Keil, P. | bioRxiv Science

bioRxiv2018

Integrating global patterns and drivers of tree diversity across a continuum of spatial grains

What drives biodiversity and where are the most biodiverse places on Earth? The answer critically depends on spatial scale (grain), and is obscured by lack of data and mismatches in their grain. We resolve this with cross-scale models integrating global data on tree species richness (S) from 1338 local forest surveys and 287 regional checklists, enabling estimation of drivers and patterns of biodiversity at any desired grain. We uncover grain-dependent effects of both environment and biogeographic regions on S, with a positive regional effect of Southeast Asia at coarse grain that disappears at fine grains. We show that, globally, biodiversity cannot be attributed to purely environmental or regional drivers, since regions are environmentally distinct. Finally, we predict global maps of biodiversity at two grains, identifying areas of exceptional species turnover in China, East Africa, and North America. Our cross-scale approach unifies disparate results from previous studies regarding environmental versus biogeographic predictors of biodiversity, and enables efficient integration of heterogeneous data.

ecology↗

bioRxiv2016

Extinction rate has a complex and non-linear relationship with area

Aim.Biodiversity loss, measured as count of extinction events, is a key component of biodiversity change, and can significantly impact ecosystem services. However, estimation of the loss has focused mostly on per-species extinction rates measured over limited numbers of spatial scales, with no theory linking small-scale extirpations with global extinctions. Here we provide such link by introducing the relationship between area and per-species probability of extinction (PxAR) and between area and count of realized extinction events in that area (NxAR). We show theoretical and empirical forms of these relationships, and we discuss their role in perception and estimation of the current extinction crisis.\n\nLocationUSA, Europe, Czech Republic, Barro Colorado Island\n\nMethodsWe derived the expected forms of PxAR and NxAR from a range of theoretical frameworks based on theory of island biogeography, neutral models, and species-area relationships. We constructed PxAR and NxAR in five empirical datasets on butterflies, plants, trees and birds, collected over range of spatial scales.\n\nResultsBoth the theoretical arguments and empirical data support monotonically decreasing PxAR, i.e. per-species extinction probability decreasing with increasing area; however, we also report a rare theoretical possibility of locally increasing PxAR. In contrast, both theory and data revealed complex NxAR, i.e. counts of extinction events follow variety of relationships with area, including nonlinear unimodal, multimodal and U-shaped relationships, depending on region and taxon.\n\nMain conclusionsThe uncovered wealth of forms of NxAR can explain why biodiversity change (the net outcome of losses and gains) also appears scale-dependent. Furthermore, the complex scale dependence of PxAR and NxAR means that global extinctions indicate little about local extirpations, and vice versa. Hence, effort should be made to understand and report extinction crisis as a scale-dependent problem. In this effort, estimation of scaling relationships such as PxAR and NxAR should be central.

ecology↗