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Climate change threatens to shift vegetation, disrupting ecosystems and damaging human well-being. Field observations in boreal, temperate and tropical ecosystems have detected biome changes in the 20th century, yet a lack of spatial data on vulnerability hinders organizations that manage natural resources from identifying priority areas for adaptation measures. We explore potential methods to identify areas vulnerable to vegetation shifts and potential refugia. Global vegetation biomes. We examined nine combinations of three sets of potential indicators of the vulnerability of ecosystems to biome change: (1) observed changes of 20th-century climate, (2) projected 21st-century vegetation changes using the MC1 dynamic global vegetation model under three Intergovernmental Panel on Climate Change (IPCC) emissions scenarios, and (3) overlap of results from (1) and (2). Estimating probability density functions for climate observations and confidence levels for vegetation projections, we classified areas into vulnerability classes based on IPCC treatment of uncertainty. One-tenth to one-half of global land may be highly (confidence 0.80-0.95) to very highly (confidence ≥ 0.95) vulnerable. Temperate mixed forest, boreal conifer and tundra and alpine biomes show the highest vulnerability, often due to potential changes in wildfire. Tropical evergreen broadleaf forest and desert biomes show the lowest vulnerability. Spatial analyses of observed climate and projected vegetation indicate widespread vulnerability of ecosystems to biome change. A mismatch between vulnerability patterns and the geographic priorities of natural resource organizations suggests the need to adapt management plans. Approximately a billion people live in the areas classified as vulnerable.

The response of vegetation distribution, carbon, and fire to three scenarios of future climate change was simulated for California using the MC1 Dynamic General Vegetation Model. Under all three scenarios, Alpine/Subalpine Forest cover declined, and increases in the productivity of evergreen hardwoods led to the displacement of Evergreen Conifer Forest by Mixed Evergreen Forest. Grassland expanded, largely at the expense of Woodland and Shrubland, even under the cooler and less dry climate scenario where increased woody plant production was offset by increased wildfire. Increases in net primary productivity under the cooler and less dry scenario contributed to a simulated carbon sink of about 321 teragrams for California by the end of the century. Declines in net primary productivity under the two warmer and drier scenarios contributed to a net loss of carbon ranging from about 76 to 129 teragrams. Total annual area burned in California increased under all three scenarios, ranging from 9-15% above the historical norm by the end of the century. Annual biomass consumption by fire by the end of the century was about 18% greater than the historical norm under the more productive cooler and less dry scenario. Under the warmer and drier scenarios, simulated biomass consumption was initially greater, but then at, or below, the historical norm by the end of the century.

The magnitude of future climate change depends substantially on the greenhouse gas emission pathways we choose. Here we explore the implications of the highest and lowest Intergovernmental Panel on Climate Change emissions pathways for climate change and associated impacts in California. Based on climate projections from two state-of-the-art climate models with low and medium sensitivity (Parallel Climate Model and Hadley Centre Climate Model, version 3, respectively), we find that annual temperature increases nearly double from the lower B1 to the higher A1fi emissions scenario before 2100. Three of four simulations also show greater increases in summer temperatures as compared with winter. Extreme heat and the associated impacts on a range of temperature-sensitive sectors are substantially greater under the higher emissions scenario, with some interscenario differences apparent before midcentury. By the end of the century under the B1 scenario, heatwaves and extreme heat in Los Angeles quadruple in frequency while heat-related mortality increases two to three times; alpine/subalpine forests are reduced by 50-75%; and Sierra snowpack is reduced 30-70%. Under A1fi, heatwaves in Los Angeles are six to eight times more frequent, with heat-related excess mortality increasing five to seven times; alpine/subalpine forests are reduced by 75-90%; and snowpack declines 73-90%, with cascading impacts on runoff and streamflow that, combined with projected modest declines in winter precipitation, could fundamentally disrupt California's water rights system. Although interscenario differences in climate impacts and costs of adaptation emerge mainly in the second half of the century, they are strongly dependent on emissions from preceding decades.

The objective of this study was to dynamically simulate the response of vegetation distribution, carbon, and fire to the historical climate and to two contrasting scenarios of climate change in California. The results of the simulations for the historical climate compared favorably to independent estimates and observations, but validation of the results was complicated by the lack of land use effects in the model. The response to increasing temperatures under both scenarios was characterized by a shift in dominance from needle-leaved to broad-leaved life-forms and by increases in vegetation productivity, especially in the relatively cool and mesic regions of the state. The simulated response to changes in precipitation were complex, involving not only the effect of changes in soil moisture on vegetation productivity, but also changes in tree-grass competition mediated by fire. Summer months were warmer and persistently dry under both scenarios, so the trends in simulated fire area under both scenarios were primarily a response to changes in vegetation biomass. Total ecosystem carbon increased under both climate scenarios, but the proportions allocated to the wood and grass carbon pools differed. The results of the simulations underscore the potentially large impact of climate change on California ecosystems, and the need for further use and development of dynamic vegetation models using various ensembles of climate change scenarios.

We developed a new climate-sensitive vegetation state-and-transition simulation model (CV-STSM) to simulate future vegetation at a fine spatial grain commensurate with the scales of human land-use decisions, and under the joint influences of changing climate, site productivity, and disturbance. CV-STSM integrates outputs from four different modeling systems. Successional changes in tree species composition and stand structure were represented as transition probabilities and organized into a state-and-transition simulation model. States were characterized based on assessments of both current vegetation and of projected future vegetation from a dynamic global vegetation model (DGVM). State definitions included sufficient detail to support the integration of CV-STSM with an agent-based model of land-use decisions and a mechanistic model of fire behavior and spread. Transition probabilities were parameterized using output from a stand biometric model run across a wide range of site productivities. Biogeographic and biogeochemical projections from the DGVM were used to adjust the transition probabilities to account for the impacts of climate change on site productivity and potential vegetation type. We conducted experimental simulations in the Willamette Valley, Oregon, USA. Our simulation landscape incorporated detailed new assessments of critically imperiled Oregon white oak ( Quercus garryana ) savanna and prairie habitats among the suite of existing and future vegetation types. The experimental design fully crossed four future climate scenarios with three disturbance scenarios. CV-STSM showed strong interactions between climate and disturbance scenarios. All disturbance scenarios increased the abundance of oak savanna habitat, but an interaction between the most intense disturbance and climate-change scenarios also increased the abundance of subtropical tree species. Even so, subtropical tree species were far less abundant at the end of simulations in CV-STSM than in the dynamic global vegetation model simulations. Our results indicate that dynamic global vegetation models may overestimate future rates of vegetation change, especially in the absence of stand-replacing disturbances. Modeling tools such as CV-STSM that simulate rates and direction of vegetation change affected by interactions and feedbacks between climate and land-use change can help policy makers, land managers, and society as a whole develop effective plans to adapt to rapidly changing climate.

Aim Greenhouse‐induced warming and resulting shifts in climatic zones may exceed the migration capabilities of some species. We used fourteen combinations of General Circulation Models (GCMs) and Global Vegetation Models (GVMs) to investigate possible migration rates required under CO2‐doubled climatic forcing. Location Global. Methods Migration distances were calculated between grid cells of future biome type x and nearest same‐biome‐type cells in the current climate. In `base‐case' calculations, we assumed that 2 × CO2 climate forcing would occur in 100 years, we used ten biome types and we measured migration distances as straight‐line distances ignoring water barriers and human development. In sensitivity analyses, we investigated different time periods of 2 × CO2 climate forcing, more narrowly defined biomes and barriers because of water bodies and human development. Results In the base‐case calculations, average migration rates varied significantly according to the GVM used (BIOME3 vs. MAPSS), the age of the GCM (older‐ vs. newer‐generation GCMs), and whether or not GCMs included sulphate cooling or CO2 fertilization effects. However, high migration rates (≥ 1000 m year−1) were relatively common in all models, consisting on average of 17% grid cells for BIOME3 and 21% for MAPSS. Migration rates were much higher in boreal and temperate biomes than in tropical biomes. Doubling of the time period of 2 × CO2 forcing reduced these areas of high migration rates to c. 12% of grid cells for both BIOME3 and MAPSS. However, to obtain migration rates in the Boreal biome that were similar in magnitude to those observed for spruce when it followed the retreating North American Glacier, a radical increase in the period of warming was required, from 100 to >1000 years. A reduction in biome area by an order of magnitude increased migration rates by one to three orders of magnitude, depending on the GVM. Large water bodies and human development had regionally important effects in increasing migration rates. Main conclusions In conclusion, evidence from coupled GCMs and GVMs suggests that global warming may require migration rates much faster than those observed during post‐glacial times and hence has the potential to reduce biodiversity by selecting for highly mobile and opportunistic species. Several poorly understood factors that are expected to influence the magnitude of any such reduction are discussed, including intrinsic migrational capabilities, barriers to migration, the role of outlier populations in increasing migration rates, the role of climate in setting range limits and variation in species range sizes.

The Kyoto protocol has focused the attention of the public and policymarkers on the earth's carbon (C) budget. Previous estimates of the impacts of vegetation change have been limited to equilibrium \"snapshots\" that could not capture nonlinear or threshold effects along the trajectory of change. New models have been designed to complement equilibrium models and simulate vegetation succession through time while estimating variability in the C budget and responses to episodic events such as drought and fire. In addition, a plethora of future climate scenarios has been used to produce a bewildering variety of simulated ecological responses. Our objectives were to use an equilibrium model (Mapped Atmosphere-Plant-Soil system, or MAPSS) and a dynamic model (MC1) to (a) simulate changes in potential equilibrium vegetation distribution under historical conditions and across a wide gradient of future temperature changes to look for consistencies and trends among the many future scenarios, (b) simulate time-dependent changes in vegetation distribution and its associated C pools to illustrate the possible trajectories of vegetation change near the high and low ends of the temperature gradient, and (c) analyze the extent of the US area supporting a negative C balance. Both models agree that a moderate increase in temperature produces an increase in vegetation density and carbon sequestration across most of the US with small changes in vegetation types. Large increases in temperature cause losses of C with large shifts in vegetation types. In the western states, particularly southern California, precipitation and thus vegetation density increase and forests expand under all but the hottest scenarios. In the eastern US, particularly the Southeast, forests expand under the more moderate scenarios but decline under more severe climate scenarios, with catastrophic fires potentially causing rapid vegetation conversions from forest to savanna. Both models show that there is a potential for either positive or negative feedbacks to the atmosphere depending on the level of warming in the climate change scenarios.

Global warming is a key threat to biodiversity, but few researchers have assessed the magnitude of this threat at the global scale. We used major vegetation types (biomes) as proxies for natural habitats and, based on projected future biome distributions under doubled-CO2 climates, calculated changes in habitat areas and associated extinctions of endemic plant and vertebrate species in biodiversity hotspots. Because of numerous uncertainties in this approach, we undertook a sensitivity analysis of multiple factors that included (1) two global vegetation models, (2) different numbers of biome classes in our biome classification schemes, (3) different assumptions about whether species distributions were biome specific or not, and (4) different migration capabilities. Extinctions were calculated using both species-area and endemic-area relationships. In addition, average required migration rates were calculated for each hotspot assuming a doubled-CO2 climate in 100 years. Projected percent extinctions ranged from <1 to 43% of the endemic biota (average 11.6%), with biome specificity having the greatest influence on the estimates, followed by the global vegetation model and then by migration and biome classification assumptions. Bootstrap comparisons indicated that effects on hotpots as a group were not significantly different from effects on random same-biome collections of grid cells with respect to biome change or migration rates; in some scenarios, however, hotspots exhibited relatively high biome change and low migration rates. Especially vulnerable hotspots were the Cape Floristic Region, Caribbean, Indo-Burma, Mediterranean Basin, Southwest Australia, and Tropical Andes, where plant extinctions per hotspot sometimes exceeded 2000 species. Under the assumption that projected habitat changes were attained in 100 years, estimated global-warming-induced rates of species extinctions in tropical hotspots in some cases exceeded those due to deforestation, supporting suggestions that global warming is one of the most serious threats to the planet's biodiversity.

A Mapped Atmosphere-Plant-Soil System (MAPSS) has been constructed for simulating the potential biosphere impacts and biosphere-atmosphere feedbacks from climatic change. The system calculates the potential vegetation type and leaf area that could be supported at a site, within the constraints of the abiotic climate. Both woody vegetation and grass are supported and compete for light and water. The woody vegetation can be either trees or shrubs, evergreen or deciduous, and needleleaved or broadleaved. A complete site water balance is calculated and integrates the vegetation leaf area and stomatal conductance in canopy transpiration and soil hydrology. The MAPSS model accurately simulates the distributions of forests, grasslands, and deserts and reproduces observed monthly runoff. The model can be used for predictions of new vegetation distribution patterns, soil moisture, and runoff patterns in alternative climates.

The diverse vegetation types and carbon pools of the U.S. Pacific Northwest (PNW) are tightly coupled to fire regimes that depend on climate and fire suppression. To realistically assess the effects of twenty‐first‐century climate change on PNW fire and carbon dynamics, we developed a new fire suppression rule for the MC1 dynamic general vegetation model that we ran under three climate change scenarios. Climate projections from the CSIRO Mk3, MIROC 3.2 medres, and Hadley CM3 general circulation models, forced by the A2 CO2 emissions scenario, were downscaled to a 30 arc‐second (∼0.6 km2) grid. Future climates amplify the already strong seasonality of temperature and precipitation across the domain. Simulations displayed large increases in area burned (76%–310%) and burn severities (29%–41%) by the end of the twenty‐first century. The relatively dry ecosystems east of the Cascades gain carbon in the future despite projections of more intense wildfires, while the mesic maritime forests lose up to 1.2 Pg C from increased burning. Simulated fire suppression causes overall carbon gains yet leaves ecosystems vulnerable to large future fires. Overall, our simulations suggest the Pacific Northwest has the potential to sequester ∼1 Pg C over the next century unless summer droughts severely intensify fire regimes. Key Points Mesic forests may be vulnerable to future fires and emit large amounts of carbon Fire intensities will increase and suppression will become less effective Dry ecosystems display increased productivity, carbon sequestration, and fire frequencies under climate change