Search

Projected climatic warming has direct implications for future disturbance regimes, particularly fire-dominated ecosystems at high latitudes, where climate warming is expected to be most dramatic. It is important to ascertain the potential range of climate change impacts on terrestrial ecosystems, which is relevant to making projections of the response of the Earth system and to decisions by policymakers and land managers. Computer simulation models that explicitly model climate–fire relationships represent an important research tool for understanding and projecting future relationships. Retrospective model analyses of ecological models are important for evaluating how to effectively couple ecological models of fire dynamics with climate system models. This paper uses a transient landscape-level model of vegetation dynamics, Alaskan Frame-based Ecosystem Code (ALFRESCO), to evaluate the influence of different driving datasets of climate on simulation results. Our analysis included the use of climate data based on first-order weather station observations from the Climate Research Unit (CRU), a statistical reanalysis from the NCEP–NCAR reanalysis project (NCEP), and the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5). Model simulations of annual area burned for Alaska and western Canada were compared to historical fire activity (1950–2000). ALFRESCO was only able to generate reasonable simulation results when driven by the CRU climate data. Simulations driven by the NCEP and MM5 climate data produced almost no annual area burned because of substantially colder and wetter growing seasons (May–September) in comparison with the CRU climate data. The results of this study identify the importance of conducting retrospective analyses prior to coupling ecological models of fire dynamics with climate system models. The authors’ suggestion is to develop coupling methodologies that involve the use of anomalies from future climate model simulations to alter the climate data of more trusted historical climate datasets. [ABSTRACT FROM AUTHOR]

Water balance influences the distribution, abundance, and diversity of plant species across Earth's terrestrial system. In this study, we examine changes in the water balance and, consequently, the dryland extent across eight ecoregions of the north-central United States by quantifying changes in the growing season (May–September) moisture index (MI) by 2071–99, relative to 1980–2005, under three high-resolution (~4 km) downscaled climate projections (CNRM-CM5, CCSM4, and IPSL-CM5A-MR) of high-emission scenarios (RCP8.5). We find that all ecoregions are projected to become drier as based on significant decreases in MI, except four ecoregions under CNRM-CM5, which projects relatively more moderate warming and much greater increases in precipitation relative to the other two projections. The mean projected MI across the entire study area changes by from +4% to −33%. The proportion of dryland (MI < 0.65) is projected to increase under all projections, but more significantly under the warmer and drier projections represented by CCSM4 and IPSL-CM5A-MR; these two projections also show the largest spatial increases in the arid (33%–53%) and hyperarid (135%–180%) dryland classes and the greatest decrease in the dry subhumid (from −56% to −88%) dryland class. Among the ecoregions, those in the semiarid class have the highest increase in potential evapotranspiration, those in the nondryland and dry subhumid class have the largest decrease in MI, and those in the dry subhumid class have the greatest increase in dryland extent. These changes are expected to have important implications for agriculture, ecological function, biodiversity, vegetation dynamics, and hydrological budget. [ABSTRACT FROM AUTHOR]

Vegetation activity and phenology are significantly affected by climate change, and changes in vegetation activity and phenology can in turn affect regional or global climate patterns. As one of the world’s great biomes, temperate grasslands have undergone remarkable changes in recent decades, but the connections between vegetation activity and phenology changes and regional climate there have remained unclear. Using the observation minus reanalysis (OMR) method, this study investigated the possible effects of vegetation activity and vegetation growing season changes on air temperatures in temperate grasslands of China. The results showed that average NDVI of the temperate grassland significantly increased by 0.011 decade21 for the growing season during 1982–2015. The growing season started earlier and ended later, resulting in an extension. Increased vegetation activity during spring and autumn significantly warmed spring and autumn air temperatures by reducing albedo. By contrast, summer greening had no significant effect on summer temperature, due to the opposing effects of decreased albedo and enhanced evapotranspiration on temperature. The earlier start and later end of the growing season contributed to warmer spring and autumn air temperatures. As phenological changes had no significant effect on summer temperature, the extended growing season warmed air temperature. Our results suggest that the climate change–induced increasing vegetation activity and extended growing seasons can further aggravate regional warming in temperate grasslands of China, implying that the effects of vegetation activity and phenology changes on regional climate should be considered in climate models for accurately simulating climate change in temperate grasslands. [ABSTRACT FROM AUTHOR]