González Villalobos, 2007), the species in agroforestry systems are often different from forest (Tejeda-Cruz & Sutherland, 2004; Harvey & González Villalobos, 2007; Mendenhall et al., 2014, Philpott et al., 2008; Sánchez-Clavijo et al., 2019). In Costa Rica, remnant forests in working landscapes maintained relatively high bird richness compared to protected areas but harbored very distinct communities (Karp et al., 2019). Similarly, the composition of bird species in agroforestry systems can vary through a gradient of local and landscape factors (Clough et al., 2009), and this variation might not be reflected in changes in bird richness. By measuring community completeness, it is possible to detect how much of the agroforestry species pool is realized within each coffee plantation in response to local and landscape forest cover variation and propose conservation or restoration strategies at the appropriate scale for each habitat to reach its potential biodiversity. My analysis of community completeness showed that the landscape mediates the response of bird communities to local variables. Specifically, community completeness in the most forested region increased when tree richness at the local scale was greater, but only when the forest-agriculture mosaic cover at the landscape scale was greater than 73%. These results suggest that the agroforestry species pool in coffee plantations may switch depending on the amount of forest-agriculture mosaic in the landscape. When the amount of forest-agriculture mosaic cover in the landscape is low, low tree richness within coffee plantations may benefit the 25 completeness of agroforestry-related species pools that prefer open habitats. However, when the amount of forest-agriculture mosaic cover in the landscape is high, high tree richness at the local scale may benefit the completeness of the pool of species that prefer more forested habitats. This type of interaction has been previously observed elsewhere in tropical agroforestry systems. For example, in Costa Rica, the abundance of agricultural specialist species was higher in plantations where local and landscape forest cover was low, while forest specialists were most abundant across forested landscapes (Frishkoff & Karp, 2019). In Argentina, the woodland cover at the landscape scale determined how birds respond to agricultural intensity at the local scale. Specifically, the occurrence of birds declined with increasing agricultural intensity at the local scale when woodland cover at the landscape scale was low but remained constant or increased when woodland extent was intermediate or high (Macchi et al., 2020). 26 Chapter 3: Conclusion 3.1 Caveats My study has some important caveats and limitations. First, in testing the influence of the local and landscape scales, I examined richness and completeness at the community level rather than by migratory, foraging, habitat, functional, or taxonomic subgroupings that may respond differently to local and landscape variables (Frishkoff & Karp, 2019). Future studies aimed at developing conservation strategies for specific groups could focus on how scale effects differ on the richness and community completeness of these groups. Second, I did not consider the influence of tree-species identity or phenology (e.g., flowering) on bird biodiversity when I evaluated the influence of tree richness at the local scale on bird richness and community completeness. Previous studies have noted that tree species have different potential to attract neotropical migratory birds in coffee plantations. For example, Cerulean (Bakermans et al., 2012; Newell et al., 2014), Blackburnian, and Tennessee warbles in coffee plantations in Venezuela showed preferences for foraging in Inga trees (Newell et al., 2014). Similarly, in Colombia and Nicaragua, Neotropical migratory birds prioritized foraging on trees from the Fabaceae family while other tree species were avoided (Narango et al., 2019). Likewise, tree species with extended flowering or fruiting tend to attract many animal species (Peters et al., 2016). Differences in tree species composition of coffee plantations in Antioquia and Cauca may influence the response of bird biodiversity to tree richness. A further study could assess bird preferences for particular tree species and regional variation in these preferences. Third, my study only used data from birds co-occurring in agroforestry systems to calculate community completeness. Therefore, differences in community completeness reflect the shifts in the composition of the species pool specific to agroforestry systems but do not 27 reflect the differences relative to the regional species pool. To measure community completeness with respect to the regional species pool would require additional studies with surveys conducted across natural and agricultural land cover types. 3.2 Conservation implications My work showed that considering habitat quality at the local and landscape scale as well as the regional context where agroforestry systems are embedded could aid the development of conservation strategies for bird communities across diverse agricultural landscapes by implementing actions at the appropriate scale. My results suggest that reforestation strategies can benefit Andean bird diversity but will depend on the extent of forest cover. Where regional forest cover is very low, a focus on preserving and reforesting natural and semi-natural habitats around shade coffee plantations in Cauca would provide complementary or supplementary habitat to birds in coffee plantations and help increase richness and community completeness. However, as a more immediate need to support bird diversity in agricultural areas, reforestation strategies might best be targeted to increasing forest cover and quality within plantations. Increasing forest cover at the broader landscape could also help buffer negative impacts of agricultural intensification (i.e., increasing coffee plants) within plantations. For example, although coffee density was higher in coffee plantations in the more forested Antioquia region, the negative effect of coffee density on community completeness was stronger in the more deforested Cauca region. Tscharntke et al. (2005, 2012) suggested that forests in forested landscapes act as a source of species that compensate for the management intensity at the local scale (e.g., more coffee plants, lower tree richness). Planting more trees within coffee plantations may increase bird richness, but creation of new natural areas would be necessary to increase 28 sources of populations in the landscape that enhance communities of coffee plantations and compensate for the negative influence of coffee production intensity (Tscharntke et al., 2005) on community completeness within coffee plantations. Conservation strategies to enhance communities in agroforestry systems could also align with reforestation programs where there is currently much attention at a global scale. Besides providing connectivity, foraging habitats, nesting sites and shelter for wildlife (Manning et al., 2009), trees can store and absorb atmospheric CO2 contributing to reducing the impacts of climate change (Zomer et al., 2008). 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Landscape variables: Fdist: Distance to 1ha forest, Agriculture: Agriculture, Forest_ag: Forest-agriculture mosaic, Forest: Forest, Forest mosaic: sum of forest and forest-agriculture mosaic. 45 A.2 Cauca Local variables: TreeAb: Tree abundance, TreeRich: Tree richness, Coffee: Coffee density. Landscape variables: Fdist: Distance to 1ha forest, Agriculture: Agriculture, Forest_ag: Forest-agriculture mosaic, Forest: Forest, Forest mosaic: sum of forest and forest-agriculture mosaic. 46 Appendix B Pearson’s correlation coefficients for local and landscape variables B.1 Antioquia Local variables: TreeAb: Tree abundance, TreeRich: Tree richness, Coffee: Coffee density. Landscape variables: Fdist: Distance to 1ha forest, Agriculture: Agriculture, Forest_ag: Forest-agriculture mosaic, Forest: Forest, Forest mosaic: sum of forest and forest-agriculture mosaic. B.2 Cauca Local variables: TreeAb: Tree abundance, TreeRich: Tree richness, Coffee: Coffee density. Landscape variables: Fdist: Distance to 1ha forest, Agriculture: Agriculture, Forest_ag: Forest-agriculture mosaic, Forest: Forest, Forest mosaic: sum of forest and forest-agriculture mosaic. . 47 Appendix C Selection of the most important variables at each spatial scale. Akaike’s Criterion (AICC) results for the influence of local and landscape variables on a. bird richness and b. Community Completeness Index (CCI) in coffee plantations of two Colombian regions. Variables with the lowest ∆ AIC at each scale (in bold) were included in the additive and interaction models when the two scales were considered together. a. Bird Richness Antioquia Cauca Model ∆ AIC wi ∆ AIC wi Local TreeAb + yr 0.00 0.83 2.36 0.24 TreeRich + yr 3.24 0.17 0.00 0.76 Landscape Forest mosaic + yr 0.00 0.65 0.21 0.32 Fdist - - 0.00 0.36 Forest_ag + yr 1.32 0.33 0.25 0.32 Forest + yr 7.06 0.02 - - b. CCI Antioquia Cauca Model ∆ AIC wi ∆ AIC wi Local TreeAb 0.56 0.43 2.31 0.24 TreeRich 0.00 0.57 0.00 0.76 Landscape Forest mosaic 1.48 0.29 0.68 0.29 Fdist - - 0.0 0.41 Forest_ag 0.00 0.60 0.69 0.29 Forest 3.37 0.11 - - . 48 Appendix D Set of candidate models to identify variables at local and landscape scales as important predictors of species richness in Antioquia and Cauca. *Models tested only in Antioquia. + Models tested only in Cauca Hypothesis Candidate model Prediction Null model Intercept No covariates explain bird richness and the null model with only the intercept provides the most parsimonious model. Year Year No covariates explain bird richness, but richness varies between 2014 and 2016. Local structure Tree abundance High tree abundance increases species richness by increasing habitat availability for birds. Local composition Tree richness Increasing the number of species of shade trees within the coffee plantations increases bird richness by providing a broader variety of resources. Local coffee intensity Coffee density High coffee production intensity negatively influences bird richness by reducing habitat heterogeneity. Local structure and coffee intensity Tree abundance + Coffee density* Variables at the local scale have an additive effect on bird richness. Tree abundance has a positive effect on bird richness, but richness is decreased as coffee production increases Landscape forest cover Forest* Bird richness increases with increasing forest cover at the landscape scale because it provides habitat for a greater pool of species that may use coffee plantations Heterogenous landscape Forest-agriculture mosaic Bird richness increases when landscape heterogeneity is high because it supports a greater range of open country and forest species that may use coffee plantations Landscape forest mosaic Forest mosaic Bird richness increases when forest mosaic cover is high 49 Hypothesis Candidate model Prediction Forest distance Forest distance+ Bird richness decreases when distance between the plantation and forest increase. Local structure - landscape forest mosaic Tree abundance + Forest mosaic* Bird richness is positively influenced by both the number of trees within farms and the proportion of forest mosaic in the surrounding landscape. Interaction-Local structure and forest mosaic Tree abundance * Forest mosaic* Low and high levels of landscape forest mosaic will have little influence on the positive effect of high tree abundance on bird richness. At intermediate levels of forest mosaic cover, an increase in shade trees will increase bird richness. Local structure and coffee intensity - landscape forest mosaic Tree abundance + Coffee density + Forest mosaic* Greater tree abundance and landscape forest mosaic can reduce the negative influence of coffee production intensity on bird richness. Local composition - forest distance Tree richness + Forest distance+ Greater tree richness in the plantation can reduce the negative influence of higher distance between the plantation and forest. Interaction-Local composition and forest distance Tree richness * Forest distance+ High or low forest distance will have little influence on the value of local composition in maintaining a high bird richness. At an intermediate distance to the forest, increasing species of shade trees within the plantation will increase bird richness. Local composition and coffee intensity - forest distance Tree richness + Coffee density + Forest distance+ Greater tree richness within the plantation reduces the negative influence of coffee production intensity and high distance between the plantation and forest. . 50 Appendix E Set of candidate models to test the effect of local and landscape features on CCI in Antioquia and Cauca. *Models tested only in Antioquia. + Models tested only in Cauca Hypothesis Candidate model Prediction Null model Intercept No covariates explain CCI and the null model with only the intercept provides the most parsimonious model. Local structure Tree abundance High tree abundance increases bird community completeness by increasing habitat availability for birds. Local composition Tree richness Increasing the number of species of shade trees within the coffee plantations increases bird community completeness by providing a broader variety of resources. Local coffee intensity Coffee density High coffee production intensity negatively influences bird community completeness by reducing habitat heterogeneity. Local structure and coffee intensity Tree richness + Coffee density Variables at the local scale have an additive effect on bird community completeness. Tree richness has a positive effect on bird community completeness, but completeness decreases as coffee production increases Landscape forest cover Forest* Bird communities are more complete with increasing forest cover at the landscape scale because it provides habitat for a greater pool of species that may use coffee plantations. Heterogenous landscape Forest-agriculture mosaic Bird communities are more complete when landscape heterogeneity is high because it supports a greater range of open country and forest species that may use coffee plantations. Landscape forest mosaic Forest mosaic Bird communities are more complete when forest mosaic cover is high Forest distance Forest distance+ Bird communities are less complete when distance between the plantation and forest increase. Local composition – heterogenous landscape Tree richness + Forest-agriculture mosaic * Bird community completeness is positively influenced by both the number of species of trees within farms and the proportion of forest-agriculture mosaic in the surrounding landscape. 51 Hypothesis Candidate model Prediction Interaction-Local composition and heterogenous landscape Tree richness * Forest-agriculture mosaic * Low and high levels of landscape forest-agriculture mosaic will have little influence on the positive effect of high tree richness on bird community completeness. At intermediate levels of forest-agriculture mosaic cover, an increase in tree richness will increase bird community completeness. Local composition and coffee intensity - heterogenous landscape Tree richness + Coffee density + Forest-agriculture mosaic * Greater tree richness and landscape forest-agriculture mosaic can reduce the negative influence of coffee production intensity on bird community completeness. Local composition - forest distance Tree richness + Forest distance+ Greater tree richness in the plantation can reduce the negative influence of higher distance between the plantation and forest. Interaction-Local composition and forest distance Tree richness * Forest distance+ High or low forest distance will have little influence on the value of local composition in maintaining a high CCI. At an intermediate distance to the forest, an increase in species of shade trees within the plantation will increase CCI. Local composition and coffee intensity - forest distance Tree richness + Coffee density + Forest distance+ Greater tree richness within the plantation reduces the negative influence of coffee production intensity and high distance between the plantation and forest. . 52 Appendix F Regional forest cover within the joined area of the 2 km buffer around each coffee plantation in Antioquia and Cauca according to the forest cover map from 2016. Minimum forest area= 1ha. 53 Appendix G Landscape composition in the 2km buffer of each coffee plantation in Antioquia and Cauca according to the data layer of Colombian Land Cover from 2010 to 2012. Minimum mappable unit= 25ha. 54 Appendix H Summary of local (within plantation) and landscape (2km buffer) variables in two regions of Colombia: Antioquia and Cauca Values presented are mean ± SE, minimum values and maximum values. Antioquia Cauca Mean ± SE Min Max Mean ± SE Min Max Local variables Tree richness 1.6 ± 0.18 0.0 8.0 3.99 ± 0.27 0 11 Tree abundance 2.98 ± 0.38 0.0 13.0 8.91 ± 0.61 0 28 Coffee density 28 ± 1.55 6.0 80.0 23.12 ± 0.94 7 51 Landscape Variable Distance to forest (km) 0.15 ± 0.02 0 0.61 5.60 ± 0.56 0.11 18.43 Agriculture (%) 25.81 ± 1.78 0 46.53 29.42 ± 2.25 0 74.7 Forest-agriculture Mosaic (%) 67.65 ± 2.31 41.88 99.88 68.11 ± 2.12 25.24 99.93 Forest (%) 5.91 ± 0.90 0 39.77 0.68 ± 0.20 0 10.77 Forest Mosaic (%) 73.56 ± 1.82 50.53 99.88 68.79 ± 2.17 25.24 99.93 55 Appendix I Coefficient and 95% confidence intervals for the effect of local and landscape attributes on a. bird richness and b. community completeness in Antioquia and Cauca. I report the average estimates for all models and the 95% unconditional confidence interval of each response variable. Local variables are in violet and landscape variables are in green. 56 Appendix J Coefficient and standard error of local and landscape attributes on a. bird richness and b. community completeness in Antioquia and Cauca. I report the averaged estimates for all models and the unconditional standard error (SE) of each variable. a. Bird Richness Antioquia Cauca Variable Estimate SE Estimate SE Local Tree richness 0.007 0.031 0.117 0.041 Tree abundance 0.078 0.045 0.100 0.042 Coffee density -0.050 0.047 -0.066 0.042 Landscape Forest-agriculture 0.121 0.047 0.014 0.043 Forest mosaic 0.130 0.046 0.016 0.043 Forest -0.049 0.049 Forest distance -0.014 0.042 a. CCI Antioquia Cauca Variable Estimate SE Estimate SE Local Tree richness -0.176 0.187 0.275 0.177 Tree abundance 0.049 0.194 0.096 0.182 Coffee density 0.033 0.191 -0.374 0.176 Landscape Forest-agriculture 0.512 0.185 0.173 0.181 Forest mosaic 0.457 0.187 0.174 0.181 Forest -0.380 0.189 Forest distance -0.205 0.178 57 Appendix K Coefficient and standard error of local and landscape attributes on a. bird richness and b. community completeness in Antioquia and Cauca. I report the estimates from the top model of each response variable and the standard error (SE). a. Bird Richness Antioquia Cauca Variable Estimate SE Estimate SE Local Tree richness 0.007 0.031 0.117 0.041 Tree abundance 0.077 0.045 0.100 0.042 Coffee density -0.050 0.047 -0.066 0.042 Landscape Forest-agriculture 0.121 0.047 0.014 0.043 Forest mosaic 0.129 0.046 0.016 0.043 Forest -0.049 0.049 Forest distance -- -- -0.014 0.042 b. CCI Antioquia Cauca Variable Estimate SE Estimate SE Interaction Tree richness*Forest-ag 0.412 0.220 -- -- Local Tree richness -0.176 0.185 0.278 0.176 Tree abundance 0.049 0.194 0.096 0.182 Coffee density 0.040 0.189 -0.374 0.176 Landscape Forest-agriculture 0.509 0.185 0.173 0.181 Forest mosaic 0.457 0.187 0.174 0.181 Forest -0.380 0.189 Forest distance -- -- -0.196 0.176
Thesis/Dissertation
eng
Forestry
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Wilson, Scott D.
Arcese, Peter
Effect of local habitat and landscape attributes on bird species richness and community completeness in shade coffee plantations in Colombia
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