Beyond counts and averages: Relating geodiversity to dimensions of biodiversity

Abstract

Aim 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. Location Contiguous USA. Time period 2007–2016. Taxa studied Birds and trees. Methods 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. Results 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. Main conclusions 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.

Towards a systematics of ecodiversity: The EcoSyst framework

“…Most variables that were used for the analyses underpinning the NiN landscape‐type system are also relevant for other regions. Furthermore, data availability is rapidly increasing (e.g., as a result of the improved resolution and quality of remote sensors; Read et al., 2020; Zarnetske et al., 2019). The potential of remote sensing data for this purpose is exemplified by recently published global maps of physiographic features with fine‐grained resolution developed by a joint venture among scientists (e.g., Sayre et al., 2014).…”

Floristics of forests across low nutrient soils in Sulawesi, Indonesia

“…Recently, there has been a re-emphasis on the effects of geological variability upon biodiversity (Alahuhta, Toivanen, & Hjort, 2020;Read et al, 2020). Sulawesi not only has many types of geology (i.e., TA B L E 2 Indicator tree species for communities in forest plots across three regions of Sulawesi, Indonesia those underlying the soil types studied here), but it also has an ontogeny with the potential to influence biogeography irrespective of geological similarity or dissimilarity.…”

Hillslope geodiversity shapes ammonia-oxidizing communities and other microbial regulators in a semi-arid shrubland

“…The interaction between this physical background and rainfall patterns, particularly in water-limited ecosystems, modulates the effects of climate change on biodiversity. Geodiversity effects on biodiversity have been studied mostly for plants and animals (Cartwright, 2019; Ibáñez and Feoli, 2013; Read et al, 2020; Stavi et al, 2018b; Stein et al, 2014), and for large geographic scales, such as watersheds and landscapes (Ibáñez et al, 2012; Janion-Scheepers et al, 2016). Millimetric scale pedodiversity as a driver of microbial diversity has also been investigated (Upton et al, 2019).…”