Biogeographic multi‐species occupancy models for large‐scale survey data

Ecologists often seek to infer patterns of species occurrence or community structure from survey data. Hierarchical models, including multi-species occupancy models (MSOMs), can improve inference by pooling information across multiple species via random effects. Originally developed for local-scale survey data, MSOMs are increasingly applied to larger spatial scales that transcend major abiotic gradients and dispersal barriers. At biogeographic scales, the benefits of partial pooling in MSOMs trade off against the difficulty of incorporating sufficiently complex spatial effects to account for biogeographic variation in occupancy across multiple species simultaneously. We show how this challenge can be overcome by incorporating preexisting range information into MSOMs, yielding a “biogeographic multi-species occupancy model” (bMSOM). We illustrate the bMSOM using two published datasets: Parulid warblers in the United States Breeding Bird Survey and entire avian communities in forests and pastures of Colombia's West Andes. Compared with traditional MSOMs, the bMSOM provides dramatically better predictive performance at lower computational cost. The bMSOM avoids severe spatial biases in predictions of the traditional MSOM and provides principled species-specific inference even for never-observed species. Incorporating preexisting range data enables principled partial pooling of information across species in large-scale MSOMs. Our biogeographic framework for multi-species modeling should be broadly applicable in hierarchical models that predict species occurrences, whether or not false absences are modeled in an occupancy framework

Ignoring variation in wood density drives substantial bias in biomass estimates across spatial scales

Rapid development of remote sensing and Light Detection and Ranging (LiDAR) technology has refined estimates of tree architecture and extrapolation of biomass across large spatial scales. Yet, current biomass maps show significant discrepancies and mismatch to independent ground data. A potential obstacle to accurate biomass estimation is the loss of information on wood density, which can vary at local and regional scales, in the extrapolation process. Here we investigate if variation in wood specific gravity (WSG) substantially impacts the distribution of above-ground biomass (AGB) across a range of scales from local plots to large regions. We collected wood cores and measured tree volume in 341 forest sites across large altitudinal and climatic gradients in Colombia. At all spatial scales, variation in WSG was substantial compared to variation in volume. Imputing study-wide average values of WSG induced regional biases in AGB estimates of almost 30%, consequently undervaluing the difference between forest areas of low and high average wood density. Further, neither stem size nor climate usefully predicted WSG when accounting for spatial dependencies among our sampling plots. These results suggest that remote sensing- and LiDAR-based projections to biomass estimates can be considerably improved by explicitly accounting for spatial variation in WSG, necessitating further research on the spatial distribution of WSG and potential environmental predictors to advance efficient and accurate large-scale mapping of biomass

Land sparing outperforms land sharing for Amazonian bird communities regardless of surrounding landscape context

1. Two strategies are central to the debate regarding agricultural development: one integrates farming and conservation (land sharing), and the other separates farming and conservation, intensifying production to allow the offset of natural habitat (land sparing). The role of wildlife-friendly habitat in the wider surrounding landscape (landscape wildlife friendliness (WF)) in promoting farmland diversity is potentially an unexplored benefit of land sharing. 2. We sampled birds across primary forests and cattle pastures in the western Amazon, where terrestrial biodiversity peaks. We tested the hypothesis that increased landscape WF will lead to increased species richness (SR) on farmland, even at low levels of ‘on-farm’ wildlife-friendly habitat (farm WF). 3. We show that while there is a minor increase in SR linked to increased levels of landscape WF, a large component of the avian community is functionally absent. Most forest-dependent species are missing from pasture, even at high levels of farm WF. For these species, the preservation of blocks of contiguous forest under land sparing is vastly superior. 4. We modelled both strategies under different levels of production. Land sparing always retained significantly higher SR than land sharing, regardless of the level of landscape WF. 5. Synthesis and applications. Landscape wildlife friendliness (WF) provided through land sharing is of limited benefit to many tropical forest-dependent species that are unable to move across or utilise pasture, even at high levels of farm and landscape WF. To ensure the persistence of these species, policymakers should urgently implement sustainable intensification mechanisms to increase farmland productivity while enabling the protection of large blocks of spared natural habitat

Avian biodiversity losses from grazing of high Andean páramo

Páramos are high-elevation grassland-dominated ecosystems of the northern Andes that harbour large numbers of small-ranged and endemic species and provide important ecosystem services. Though páramos are increasingly managed with a conservation focus, they remain ecologically threatened, in part due to overgrazing. Here, we assess the impacts of grazing on bird communities using data collected from three páramo complexes in the Eastern Andes of Colombia. We (1) assess how densities of shrubs and frailejones—a keystone group of plants in the páramo—are impacted by grazing, (2) determine the influence of these vegetation features on bird occupancy, and (3) examine how bird species richness and community composition are impacted by páramo grazing. We find that grazing status strongly influences the vegetation characteristics of the páramo, resulting in large reductions in the abundance of shrubs and frailejones. These vegetation changes have significant impacts on páramo bird communities, with reduced shrub abundance resulting in lower occupancy for most species (4 out of 48). As a consequence, grazed páramo communities contain fewer bird species and vary in composition relative to those of natural páramo. However, the magnitudes of these differences are modest and it is possible that low-intensity grazing remains compatible with conservation management. We suggest that it is important to consider how páramo conservation may interact with management of adjacent montane forests and the potential for leakage effects resulting in increased deforestation outside of protected areas

Ecological filtering shapes the impacts of agricultural deforestation on biodiversity

The biodiversity impacts of agricultural deforestation vary widely across regions. Previous efforts to explain this variation have focused exclusively on the landscape features and management regimes of agricultural systems, neglecting the potentially critical role of ecological filtering in shaping deforestation tolerance of extant species assemblages at large geographical scales via selection for functional traits. Here we provide a large-scale test of this role using a global database of species abundance ratios between matched agricultural and native forest sites that comprises 71 avian assemblages reported in 44 primary studies, and a companion database of 10 functional traits for all 2,647 species involved. Using meta-analytic, phylogenetic and multivariate methods, we show that beyond agricultural features, filtering by the extent of natural environmental variability and the severity of historical anthropogenic deforestation shapes the varying deforestation impacts across species assemblages. For assemblages under greater environmental variability—proxied by drier and more seasonal climates under a greater disturbance regime—and longer deforestation histories, filtering has attenuated the negative impacts of current deforestation by selecting for functional traits linked to stronger deforestation tolerance. Our study provides a previously largely missing piece of knowledge in understanding and managing the biodiversity consequences of deforestation by agricultural deforestation