What's hot and what's not: Making sense of biodiversity 'hotspots'

Abstract

Conserving biogeographic regions with especially high biodiversity, known as biodiversity 'hotspots', is intuitive because finite resources can be focussed towards manageable units. Yet, biodiversity, environmental conditions and their relationship are more complex with multidimensional properties. Assessments which ignore this risk failing to detect change, identify its direction or gauge the scale of appropriate intervention. Conflicting concepts which assume assemblages as either sharply delineated communities or loosely collected species have also hampered progress in the way we assess and conserve biodiversity. We focus on the marine benthos where delineating manageable areas for conservation is an attractive prospect because it holds most marine species and constitutes the largest single ecosystem on earth by area. Using two large UK marine benthic faunal datasets, we present a spatially gridded data sampling design to account for survey effects which would otherwise be the principal drivers of diversity estimates. We then assess γ-diversity (regional richness) with diversity partitioned between α (local richness) and β (dissimilarity), and their change in relation to covariates to test whether defining and conserving biodiversity hotspots is an effective conservation strategy in light of the prevailing forces structuring those assemblages. α-, β- and γ-diversity hotspots were largely inconsistent with each metric relating uniquely to the covariates, and loosely collected species generally prevailed with relatively few distinct assemblages. Hotspots could therefore be an unreliable means to direct conservation efforts if based on only a component part of diversity. When assessed alongside environmental gradients, α-, β- and γ-diversity provide a multidimensional but still intuitive perspective of biodiversity change that can direct conservation towards key drivers and the appropriate scale for intervention. Our study also highlights possible temporal declines in species richness over 30 years and thus the need for future integrated monitoring to reveal the causal drivers of biodiversity change.

Keywords: Random Forest analysis; biodiversity; biodiversity hotspot; conservation; diversity partitioning; marine benthic fauna; rarefaction and extrapolation; species richness.