Agriculture rivals biomes in predicting global species richness

Species-area relationships (SARs) provide an avenue to model patterns of species richness and have recently been shown to vary substantially across regions of different climate, vegetation, and land cover. Given that a large proportion of the globe has been converted to agriculture, and considering the large variety in agricultural management practices, a key question is whether global SARs vary across gradients of agricultural intensity. We developed SARs for mammals that account for geographic variation in biomes, land cover and a range of land-use intensity indicators representing inputs (e.g. fertilizer, irrigation), outputs (e.g. yields) and system-level measures of intensity (e.g. human appropriation of net primary productivity - HANPP). We systematically compared the resulting SARs in terms of their predictive ability. Our global SAR with a universal slope was significantly improved by the inclusion of any one of the three variable types: biomes, land cover, and land-use intensity. The latter, in the form of human appropriation of net primary productivity (HANPP), performed as well as biomes and land-cover in predicting species richness. Other land-use intensity indicators had a lower predictive ability. Our main finding that land-use intensity performs as well as biomes and land cover in predicting species richness emphasizes that human factors are on a par with environmental factors in predicting global patterns of biodiversity. While our broad-scale study cannot establish causality, human activity is known to drive species richness at a local scale, and our findings suggest that this may hold true at a global scale. The ability of land-use intensity to explain variation in SARs at a global scale had not previously been assessed. Our study suggests that the inclusion of land-use intensity in SAR models allows us to better predict and understand species richness patterns.