Department of Computational Landscape Ecology, UFZ-Helmholtz Centre for Environmental Research, Leipzig, Germany.
Marine Ecology Department, Lurio University, Nampula, Mozambique.
Nat Ecol Evol. 2024 Apr;8(4):752-760. doi: 10.1038/s41559-024-02349-0. Epub 2024 Mar 6.
Intensive agriculture with high reliance on pesticides and fertilizers constitutes a major strategy for 'feeding the world'. However, such conventional intensification is linked to diminishing returns and can result in 'intensification traps'-production declines triggered by the negative feedback of biodiversity loss at high input levels. Here we developed a novel framework that accounts for biodiversity feedback on crop yields to evaluate the risk and magnitude of intensification traps. Simulations grounded in systematic literature reviews showed that intensification traps emerge in most landscape types, but to a lesser extent in major cereal production systems. Furthermore, small reductions in maximal production (5-10%) could be frequently transmitted into substantial biodiversity gains, resulting in small-loss large-gain trade-offs prevailing across landscape types. However, sensitivity analyses revealed a strong context dependence of trap emergence, inducing substantial uncertainty in the identification of optimal management at the field scale. Hence, we recommend the development of case-specific safety margins for intensification preventing double losses in biodiversity and food security associated with intensification traps.
集约化农业高度依赖农药和化肥,这是“养活世界”的主要策略。然而,这种传统的集约化与收益递减有关,可能导致“集约化陷阱”——在高投入水平下,生物多样性丧失的负反馈导致产量下降。在这里,我们开发了一种新的框架,该框架考虑了生物多样性对作物产量的反馈,以评估集约化陷阱的风险和规模。基于系统文献综述的模拟表明,集约化陷阱出现在大多数景观类型中,但在主要粮食生产系统中出现的程度较小。此外,最大产量的微小减少(5-10%)可能经常转化为生物多样性的大量增加,从而导致在整个景观类型中普遍存在小损失大收益的权衡。然而,敏感性分析显示出陷阱出现的强烈背景依赖性,导致在田间尺度上确定最佳管理存在很大的不确定性。因此,我们建议为防止与集约化陷阱相关的生物多样性和粮食安全的双重损失而制定特定案例的安全边际。