Disentangling the effects of multiple environmental drivers on population changes within communities
Disentangling the effects of multiple environmental drivers on population changes within communities
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DOI：
10.1111/1365-2656.12829
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发表时间：
2018-07-01
影响因子：
4.8
通讯作者：
Boehning-Gaese, Katrin
中科院分区：
文献类型：
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作者：
Bowler, Diana E.;Heldbjerg, Henning;Boehning-Gaese, Katrin
1.不同的环境驱动因素对物种种群丰度变化的影响可能难以区分，因为它们往往同时发生作用。研究人员已经建立了包括环境变量（如年温度）或物种属性（如物种的温度偏好）的统计模型，这些模型被认为可以检测特定驱动因素（如气候变化）的影响。然而，这些方法往往是单独应用，或者，如果结合起来，没有明确比较。2.我们将这两种方法应用于丹麦陆生鸟类的社区数据集，获得了互补的见解。我们使用我们的分析来比较1983年至2013年期间气候变化和农业土地利用变化对社区内丰度变化的相对重要性。种群模型与物种年度丰度的社区数据相吻合，预测因子包括：物种属性（物种的温度和生境偏好），环境变量（气候和农业土地使用变化变量）或两者兼而有之。利用物种多度与环境变量之间的关系，确定了群落中物种平均多度变化的驱动因素。利用物种多度与其属性之间的关系，了解物种多度变化的种间差异驱动因素.温暖的冬天与群落水平的丰度呈正相关，温暖适应的物种比冷适应的物种有更多的积极的丰度变化。农业土地利用面积与社区水平的丰度呈负相关，鸟类使用高比例的草甸和栖息地专家有更多的负丰度变化比鸟类使用其他栖息地和栖息地通才。环境变量对农业土地利用变化的效应量较大，而物种属性对气候变化的效应量较大.环境数据的方法表明，农业土地利用的变化减少了社区的物种的平均丰度，影响总的社区规模，而基于物种属性的方法表明，气候变化造成物种之间的丰度变化，影响社区的组成。假设与具体驱动因素有关的环境变量和物种属性可一起使用，以提供关于不同驱动因素对社区影响的补充信息。
1. The effects of different environmental drivers on the changes in species' population abundances can be difficult to disentangle as they often act simultaneously. Researchers have built statistical models that include environmental variables (such as annual temperature) or species attributes (such as a species' temperature preference), which are assumed to detect the impacts of specific drivers (such as climate change). However, these approaches are often applied separately or, if combined, not explicitly compared.2. We show the complementary insights gained by applying both these approaches to a community dataset on Danish terrestrial birds. We use our analysis to compare the relative importance of climate change and agricultural land-use change for the abundance changes within the community between 1983 and 2013.3. Population models were fitted to the community data of species' annual abundances with predictors comprising: species attributes (species' temperature and habitat preferences), environmental variables (climatic and agricultural land-use change variables) or both. Relationships between species' abundances and environmental variables were used to identify the drivers associated with average abundance changes of species in the community. Relationships between species' abundances and their attributes were used to understand the drivers causing interspecific variation in abundance changes.4. Warmer winters were positively associated with community-level abundances, and warm-adapted species had more positive abundance changes than cold-adapted ones. Agricultural land-use area was negatively associated with community-level abundances, and birds using a high proportion of meadow and habitat specialists had more negative abundance changes than birds using other habitats and habitat generalists. Effect sizes of environmental variables were larger for agricultural land-use change while those of species attributes were larger for climate change.5. The environmental data approach suggested that agricultural land-use change has decreased the average abundances of species in the community, affecting total community size while the species attribute-based approach suggested that climate change has caused variation in abundance among species, affecting community composition. Environmental variables and species attributes that are hypothesized to link to specific drivers can be used together to provide complementary information on the impacts of different drivers on communities.