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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. 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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4. The influence of scale-dependent geodiversity on species distribution models in a biodiversity hotspot

   https://doi.org/10.1098/rsta.2023.0057  

   Gerstner, Beth E ; Blair, Mary E ; Bills, Patrick ; Cruz-Rodriguez, Cristian A ; Zarnetske, Phoebe L ( April 2024 , Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences)

   Dainton, John (Ed.)

   Improving models of species' distributions is essential for conservation, especially in light of global change. Species distribution models (SDMs) often rely on mean environmental conditions, yet species distributions are also a function of environmental heterogeneity and filtering acting at multiple spatial scales. Geodiversity, which we define as the variation of abiotic features and processes of Earth's entire geosphere (inclusive of climate), has potential to improve SDMs and conservation assessments, as they capture multiple abiotic dimensions of species niches, however they have not been sufficiently tested in SDMs. We tested a range of geodiversity variables computed at varying scales using climate and elevation data. We compared predictive performance of MaxEnt SDMs generated using CHELSA bioclimatic variables to those also including geodiversity variables for 31 mammalian species in Colombia. Results show the spatial grain of geodiversity variables affects SDM performance. Some variables consistently exhibited an increasing or decreasing trend in variable importance with spatial grain, showing slight scale-dependence and indicating that some geodiversity variables are more relevant at particular scales for some species. Incorporating geodiversity variables into SDMs, and doing so at the appropriate spatial scales, enhances the ability to model species-environment relationships, thereby contributing to the conservation and management of biodiversity.

   This article is part of the Theo Murphy meeting issue ‘Geodiversity for science and society’.

    

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5. Plant spectral diversity as a surrogate for species, functional and phylogenetic diversity across a hyper‐diverse biogeographic region

   https://doi.org/10.1111/geb.13306  

   Frye, Henry A. ; Aiello‐Lammens, Matthew E. ; Euston‐Brown, Douglas ; Jones, Cynthia S. ; Kilroy Mollmann, Hayley ; Merow, Cory ; Slingsby, Jasper A. ; van der Merwe, Helga ; Wilson, Adam M. ; Silander, Jr, John A. ; et al ( May 2021 , Global Ecology and Biogeography)

   With plant biodiversity under global threat, there is an urgent need to monitor the spatial distribution of multiple axes of biodiversity. Remote sensing is a critical tool in this endeavour. One remote sensing approach for detecting biodiversity is based on the hypothesis that the spectral diversity of plant communities is a surrogate of multiple dimensions of biodiversity. We investigated the generality of this ‘surrogacy’ for spectral, species, functional and phylogenetic diversity across 1,267 plots in the Greater Cape Floristic Region (GCFR), a hyper‐diverse region comprising several biomes and two adjacent global biodiversity hotspots.

   The GCFR centred in south‐western and western South Africa.

   All data were collected between 1978–2014.

   Vascular plants within the GCFR.

   Spectral diversity was calculated using leaf reflectance spectra (450–950 nm) and was related to other dimensions of biodiversity via linear models. The accuracy of different spectral diversity metrics was compared using 10‐fold cross‐validation.

   We found that a distance‐based spectral diversity metric was a robust predictor of species, functional and phylogenetic biodiversity. This result serves as a proof‐of‐concept that spectral diversity is a potential surrogate of biodiversity across a hyper‐diverse biogeographic region. While our results support the generality of spectral diversity as a biodiversity surrogate, we also find that relationships vary between different geographic subregions and biomes, suggesting that differences in broad‐scale community composition can affect these relationships.

   Spectral diversity was shown to be a robust surrogate of multiple dimensions of biodiversity across biomes and a widely varying biogeographic region. We also extend these surrogacy relationships to ecological redundancy to demonstrate the potential for additional insights into community structure based on spectral reflectance.

    

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