A graphical null model for scaling biodiversity-ecosystem functioning relationships

1. Global biodiversity is declining at rates faster than at any other
point in human history. Experimental manipulations at small spatial scales
have demonstrated that communities with fewer species consistently produce
less biomass than higher diversity communities. Understanding how the
global extinction crisis is likely to impact global ecosystem functioning
requires applying these local experimental results at substantially larger
spatial and temporal scales. 2. Here we propose a null model for scaling
biodiversity-ecosystem functioning relationships using observed
macroecological patterns. We use species-area and biomass-area curves to
predict species richness – biomass relationships at multiple scales and
validate these predictions with data from a Minnesota grassland and a
Panamanian tropical dry forest. 3. Our null model accurately predicts
species richness-biomass relationships across scales from these
species-area and biomass-area relationships. However, we note two
important caveats that will increase our ability to apply experimentally
collected data to the global scale problem of species loss. First when
ecosystem functioning is measured as per unit area (e.g., biomass m-2), as
is common in biodiversity-ecosystem functioning experiments, the slope of
the biodiversity ecosystem functioning relationship should decrease with
increasing scale. Alternatively, when ecosystem functioning is not
measured per unit area (e.g., summed total biomass), as is common in
scaling studies, the slope of the biodiversity-ecosystem functioning
relationship should increase with increasing spatial scale. Second, the
underlying macroecological patterns of biodiversity experiments are
predictably different from some naturally assembled systems. For example,
in non-successional naturally assembled ecosystem, biomass is unlikely to
change directionally through time. Biodiversity-ecosystem functioning
experiments, however, often start from bare ground and biomass increases
through time. From these underlying patterns, we would predict that the
slope of the biodiversity-productivity relationship in a naturally
assembled system not undergoing succession would decrease with increasing
time. Alternatively, in an experiment we would predict an increase over
time. 4. This paper provides a simple but novel null hypothesis for
scaling any relationship between biodiversity and any ecosystem function
in space and time. These predictions provide crucial insights into how and
when we can extend results from small scale biodiversity experiments to
naturally assembled regional and global ecosystems.

1. 全球生物多样性（global biodiversity）正以人类历史上前所未有的速率快速衰退。小空间尺度下的操控性实验已证实，物种丰富度更低的群落，其生物量产出始终低于多样性更高的群落。要明晰全球灭绝危机可能如何影响全球生态系统功能（ecosystem functioning），就需要将这些局地实验结果推广至尺度大得多的空间与时间维度。
2. 本研究基于观测得到的宏生态格局（macroecological patterns），提出了用于拓展生物多样性-生态系统功能关系（biodiversity-ecosystem functioning relationships）尺度的零模型（null model）。我们利用物种-面积曲线与生物量-面积曲线，预测多尺度下的物种丰富度-生物量关系，并以明尼苏达草原与巴拿马热带旱林的实测数据对预测结果进行验证。
3. 本研究提出的零模型可基于物种-面积与生物量-面积关系，准确预测不同尺度下的物种丰富度-生物量关系。但需注意两项关键限定条件，这将有助于我们更好地将实验获取的数据应用于全球尺度的物种丧失问题研究。其一，若以单位面积（如每平方米生物量，即biomass m⁻²）衡量生态系统功能（ecosystem functioning）（这也是生物多样性-生态系统功能实验中的常见做法），则生物多样性-生态系统功能关系（biodiversity-ecosystem functioning relationships）的斜率应随尺度增大而降低；反之，若不以单位面积衡量生态系统功能（ecosystem functioning）（如总累积生物量（summed total biomass）），则该关系的斜率应随空间尺度增大而升高。其二，生物多样性实验的核心宏生态格局（macroecological patterns）与部分自然组装生态系统存在可预见的差异。例如，在非演替的自然组装生态系统中，生物量不会随时间发生方向性变化；而生物多样性-生态系统功能实验通常从裸地起始，生物量随时间不断增加。基于这些核心格局，我们可预测：未经历演替的自然组装生态系统中，生物多样性-生产力关系（biodiversity-productivity relationship）的斜率会随时间推移而降低；而在实验环境中，该斜率则会随时间升高。
4. 本研究提出了一个简洁却新颖的零假设（null hypothesis），可用于拓展空间与时间维度上任意生物多样性与生态系统功能之间的关系。这些预测结果为我们厘清何时、以何种方式可将小尺度生物多样性实验的结果推广至区域乃至全球尺度的自然组装生态系统，提供了关键的理论启示。