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1. A Test of Species Distribution Model Transferability Across Environmental and Geographic Space for 108 Western North American Tree Species

   https://doi.org/10.3389/fevo.2021.689295  

   Charney, Noah D. ; Record, Sydne ; Gerstner, Beth E. ; Merow, Cory ; Zarnetske, Phoebe L. ; Enquist, Brian J. ( July 2021 , Frontiers in Ecology and Evolution)

   Predictions from species distribution models (SDMs) are commonly used in support of environmental decision-making to explore potential impacts of climate change on biodiversity. However, because future climates are likely to differ from current climates, there has been ongoing interest in understanding the ability of SDMs to predict species responses under novel conditions (i.e., model transferability). Here, we explore the spatial and environmental limits to extrapolation in SDMs using forest inventory data from 11 model algorithms for 108 tree species across the western United States. Algorithms performed well in predicting occurrence for plots that occurred in the same geographic region in which they were fitted. However, a substantial portion of models performed worse than random when predicting for geographic regions in which algorithms were not fitted. Our results suggest that for transfers in geographic space, no specific algorithm was better than another as there were no significant differences in predictive performance across algorithms. There were significant differences in predictive performance for algorithms transferred in environmental space with GAM performing best. However, the predictive performance of GAM declined steeply with increasing extrapolation in environmental space relative to other algorithms. The results of this study suggest that SDMs may be limited in theirmore »ability to predict species ranges beyond the environmental data used for model fitting. When predicting climate-driven range shifts, extrapolation may also not reflect important biotic and abiotic drivers of species ranges, and thus further misrepresent the realized shift in range. Future studies investigating transferability of process based SDMs or relationships between geodiversity and biodiversity may hold promise.« less
2. Clustering Species With Residual Covariance Matrix in Joint Species Distribution Models

   https://doi.org/10.3389/fevo.2021.601384  

   Bystrova, Daria ; Poggiato, Giovanni ; Bektaş, Billur ; Arbel, Julyan ; Clark, James S. ; Guglielmi, Alessandra ; Thuiller, Wilfried ( March 2021 , Frontiers in Ecology and Evolution)

   Modeling species distributions over space and time is one of the major research topics in both ecology and conservation biology. Joint Species Distribution models (JSDMs) have recently been introduced as a tool to better model community data, by inferring a residual covariance matrix between species, after accounting for species' response to the environment. However, these models are computationally demanding, even when latent factors, a common tool for dimension reduction, are used. To address this issue, Taylor-Rodriguez et al. ( 2017 ) proposed to use a Dirichlet process, a Bayesian nonparametric prior, to further reduce model dimension by clustering species in the residual covariance matrix. Here, we built on this approach to include a prior knowledge on the potential number of clusters, and instead used a Pitman–Yor process to address some critical limitations of the Dirichlet process. We therefore propose a framework that includes prior knowledge in the residual covariance matrix, providing a tool to analyze clusters of species that share the same residual associations with respect to other species. We applied our methodology to a case study of plant communities in a protected area of the French Alps (the Bauges Regional Park), and demonstrated that our extensions improve dimension reductionmore »and reveal additional information from the residual covariance matrix, notably showing how the estimated clusters are compatible with plant traits, endorsing their importance in shaping communities.« less
3. Clustering Species With Residual Covariance Matrix in Joint Species Distribution Models

   https://doi.org/doi: 10.3389/fevo.2021.601384  

   Daria Bystrova, Giovanni Poggiato ( January 2021 , Frontiers in ecology and evolution)
4. Hindcast‐validated species distribution models reveal future vulnerabilities of mangroves and salt marsh species

   https://doi.org/10.1002/ece3.9252  

   Hodel, Richard G. J. ; Soltis, Douglas E. ; Soltis, Pamela S. ( September 2022 , Ecology and Evolution)
5. Species Composition and Distribution of Jellyfish in a Seasonally Hypoxic Estuary, Hood Canal, Washington

   https://doi.org/10.3390/d12020053  

   Herrmann, BethElLee ; Keister, Julie E. ( February 2020 , Diversity)

   Seasonal hypoxia (≤2 mg dissolved oxygen L−1) can have detrimental effects on marine food webs. Recent studies indicate that some jellyfish can tolerate low oxygen and may have a competitive advantage over other zooplankton and fishes in those environments. We assessed community structure and distributions of cnidarian and ctenophore jellyfish in seasonally hypoxic Hood Canal, WA, USA, at four stations that differed in oxygen conditions. Jellyfish were collected in June through October 2012 and 2013 using full-water-column and discrete-depth net tows, concurrent with CTD casts to measure dissolved oxygen (DO). Overall, southern, more hypoxic, regions of Hood Canal had higher abundances and higher diversity than the northern regions, particularly during the warmer and more hypoxic year of 2013. Of fifteen species identified, the most abundant—the siphonophore Muggiaea atlantica and hydrozoan Aglantha digitale—reached peak densities > 1800 Ind m−3 and 38 Ind m−3, respectively. M. atlantica were much more abundant at the hypoxic stations, whereas A. digitale were also common in the north. Vertical distributions explored during hypoxia showed that jellyfish were mostly in the upper 10 m regardless of the oxycline depth. Moderate hypoxia seemed to have no detrimental effect on jellyfish in Hood Canal, and may have resulted inmore »high population densities, which could influence essential fisheries and trophic energy flow.« less