The geographic scope of local interactions.

点击翻译按钮获取中文摘要

Human impacts are occurring at many scales in natural systems. Introduction of invasive species and climate change effects are two mostly negative examples. Spatial pattern analysis provides the means to map and identify many important drivers of these changes. I will link local measures of interactions between plants and insects, including pollinators, to climate. To do this, interactions with dominant plant species will be measured in four major ecosystems - forests, mountains, deserts, and grasslands. In each, either invasive species or climate change effects are used to structure all experiments. Webs of environmental sensors will also be placed at all sites, and regional climate data will be derived from public sources. Taken together, these linked datasets will provide a powerful test of the capacity for local interactions to filter large human impacts. This research is important to managers, conservation biologists, and policy makers. If dominant or foundational plant species respond differently to climate or invasive species, the effects of our disturbances may be magnified or perhaps buffered in some instances. This is critical information needed to predict how our natural systems will respond to change. It will also advance community and spatial ecology by providing a general set of protocols for coupling local interactions to larger geographic processes. Linking measures of biotic interactions to climate is very novel, and including insects speaks to important ecosystem services such as pollination. Anticipated outcomes include training of 50 HQP with 5 PhD students and 2 postdocs, peer-reviewed publications in top journals, establishment of distributed long-term sites for monitoring change, and estimates of biodiversity in several important ecosystems. Canada will benefit from this research directly since human impacts will be measured in Ontario forests, mountains in BC, and grasslands in Southern Ontario. We will also benefit by demonstrating international leadership in applying spatial and geographic tools to better understanding ecology.