Terry L. Root

Climate is a driver of biotic systems. It affects individual fitness, population dynamics, distribution and abundance of species, and ecosystem structure and function. Regional variation in climatic regimes creates selective pressures for the evolution of locally adapted physiologies, morphological adaptations (e.g., color patterns, surface textures, body shapes and sizes), and behavioral adaptations (e.g., foraging strategies and breeding systems). In the absence of humans, broad-scale, long-term consequences of climatic warming on wild organisms are generally predictable. Evidence from Pleistocene glaciations indicates that most species responded ecologically by shifting their ranges poleward and upward in elevation, rather than evolutionary through local adaptation (e.g., morphological changes). But these broad patterns tell us little about the relative importance of gradual climatic trends as compared to extreme weather events in shaping these processes. Here, evidence is brought forward that extreme weather events can be implicated as mechanistic drivers of broad ecological responses to climatic trends. They are, therefore, essential to include in predictive biological models, such as doubled CO2 scenarios.

Weather and climatic extremes can have serious and damaging effects on human society and infrastructure as well as on ecosystems and wildlife. Thus, they are usually the main focus of attention of the news media in reports on climate. There are some indications from observations concerning how climatic extremes may have changed in the past. Climate models show how they could change in the future either due to natural climate fluctuations or under conditions of greenhouse gas-induced warming. These observed and modeled changes relate directly to the understanding of socioeconomic and ecological impacts related to extremes.

Spatially explicit population models are becoming increasingly useful tools for population ecologists, conservation biologists, and land managers. Models are spatially explicit when they combine a population simulator with a landscape map that describes the spatial distribution of landscape features. With this map, the locations of habitat patches, individuals, and other items of interest are explicitly incorporated into the model, and the effect of changing landscape features on population dynamics can be studied. In this paper we describe the structure of some spatially explicit models under development and provide examples of current and future research using these models. Spatially explicit models are important tools for investigating scale‐related questions in population ecology, especially the response of organisms to habitat change occurring at a variety of spatial and temporal scales. Simulation models that incorporate real‐world landscapes, as portrayed by landscape maps created with geographic information systems, are also proving to be crucial in the development of management strategies in response to regional land‐use and other global change processes. Spatially explicit population models will increase our ability to accurately model complex landscapes, and therefore should improve both basic ecological knowledge of landscape phenomena and applications of landscape ecology to conservation and management.