Responses of plant performance and functional diversity along a climate and land-use gradient in Mongolia

了解生态系统过程对气候和土地利用变化的响应是生态学在理论和应用方面的一个关键挑战。然而，到目前为止，气候和土地利用如何共同影响生态系统进程和生物量生产等服务，还没有得到充分了解。为数不多的可用多地点比较使用物种和功能性状多样性作为生态系统过程的预测因子，但侧重于气候或土地利用梯度。在这里，我们建议量化土地利用和气候对生态系统过程和服务的联合影响。我们选择了蒙古的牧场作为研究系统，其中降水梯度涵盖了广泛的环境条件。将在从沙漠到森林草原的15个地点开展工作，当地放牧梯度垂直。我们将分析20多个代表优势和特征类群的重点植物物种，并测量它们对气候和土地利用的反应。重点将放在与生物质生产力有关的一系列性能特征上，生物质生产力是该区域的关键生态系统服务。这将辅之以社区一级的方法，其中研究多样性、植物社区组成和选定关键性状的多样性，以捕捉整个社区的反应。我们将使用环境变量和代理放牧作为预测因子的反应，两个人的性状进行分析，在贝叶斯框架，以及社区的反应，如物种和功能多样性进行分析与多元统计。这两种方法将结合在一个综合建模方法中。这导致更好地了解生态系统的反应与正在进行的全球变化，并代表了管理建议的基础上，在不同的气候条件下，在半干旱到干旱景观的土地利用强度。

Understanding responses of ecosystem processes to climate and land use change is a key challenge in ecology under both theoretical and applied aspects. So far it is not fully understood, however, how climate and land-use jointly affect ecosystem processes and services such as biomass production. The few available multi-site comparisons use species and functional trait diversity as predictors of ecosystem processes, but focus either on climate or land-use gradients. Here we propose to quantify the joint effect of land-use and climate on ecosystem processes and services. We chose the rangelands of Mongolia as study system, where precipitation gradients cover a wide range of environmental conditions. Work will be conducted at 15 localities from deserts to forest steppes, with local grazing gradients running perpendicular. We will analyse more than twenty selected focal plant species representing dominant and characteristic taxa, and measure their response to climate and land-use. The focus will be on a range of performance traits relevant for biomass productivity as the key ecosystem service in the region. This will be supplemented by a community level approach, where diversity, plant community composition and diversity of selected key traits is studied to capture responses of entire communities. We will use environmental variables and proxies for grazing as predictors for responses of both individual traits to be analysed in a Bayesian framework, as well as community responses such as species and functional diversity to be analysed with multivariate statistics. Both approaches will be combined in a synthetic modelling approach. This leads to an improved understanding of ecosystem responses with on-going global change, and represents a basis for management recommendations with respect to land-use intensity under different climate conditions in semi-arid to arid landscapes.