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      Climate change and fire effects on a prairie–woodland ecotone: projecting species range shifts with a dynamic global vegetation model

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          Abstract

          Large shifts in species ranges have been predicted under future climate scenarios based primarily on niche-based species distribution models. However, the mechanisms that would cause such shifts are uncertain. Natural and anthropogenic fires have shaped the distributions of many plant species, but their effects have seldom been included in future projections of species ranges. Here, we examine how the combination of climate and fire influence historical and future distributions of the ponderosa pine–prairie ecotone at the edge of the Black Hills in South Dakota, USA, as simulated by MC1, a dynamic global vegetation model that includes the effects of fire, climate, and atmospheric CO 2 concentration on vegetation dynamics. For this purpose, we parameterized MC1 for ponderosa pine in the Black Hills, designating the revised model as MC1-WCNP. Results show that fire frequency, as affected by humidity and temperature, is central to the simulation of historical prairies in the warmer lowlands versus woodlands in the cooler, moister highlands. Based on three downscaled general circulation model climate projections for the 21st century, we simulate greater frequencies of natural fire throughout the area due to substantial warming and, for two of the climate projections, lower relative humidity. However, established ponderosa pine forests are relatively fire resistant, and areas that were initially wooded remained so over the 21st century for most of our future climate x fire management scenarios. This result contrasts with projections for ponderosa pine based on climatic niches, which suggest that its suitable habitat in the Black Hills will be greatly diminished by the middle of the 21st century. We hypothesize that the differences between the future predictions from these two approaches are due in part to the inclusion of fire effects in MC1, and we highlight the importance of accounting for fire as managed by humans in assessing both historical species distributions and future climate change effects.

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          Rapid shifts in plant distribution with recent climate change.

          A change in climate would be expected to shift plant distribution as species expand in newly favorable areas and decline in increasingly hostile locations. We compared surveys of plant cover that were made in 1977 and 2006-2007 along a 2,314-m elevation gradient in Southern California's Santa Rosa Mountains. Southern California's climate warmed at the surface, the precipitation variability increased, and the amount of snow decreased during the 30-year period preceding the second survey. We found that the average elevation of the dominant plant species rose by approximately 65 m between the surveys. This shift cannot be attributed to changes in air pollution or fire frequency and appears to be a consequence of changes in regional climate.
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            Niches, models, and climate change: assessing the assumptions and uncertainties.

            As the rate and magnitude of climate change accelerate, understanding the consequences becomes increasingly important. Species distribution models (SDMs) based on current ecological niche constraints are used to project future species distributions. These models contain assumptions that add to the uncertainty in model projections stemming from the structure of the models, the algorithms used to translate niche associations into distributional probabilities, the quality and quantity of data, and mismatches between the scales of modeling and data. We illustrate the application of SDMs using two climate models and two distributional algorithms, together with information on distributional shifts in vegetation types, to project fine-scale future distributions of 60 California landbird species. Most species are projected to decrease in distribution by 2070. Changes in total species richness vary over the state, with large losses of species in some "hotspots" of vulnerability. Differences in distributional shifts among species will change species co-occurrences, creating spatial variation in similarities between current and future assemblages. We use these analyses to consider how assumptions can be addressed and uncertainties reduced. SDMs can provide a useful way to incorporate future conditions into conservation and management practices and decisions, but the uncertainties of model projections must be balanced with the risks of taking the wrong actions or the costs of inaction. Doing this will require that the sources and magnitudes of uncertainty are documented, and that conservationists and resource managers be willing to act despite the uncertainties. The alternative, of ignoring the future, is not an option.
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              CO2 enhancement of forest productivity constrained by limited nitrogen availability.

              Stimulation of terrestrial plant production by rising CO(2) concentration is projected to reduce the airborne fraction of anthropogenic CO(2) emissions. Coupled climate-carbon cycle models are sensitive to this negative feedback on atmospheric CO(2), but model projections are uncertain because of the expectation that feedbacks through the nitrogen (N) cycle will reduce this so-called CO(2) fertilization effect. We assessed whether N limitation caused a reduced stimulation of net primary productivity (NPP) by elevated atmospheric CO(2) concentration over 11 y in a free-air CO(2) enrichment (FACE) experiment in a deciduous Liquidambar styraciflua (sweetgum) forest stand in Tennessee. During the first 6 y of the experiment, NPP was significantly enhanced in forest plots exposed to 550 ppm CO(2) compared with NPP in plots in current ambient CO(2), and this was a consistent and sustained response. However, the enhancement of NPP under elevated CO(2) declined from 24% in 2001-2003 to 9% in 2008. Global analyses that assume a sustained CO(2) fertilization effect are no longer supported by this FACE experiment. N budget analysis supports the premise that N availability was limiting to tree growth and declining over time--an expected consequence of stand development, which was exacerbated by elevated CO(2). Leaf- and stand-level observations provide mechanistic evidence that declining N availability constrained the tree response to elevated CO(2); these observations are consistent with stand-level model projections. This FACE experiment provides strong rationale and process understanding for incorporating N limitation and N feedback effects in ecosystem and global models used in climate change assessments.
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                Author and article information

                Journal
                Ecol Evol
                Ecol Evol
                ece3
                Ecology and Evolution
                Blackwell Publishing Ltd
                2045-7758
                2045-7758
                December 2013
                18 November 2013
                : 3
                : 15
                : 5076-5097
                Affiliations
                [1 ]Biological and Ecological Engineering, Oregon State University Corvallis, Oregon, USA
                [2 ]Conservation Biology Institute Corvallis, Oregon, USA
                [3 ]US Geological Survey Hot Springs, South Dakota, USA
                Author notes
                David A. King, Biological and Ecological Engineering, Oregon State University, Corvallis, OR 97331 USA. Fax: +1 541 752 0518; E-mail: David.A.King@ 123456oregonstate.edu

                Funding Information Research funded by the National Park Service Climate Change Response Program and by the United States Geological Survey's North Central Climate Science Center.

                Article
                10.1002/ece3.877
                3892370
                9637603f-0f1a-4508-b4f5-c9f478a4762c
                © 2013 Published by John Wiley & Sons Ltd.

                Re-use of this article is permitted in accordance with the Creative Commons Deed, Attribution 2.5, which does not permit commercial exploitation.

                History
                : 11 September 2013
                : 08 October 2013
                : 15 October 2013
                Categories
                Original Research

                Evolutionary Biology
                dgvm,mc1,drought,fire,niche-based species distribution models,pinus ponderosa
                Evolutionary Biology
                dgvm, mc1, drought, fire, niche-based species distribution models, pinus ponderosa

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