Barnes Andrew D, Weigelt Patrick, Jochum Malte, Ott David, Hodapp Dorothee, Haneda Noor Farikhah, Brose Ulrich
Systemic Conservation Biology, J. F. Blumenbach Institute of Zoology and Anthropology, University of Göttingen, Berliner Strasse 28, 37073 Göttingen, Germany
Systemic Conservation Biology, J. F. Blumenbach Institute of Zoology and Anthropology, University of Göttingen, Berliner Strasse 28, 37073 Göttingen, Germany Biodiversity, Macroecology and Conservation Biogeography Group, Faculty of Forest Sciences, University of Göttingen, Büsgenweg 1, 37077 Göttingen, Germany
Philos Trans R Soc Lond B Biol Sci. 2016 May 19;371(1694). doi: 10.1098/rstb.2015.0279.
Predicting ecosystem functioning at large spatial scales rests on our ability to scale up from local plots to landscapes, but this is highly contingent on our understanding of how functioning varies through space. Such an understanding has been hampered by a strong experimental focus of biodiversity-ecosystem functioning research restricted to small spatial scales. To address this limitation, we investigate the drivers of spatial variation in multitrophic energy flux-a measure of ecosystem functioning in complex communities-at the landscape scale. We use a structural equation modelling framework based on distance matrices to test how spatial and environmental distances drive variation in community energy flux via four mechanisms: species composition, species richness, niche complementarity and biomass. We found that in both a tropical and a temperate study region, geographical and environmental distance indirectly influence species richness and biomass, with clear evidence that these are the dominant mechanisms explaining variability in community energy flux over spatial and environmental gradients. Our results reveal that species composition and trait variability may become redundant in predicting ecosystem functioning at the landscape scale. Instead, we demonstrate that species richness and total biomass may best predict rates of ecosystem functioning at larger spatial scales.
在大空间尺度上预测生态系统功能，取决于我们将局部样地尺度的研究结果扩展到景观尺度的能力，但这在很大程度上取决于我们对功能如何随空间变化的理解。生物多样性与生态系统功能研究的实验重点主要局限于小空间尺度，这阻碍了我们对上述问题的理解。为解决这一局限性，我们在景观尺度上研究了多营养级能量通量（衡量复杂群落中生态系统功能的指标）空间变化的驱动因素。我们使用基于距离矩阵的结构方程建模框架，来测试空间距离和环境距离如何通过物种组成、物种丰富度、生态位互补性和生物量这四种机制驱动群落能量通量的变化。我们发现，在热带和温带研究区域，地理距离和环境距离均间接影响物种丰富度和生物量，有明确证据表明，这些是解释群落能量通量在空间和环境梯度上变化的主要机制。我们的研究结果表明，在景观尺度上预测生态系统功能时，物种组成和性状变异性可能变得多余。相反，我们证明，物种丰富度和总生物量最能预测更大空间尺度上的生态系统功能速率。
