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1. Beyond counts and averages: Relating geodiversity to dimensions of biodiversity

   https://doi.org/10.1111/geb.13061  

   Read, Quentin D. ; Zarnetske, Phoebe L. ; Record, Sydne ; Dahlin, Kyla M. ; Costanza, Jennifer K. ; Finley, Andrew O. ; Gaddis, Keith D. ; Grady, John M. ; Hobi, Martina L. ; Latimer, Andrew M. ; et al ( January 2020 , Global Ecology and Biogeography)

   We may be able to buffer biodiversity against the effects of ongoing climate change by prioritizing the protection of habitat with diverse physical features (high geodiversity) associated with ecological and evolutionary mechanisms that maintain high biodiversity. Nonetheless, the relationships between biodiversity and habitat vary with spatial and biological context. In this study, we compare how well habitat geodiversity (spatial variation in abiotic processes and features) and climate explain biodiversity patterns of birds and trees. We also evaluate the consistency of biodiversity–geodiversity relationships across ecoregions.

   Contiguous USA.

   2007–2016.

   Birds and trees.

   We quantified geodiversity with remotely sensed data and generated biodiversity maps from the Forest Inventory and Analysis and Breeding Bird Survey datasets. We fitted multivariate regressions to alpha, beta and gamma diversity, accounting for spatial autocorrelation among Nature Conservancy ecoregions and relationships among taxonomic, phylogenetic and functional biodiversity. We fitted models including climate alone (temperature and precipitation), geodiversity alone (topography, soil and geology) and climate plus geodiversity.

   A combination of geodiversity and climate predictor variables fitted most forms of bird and tree biodiversity with < 10% relative error. Models using geodiversity and climate performed better for local (alpha) and regional (gamma) diversity than for turnover‐based (beta) diversity. Among geodiversity predictors, variability of elevation fitted biodiversity best; interestingly, topographically diverse places tended to have higher tree diversity but lower bird diversity.

   Although climatic predictors tended to have larger individual effects than geodiversity, adding geodiversity improved climate‐only models of biodiversity. Geodiversity was correlated with biodiversity more consistently than with climate across ecoregions, but models tended to have a poor fit in ecoregions held out of the training dataset. Patterns of geodiversity could help to prioritize conservation efforts within ecoregions. However, we need to understand the underlying mechanisms more fully before we can build models transferable across ecoregions.

    

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2. Towards mapping biodiversity from above: Can fusing lidar and hyperspectral remote sensing predict taxonomic, functional, and phylogenetic tree diversity in temperate forests?

   https://doi.org/10.1111/geb.13516  

   Kamoske, Aaron G. ; Dahlin, Kyla M. ; Read, Quentin D. ; Record, Sydne ; Stark, Scott C. ; Serbin, Shawn P. ; Zarnetske, Phoebe L. ( May 2022 , Global Ecology and Biogeography)

   Rapid global change is impacting the diversity of tree species and essential ecosystem functions and services of forests. It is therefore critical to understand and predict how the diversity of tree species is spatially distributed within and among forest biomes. Satellite remote sensing platforms have been used for decades to map forest structure and function but are limited in their capacity to monitor change by their relatively coarse spatial resolution and the complexity of scales at which different dimensions of biodiversity are observed in the field. Recently, airborne remote sensing platforms making use of passive high spectral resolution (i.e., hyperspectral) and active lidar data have been operationalized, providing an opportunity to disentangle how biodiversity patterns vary across space and time from field observations to larger scales. Most studies to date have focused on single sites and/or one sensor type; here we ask how multiple sensor types from the National Ecological Observatory Network’s Airborne Observation Platform (NEON AOP) perform across multiple sites in a single biome at the NEON field plot scale (i.e., 40 m × 40 m).

   Eastern USA.

   2017–2018.

   Trees.

   With a fusion of hyperspectral and lidar data from the NEON AOP, we assess the ability of high resolution remotely sensed metrics to measure biodiversity variation across eastern US temperate forests. We examine how taxonomic, functional, and phylogenetic measures of alpha diversity vary spatially and assess to what degree remotely sensed metrics correlate with in situ biodiversity metrics.

   Models using estimates of forest function, canopy structure, and topographic diversity performed better than models containing each category alone. Our results show that canopy structural diversity, and not just spectral reflectance, is critical to predicting biodiversity.

   We found that an approach that jointly leverages spectral properties related to leaf and canopy functional traits and forest health, lidar derived estimates of forest structure, fine‐resolution topographic diversity, and careful consideration of biogeographical differences within and among biomes is needed to accurately map biodiversity variation from above.

    

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3. Landscape analyses using eDNA metabarcoding and Earth observation predict community biodiversity in California

   https://doi.org/10.1002/eap.2379  

   Lin, Meixi ; Simons, Ariel Levi ; Harrigan, Ryan J. ; Curd, Emily E. ; Schneider, Fabian D. ; Ruiz‐Ramos, Dannise V. ; Gold, Zack ; Osborne, Melisa G. ; Shirazi, Sabrina ; Schweizer, Teia M. ; et al ( July 2021 , Ecological Applications)

   Ecosystems globally are under threat from ongoing anthropogenic environmental change. Effective conservation management requires more thorough biodiversity surveys that can reveal system‐level patterns and that can be applied rapidly across space and time. Using modern ecological models and community science, we integrate environmental DNA and Earth observations to produce a time snapshot of regional biodiversity patterns and provide multi‐scalar community‐level characterization. We collected 278 samples in spring 2017 from coastal, shrub, and lowland forest sites in California, a complex ecosystem and biodiversity hotspot. We recovered 16,118 taxonomic entries from eDNA analyses and compiled associated traditional observations and environmental data to assess how well they predicted alpha, beta, and zeta diversity. We found that local habitat classification was diagnostic of community composition and distinct communities and organisms in different kingdoms are predicted by different environmental variables. Nonetheless, gradient forest models of 915 families recovered by eDNA analysis and using BIOCLIM variables, Sentinel‐2 satellite data, human impact, and topographical features as predictors, explained 35% of the variance in community turnover. Elevation, sand percentage, and photosynthetic activities (NDVI32) were the top predictors. In addition to this signal of environmental filtering, we found a positive relationship between environmentally predicted families and their numbers of biotic interactions, suggesting environmental change could have a disproportionate effect on community networks. Together, these analyses show that coupling eDNA with environmental predictors including remote sensing data has capacity to test proposed Essential Biodiversity Variables and create new landscape biodiversity baselines that span the tree of life.

    

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4. Mechanisms of community assembly explaining beta‐diversity patterns across biogeographic regions

   https://doi.org/10.1111/jvs.13032  

   Muñoz Mazón, Miguel ; Tello, J. Sebastián ; Macía, Manuel J. ; Myers, Jonathan A. ; Jørgensen, Peter M. ; Cala, Victoria ; Fuentes, Alfredo F. ; Torrez, Vania ; Arellano, Gabriel ; Price, ed., Jodi ( May 2021 , Journal of Vegetation Science)

   We examined tree beta diversity in four biogeographical regions with contrasting environmental conditions, latitude, and diversity. We tested: (a) the influence of the species pool on beta diversity; (b) the relative contribution of niche‐based and dispersal‐based assembly to beta diversity; and (c) differences in the importance of these two assembly mechanisms in regions with differing productivity and species richness.

   Lowland and montane tropical forests in the Madidi region (Bolivia), lowland temperate forests in the Ozarks (USA), and montane temperate forests in the Cantabrian Mountains (Spain).

   We surveyed woody plants with a diameter ≥2.5 cm following a standardized protocol in 236 0.1‐ha forest plots in four different biogeographical regions. We estimated the species pool at each region and used it to recreate null communities determined entirely by the species pool. Observed patterns of beta diversity smaller or greater than the null‐expected patterns of beta diversity implies the presence of local assembly mechanisms beyond the influence of the species pool. We used variation‐partitioning analyses to compare the contribution of niche‐based and dispersal‐based assembly to patterns of observed beta diversity and their deviations from null models among the four regions.

   (a) Differences in species pools alone did not explain observed differences in beta diversity among biogeographic regions. (b) In 3/4 regions, the environment explained more of the variation in beta diversity than spatial variables. (c) Spatial variables explained more of the beta diversity in more diverse and more productive regions with more rare species (tropical and lower‐elevation regions) compared to less diverse and less productive regions (temperate and higher‐elevation regions). (d) Greater alpha or gamma diversity did not result in higher beta diversity or stronger correlations with the environment.

   Overall, the observed differences in beta diversity are better explained by differences in community assembly mechanism than by biogeographical processes that shaped the species pool.

    

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5. Herbivory enhances the effect of environmental variability on plant community composition and beta diversity

   https://doi.org/10.1111/jvs.12862  

   Brambila, Alejandro ; Chesnut, John W. ; Prugh, Laura R. ; Hallett, Lauren M. ; Ward, ed., David ( April 2020 , Journal of Vegetation Science)

   Understanding the factors that shape biodiversity over space and time is a central question in ecology. Spatiotemporal environmental variation in resource availability can favor different species, generating beta diversity patterns that increase overall diversity. A key question is the degree to which biotic processes—in particular herbivory—enhance or dampen the effect of environmental variation on resource availability at different scales.

   We tested this question in a semi‐arid California grassland, which is characterized by high rainfall variability. The system supports giant kangaroo rats (Dipodomys ingens), which form mounds that structure spatial variability in soil nutrient availability.

   From 2008 to 2017 we implemented a cattle herbivory exclusion experiment to test whether herbivory moderates the effect of spatial and inter‐annual resource variability on plant biomass and diversity both on and off mounds.

   Grazing reduced local diversity regardless of mound status or amount of precipitation. However, we found that plant productivity was higher on than off mounds, increased following high rainfall years, and that grazing increased these on‐ versus off‐mound differences in wet years—especially after a major drought. Correspondingly, grazing led to on‐mound communities that were more different from each other and from off‐mound communities.

   Taken together, our results suggest that herbivory generally enhances habitat heterogeneity across this arid landscape, but is resource context‐dependent with greater effects seen in wetter years.

    

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