Global human "predation" on plant growth and biomass. Issue 6 (11th March 2020) - Jenkins, David G.; Haberl, Helmut; Erb, Karl‐Heinz; Nevai, Andrew L.
Abstract: Aim: Ecological theory is not often applied to human appropriation of net primary production (HANPP), which estimates reduction of natural net primary production (NPP) due to harvest and land use. Here we use predator–prey theory to evaluate HANPP as "predation". Macroecology and adaptive life history strategies also help evaluate relationships among global terrestrial HANPP, NPP, and plant biomass (B). Location: Lands worldwide. Time period: 2000. Major taxa studied: Terrestrial plants. Methods: HANPP and potential NPP allometric scaling were estimated for terrestrial ecoregions ( N  = 819, for 86% of global land surface area) in the year 2000. HANPP and NPP scaling were compared and projected to current and year 2050 conditions. NPP scaling for potential versus actual conditions were also compared, as were biomass turnover rates ( T ; per year). Results: Global HANPP scales predictably with B; consistent with predator–prey theory, HANPP scaling is not clearly satiated at greater B. NPP scaling supports adaptive life history strategies theory. HANPP scaling is c.  16% of NPP scaling; a conservative estimate compared to a grid‐based 22%. HANPP scaling could become 25–35% of potential NPP scaling by 2050 due to population growth, or be constrained to 20–26% of potential NPP scaling if resource use efficiency improves. However, B is more sensitive than NPP to human effects, and human population size and HANPP now dominate as predictors of T . Main conclusions: Three ecological theories converged here to broadly support prior empirical estimates and enable novel insights. B and T are more sensitive to global human impacts than is NPP and should be priorities for carbon budgets and conservation. Human population growth and resource use efficiency strongly affect terrestrial plant HANPP, B and T, and thus global carbon budget. Both human "top‐down" effects (evaluated here) and "bottom‐up" drivers (e.g., climate, nutrients, CO2 ) need to be incorporated into global carbon models.