In many places around the world, spring events, like warming temperatures, are coming earlier and fall events are coming later than they have in the past. These changes have implications for the phenology, or the timing of natural life events (e.g. the timing of plant flowering in Spring or leaves falling in Autumn), of many plant species. However, not all species and regions are changing at the same rate, which can lead to mismatches (e.g. between the emergence of plants and pollinators in early spring). Many interactions in nature depend on timing and, as such, phenology affects nearly all aspects of the environment, including the abundance, distribution, and diversity of organisms, ecosystem services, food webs, even global water [...]
Summary
In many places around the world, spring events, like warming temperatures, are coming earlier and fall events are coming later than they have in the past. These changes have implications for the phenology, or the timing of natural life events (e.g. the timing of plant flowering in Spring or leaves falling in Autumn), of many plant species. However, not all species and regions are changing at the same rate, which can lead to mismatches (e.g. between the emergence of plants and pollinators in early spring). Many interactions in nature depend on timing and, as such, phenology affects nearly all aspects of the environment, including the abundance, distribution, and diversity of organisms, ecosystem services, food webs, even global water and carbon cycles.
Phenology is among the best indicators of climate change impacts, in large part because phenological events are some of the most sensitive biological responses to environmental changes. Researchers are rapidly developing datasets, models, and indices that can improve our understanding of changing phenology. However, most indices of phenological change are poorly suited for water-limited ecosystems, and existing models are lacking in their ability to represent phenological change at local scales that are relevant and useful for decision making.
This project is a step towards addressing these limitations. The project team aims to use local phenology data and climate information to build new phenology indices and models for the southwestern U.S. that address several significant information gaps, with a specific focus on creating useful and relevant data products and decision-support tools for managers. These models will be used to evaluate variations in historical phenology trends based on time period, plant type, geography, and moisture availability. The team plans to generate a phenology tool that resource managers in the Southwest can use to predict phenology events (e.g. plant green-up) based on a specified climate (historical, future near-term, and long-term). This work will help to ensure that phenological information can be used to inform conservation planning and resource management decisions in the Southwest.
Phenology, the study of seasonal natural phenomena — the timing of bird migrations or plant flowering, for example — has become a ‘leading indicator’ of climate change impacts, in large part because phenological events are among the most sensitive biological responses to climate change. Across the globe, many spring events are occurring earlier — and fall events later — than they did in the past. However, not all species and regions are changing at the same rate, which can lead to mismatches. Many interactions in nature depend on timing and, as such, phenology affects nearly all aspects of the environment, including the abundance, distribution, and diversity of organisms, ecosystem services, food webs, even global water and carbon cycles.
One significant barrier to progress in advancing our understanding and utilization of phenology information entails the ability of the existing models to represent phenological change at more local scales, where decisions are being made. The work described in this proposal represents a critical first step in addressing this need. We propose to transfer well-established methods used to develop models of phenology to the Southwest region specifically. In a sense, we expect to ‘downscale’ and calibrate models to the unique environment and species of the Southwest. Because we will work closely with stakeholders from the very beginning, we can make a reasonable promise to deliver information that not only advances the science, but makes the science immediately relevant and useful.