Checking billy barr’s snow log…
Climate change poses a unique problem for sessile species because individuals are unable to move to track their optimal habitat. Instead, population turnover governed by population processes must occur in order for the species distribution to change. Current methods to predict current and future species distributions are limited in that they are based on presence vs. absence data and use only currently observable climate regimes that may not reflect novel future climates. The first step towards improving our framework for predicting future species distributions is to develop a mechanistic model of species performance that uses contemporary data to predict the current spatial distribution of a specific species, then validate the model against field observations. Here we develop a Demographic Distribution Model (DDM) for Valeriana edulis, a long-lived species with a broad climatic niche, that uses an Integral Projection Model (IPM) to predict the individual- and population-level impacts of climate drivers (snowmelt timing and growing season temperature and precipitation) on population growth and fate. The complex interactions of the differing effects of the climate drivers were found to impact the vital rates of individual plants, which resulted in a range of predicted population growth rates across a landscape with varying climatic conditions. This proved to be an important tool for creating informed predictions about how species distributions respond to dynamically changing climate variables.
Knowledge graph centered on Nowcasting the distribution of <i> Valeriana eduli with 23 nodes and 80 connections. Top connected: Ipomopsis, I. aggregata, Ipomopsis aggregata, Sex-specific responses to climate change in plants, climate change effects on species interactions.
Items connected by shared entities, co-authorship, citations, or semantic similarity.
3 in Knowledge Commons, 26 external