Keyword: climate models

Global variability in leaf respiration in relation to climate, plant functional types and leaf traits

A challenge for the development of terrestrial biosphere models (TBMs) and associated land surface components of Earth system models (ESMs) is improving representation of carbon (C) exchange between terrestrial plants and the atmosphere, and incorporating biological variation arising from diversity in plant functional types (PFTs) and climate (Sitch et al., 2008; Booth et al., 2012; Prentice & Cowling, 2013; Fisher et al., 2014).

Risk assessment for two bird species in northern Wisconsin

Species distribution models for 147 bird species have been derived using climate, elevation, and distribution of current tree species as potential predictors (Matthews et al. 2011). In this case study, a risk matrix was developed for two bird species (fig. A2-5), with projected change in bird habitat (the x axis) based on models of changing suitable habitat resulting from changing climate and tree species habitat.

Bark beetles in a changing climate

Over the past decade, native bark beetles (Coleoptera: Curculionidae) have killed billions of trees across millions of hectares of forest from Alaska to Mexico. Although bark beetle infestations are a regular force of natural change in forested ecosystems, several current outbreaks occurring simultaneously across western North America are the largest and most severe in recorded history.

Managing uncertainty in climate-driven ecological models to inform adaptation to climate change

The impacts of climate change on forest ecosystems are likely to require changes in forest planning and natural resource management. Changes in tree growth, disturbance extent and intensity, and eventually species distributions are expected. In natural resource management and planning, ecosystem models are typically used to provide a "best estimate" about how forests might work in the future and thus guide decision-making.

Remote sensing data assimilation for a prognostic phenology model

Predicting the global carbon and water cycle requires a realistic representation of vegetation phenology in climate models. However most prognostic phenology models are not yet suited for global applications, and diagnostic satellite data can be uncertain and lack predictive power.