Spatial extent and impact of aquatic resources on terrestrial communities, individuals and trophic dynamics in tropical and temperate forests

在我的博士学位中，我的目标是扩大我们对水陆联系如何影响陆地群落和营养结构的理解，确定这些影响距离水生源头有多远，调查不同生物群之间和跨纬度的任何观察到的模式的共性，并对结果进行建模，供决策者应用。使用氮和碳稳定同位素分析和贝叶斯分析，我将跟踪水产资源进入陆地食物网的流量，并评估消费者在群落和物种水平上沿150米横断面的饮食广度(和其他同位素指标；Layman和Post，2008)的变化。我将通过样带、溪流和站点之间的阿尔法和贝塔多样性、丰度和生物量的变化来衡量群落结构反应。通过在巴西和欧洲的多个地点进行标准化抽样，我将能够比较和对比不同气候区域(热带、温带)、森林类型(亚马逊、大西洋雨林、针叶林和阔叶林)和纬度(苏格兰到大西洋雨林)之间的模式。最后，我的目标是利用这一来自两大洲的约700个采样群落的广泛数据集，开发一个包含营养动力学和环境参数的空间模型。该模型的目的是根据地理位置、森林类型和物种组成，估计河岸缓冲区需要多宽才能涵盖整个跨生态系统的动态。这个庞大的数据集将被格式化，上传到服务器上，供将来探索假说时使用。

For my PhD I aim to expand our understanding of how aquatic-terrestrial linkages impact terrestrial community and trophic structures, determine how far away from an aquatic source these impacts remain significant, investigate the generality of any observed patterns between distinct biomes and across latitude, and model the results for application by policymakers. Using nitrogen and carbon stable isotope analysis with Bayesian analyses I will track the flux of aquatic resources into terrestrial food webs and evaluate changes in the dietary breadth (and other isotopic metrics; Layman and Post, 2008) of consumers at the community and species level along 150m transects away from streams. I will measure community structure responses as changes in alpha and beta diversity, abundance and biomass between transect points, streams and sites. Through having a standardised method of sampling carried out in multiple sites in Brazil and Europe, I will be able to compare and contrast patterns between different climatic zones (tropical, temperate), forest types (Amazon, Atlantic rainforest, conifer plantation and broadleaf forest), and latitudes (Scotland to Atlantic Rainforest). Finally, I aim to use this extensive dataset of approx 700 sampled communities, from across two continents, to develop a spatial model incorporating trophic dynamics and environmental parameters. This model will aim to estimate how wide riparian buffer zones need to be to encompass full cross-ecosystem dynamics, depending on geographic location, forest type and species compositions. The large dataset will be formatted, uploaded to a server and made available for future hypotheses to be explored.