The influence of vegetation height heterogeneity on forest and woodland bird species richness across the United States

Harmonizing spatial scales and ecological theories to predict avian richness and functional diversity within forest ecosystems

Classic ecological theory has proven that temperature, precipitation and productivity organize ecosystems at broad scales and are generalized drivers of biodiversity within different biomes. At local scales, the strength of these predictors is not consistent across different biomes. To better translate these theories to localized scales, it is essential to determine the links between drivers of biodiversity. Here we harmonize existing ecological theories to increase the predictive power for species richness and functional diversity. We test the relative importance of three-dimensional habitat structure as a link between local and broad-scale patterns of avian richness and functional diversity. Our results indicate that habitat structure is more important than precipitation, temperature and elevation gradients for predicting avian species richness and functional diversity across different forest ecosystems in North America. We conclude that forest structure, influenced by climatic drivers, is essential for predicting the response of biodiversity with future shifts in climatic regimes.

Functional and phylogenetic diversity of an agricultural matrix avifauna: The role of habitat heterogeneity in Afrotropical farmland

Varied strategies to alleviate the loss of farmland biodiversity have been tested, yet there is still insufficient evidence supporting their effectiveness, especially when considering phylogenetic and functional diversity alongside traditional taxonomic diversity metrics. This conservation challenge is accentuated in the Afrotropics by the rapid agricultural expansion and intensification for the production of cash crops and by a comparative lack of research. In this study, we assessed how farming practices influence avian phylogenetic and functional diversity. We conducted point-count surveys to assess avian diversity in monocultures of tea and mixed crop farming systems surrounding the Nyungwe rainforest in south-west Rwanda, allowing us to investigate the drivers of avian diversity at farm level. Species composition was found to be moderately different between farm types, with mixed crop farms supporting higher phylogenetic diversity than tea plantations. There were no significant seasonal differences in species composition, functional or phylogenetic diversity. Overall, functional diversity did not differ between farm types, but the dispersion of trophic-related traits was significantly higher in mixed crop farms. Both functional and phylogenetic diversity were influenced by floristic diversity, vegetation height, tree number, and elevation to varying degrees. Our results also (i) highlight the role of farmland heterogeneity (e.g., crop species composition, height, and tree cover extent) in encouraging avian functional and phylogenetic diversity in the Afrotropics and (ii) indicate that the generally negative biodiversity impacts of monoculture agriculture can be partially alleviated by extensive agroforestry with an emphasis on indigenous tree species.

Diversity begets diversity: Low resource heterogeneity reduces the diversity of nut-nesting ants in rubber plantations

One of the most general patterns in ecology is the positive relationship between environmental heterogeneity and local diversity. On the one hand, increased resource heterogeneity provides more resources for diverse consumers in the community. On the other hand, increased structural heterogeneity creates variation in the environment's physical structure, thus allowing the coexistence of diverse species with different environmental requirements. Here, we examined the relative importance of resource and structural heterogeneity in determining the taxonomic, functional, and phylogenetic diversity of nut-nesting ants in natural rainforest and rubber plantation. The species richness of nut-nesting ants was 70% higher in rainforest than in rubber plantation. The clustered functional and phylogenetic structure in rubber plantation suggested a strong effect of environmental filtering in shaping ant functional and phylogenetic structure. Nesting heterogeneity (nut diversity) was the major factor explaining variation in taxonomic, functional, and phylogenetic diversity, suggesting that resource heterogeneity plays a major role in shaping the biodiversity patterns of nut-nesting ants. Overall, these results indicate that decreased resource diversity following the conversion of rainforest to rubber plantation can drive biodiversity loss in nut-nesting ants, through its effect on reducing both ant species, functional, and phylogenetic diversity. The decline in species richness and functional and phylogenetic diversity in the local ant community might have major effects on ecosystem functioning.

The relative influence of history, climate, topography and vegetation structure on local animal richness varies among taxa and spatial grains

1. Understanding the spatial scales at which environmental factors drive species richness patterns is a major challenge in ecology. Due to the trade-off between spatial grain and extent, studies tend to focus on a single spatial scale, and the effects of multiple environmental variables operating across spatial scales on the pattern of local species richness have rarely been investigated. 2. Here, we related variation in local species richness of ground beetles, landbirds, and small mammals to variation in vegetation structure and topography, regional climate, biome diversity, and glaciation history for 27 sites across the USA at two different spatial grains. 3. We studied the relative influence of broad-scale (landscape) environmental conditions using variables estimated at the site level (climate, productivity, biome diversity, and glacial era ice cover) and fine-scale (local) environmental conditions using variables estimated at the plot level (topography and vegetation structure) to explain local species richness. We also examined whether plot-level factors scale up to drive continental scale richness patterns. We used Bayesian hierarchical models and quantified the amount of variance in observed richness that was explained by environmental factors at different spatial scales. 4. For all three animal groups, our models explained much of the variation in local species richness (85-89%), but site-level variables explained a greater proportion of richness variance than plot-level variables. Temperature was the most important site-level predictor for explaining variance in landbirds and ground beetles richness. Some aspects of vegetation structure were the main plot-level predictors of landbird richness. Environmental predictors generally had poor explanatory power for small mammal richness, while glacial era ice cover was the most important site-level predictor. 5. Relationships between plot-level factors and richness varied greatly among geographical regions and spatial grains, and most relationships did not hold when predictors were scaled up to continental scale. Our results suggest that the factors that determine richness may be highly dependent on spatial grain, geography, and animal group. We demonstrate that instead of artificially manipulating the resolution to study multi-scale effects, a hierarchical approach that uses fine grain data at broad extents could help solve the issue of scale selection in environment-richness studies.

Model-Assisted Bird Monitoring Based on Remotely Sensed Ecosystem Functioning and Atlas Data

Urgent action needs to be taken to halt global biodiversity crisis. To be effective in the implementation of such action, managers and policy-makers need updated information on the status and trends of biodiversity. Here, we test the ability of remotely sensed ecosystem functioning attributes (EFAs) to predict the distribution of 73 bird species with different life-history traits. We run ensemble species distribution models (SDMs) trained with bird atlas data and 12 EFAs describing different dimensions of carbon cycle and surface energy balance. Our ensemble SDMs—exclusively based on EFAs—hold a high predictive capacity across 71 target species (up to 0.94 and 0.79 of Area Under the ROC curve and true skill statistic (TSS)). Our results showed the life-history traits did not significantly affect SDM performance. Overall, minimum Enhanced Vegetation Index (EVI) and maximum Albedo values (descriptors of primary productivity and energy balance) were the most important predictors across our bird community. Our approach leverages the existing atlas data and provides an alternative method to monitor inter-annual bird habitat dynamics from space in the absence of long-term biodiversity monitoring schemes. This study illustrates the great potential that satellite remote sensing can contribute to the Aichi Biodiversity Targets and to the Essential Biodiversity Variables framework (EBV class “Species distribution”).

Metrics of Lidar-Derived 3D Vegetation Structure Reveal Contrasting Effects of Horizontal and Vertical Forest Heterogeneity on Bird Species Richness

The structural heterogeneity of vegetation is a key factor for explaining animal diversity patterns at a local scale. Improvements in airborne light detection and ranging (lidar) technologies have enabled researchers to study forest 3D structure with increasing accuracy. Most structure–animal diversity work has focused on structural metrics derived from lidar returns from canopy and terrain features. Here, we built new lidar structural metrics based on the Leaf Area Density (LAD) at each vegetation height layer, and used these metrics to study how different aspects of forest structural heterogeneity explain variation in bird species richness. Our goals were to test: (1) whether LAD-based metrics better explained bird species richness compared to metrics based on the top of the canopy; and (2) if different aspects of structural heterogeneity had diverse effects on bird richness. We used discrete lidar data together with 61 breeding landbird points provided by the National Ecological Observatory Network at five forest sites of the eastern US. We used the lidar metrics as predictors of bird species richness and analyzed the shape of the response curves against each predictor. Metrics based on LAD measurements had better explanatory power (43% of variance explained) than those based on the variation of canopy heights (32% of variance explained). Dividing the forest plots into smaller grids allowed us to study the within-plot horizontal variation of the vertical heterogeneity, as well as to analyze how the vegetation density is horizontally distributed at each height layer. Bird species richness increased with horizontal heterogeneity, while vertical heterogeneity had negative effects, contrary to previous research. The increasing capabilities of lidar will allow researchers to characterize forest structure with higher detail. Our findings highlight the need for structure–animal diversity studies to incorporate metrics that are able to capture different aspects of forest 3D heterogeneity.

Multidirectional abundance shifts among North American birds and the relative influence of multifaceted climate factors

Shifts in species distributions are major fingerprint of climate change. Examining changes in species abundance structures at a continental scale enables robust evaluation of climate change influences, but few studies have conducted these evaluations due to limited data and methodological constraints. In this study, we estimate temporal changes in abundance from North American Breeding Bird Survey data at the scale of physiographic strata to examine the relative influence of different components of climatic factors and evaluate the hypothesis that shifting species distributions are multidirectional in resident bird species in North America. We quantify the direction and velocity of the abundance shifts of 57 permanent resident birds over 44 years using a centroid analysis. For species with significant abundance shifts in the centroid analysis, we conduct a more intensive correlative analysis to identify climate components most strongly associated with composite change of abundance within strata. Our analysis focus on two contrasts: the relative importance of climate extremes vs. averages, and of temperature vs. precipitation in strength of association with abundance change. Our study shows that 36 species had significant abundance shifts over the study period. The average velocity of the centroid is 5.89 km·yr^-1 . The shifted distance on average covers 259 km, 9% of range extent. Our results strongly suggest that the climate change fingerprint in studied avian distributions is multidirectional. Among 6 directions with significant abundance shifts, the northwestward shift was observed in the largest number of species (n = 13). The temperature/average climate model consistently has greater predictive ability than the precipitation/extreme climate model in explaining strata-level abundance change. Our study shows heterogeneous avian responses to recent environmental changes. It highlights needs for more species-specific approaches to examine contributing factors to recent distributional changes and for comprehensive conservation planning for climate change adaptation.

Remote sensing-based landscape indicators for the evaluation of threatened-bird habitats in a tropical forest

Avian species persistence in a forest patch is strongly related to the degree of isolation and size of a forest patch and the vegetation structure within a patch and its matrix are important predictors of bird habitat suitability. A combination of space‐borne optical (Landsat), ALOS‐PALSAR (radar), and airborne Light Detection and Ranging (LiDAR) data was used for assessing variation in forest structure across forest patches that had undergone different levels of forest degradation in a logged forest—agricultural landscape in Southern Laos. The efficacy of different remote sensing (RS) data sources in distinguishing forest patches that had different seizes, configurations, and vegetation structure was examined. These data were found to be sensitive to the varying levels of degradation of the different patch categories. Additionally, the role of local scale forest structure variables (characterized using the different RS data and patch area) and landscape variables (characterized by distance from different forest patches) in influencing habitat preferences of International Union for Conservation of Nature (IUCN) Red listed birds found in the study area was examined. A machine learning algorithm, MaxEnt, was used in conjunction with these data and field collected geographical locations of the avian species to identify the factors influencing habitat preference of the different bird species and their suitable habitats. Results show that distance from different forest patches played a more important role in influencing habitat suitability for the different avian species than local scale factors related to vegetation structure and health. In addition to distance from forest patches, LiDAR‐derived forest structure and Landsat‐derived spectral variables were important determinants of avian habitat preference. The models derived using MaxEnt were used to create an overall habitat suitability map (HSM) which mapped the most suitable habitat patches for sustaining all the avian species. This work also provides insight that retention of forest patches, including degraded and isolated forest patches in addition to large contiguous forest patches, can facilitate bird species retention within tropical agricultural landscapes. It also demonstrates the effective use of RS data in distinguishing between forests that have undergone varying levels of degradation and identifying the habitat preferences of different bird species. Practical conservation management planning endeavors can use such data for both landscape scale monitoring and habitat mapping.

Do birds see the forest for the trees? Scale-dependent effects of tree diversity on avian predation of artificial larvae

The enemies hypothesis states that reduced insect herbivory in mixed-species stands can be attributed to more effective top-down control by predators with increasing plant diversity. Although evidence for this mechanism exists for invertebrate predators, studies on avian predation are comparatively rare and have not explicitly tested the effects of diversity at different spatial scales, even though heterogeneity at macro- and micro-scales can influence bird foraging selection. We studied bird predation in an established forest diversity experiment in SW Finland, using artificial larvae installed on birch, alder and pine trees. Effects of tree species diversity and densities on bird predation were tested at two different scales: between plots and within the neighbourhood around focal trees. At the neighbourhood scale, birds preferentially foraged on focal trees surrounded by a higher diversity of neighbours. However, predation rates did not increase with tree species richness at the plot level and were instead negatively affected by tree height variation within the plot. The highest probability of predation was observed on pine, and rates of predation increased with the density of pine regardless of scale. Strong tree species preferences observed may be due to a combination of innate bird species preferences and opportunistic foraging on profitable-looking artificial prey. This study therefore finds partial support for the enemies hypothesis and highlights the importance of spatial scale and focal tree species in modifying trophic interactions between avian predators and insect herbivores in forest ecosystems.