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A Geographic Mosaic of Climate Change Impacts on Terrestrial Vegetation: Which Areas Are Most at Risk?

Ackerly DD, Cornwell WK, Weiss SB, Flint LE, Flint AL - PLoS ONE (2015)

Bottom Line: The model was then projected for 54 future climate scenarios, spanning a representative range of temperature and precipitation projections from the CMIP3 and CMIP5 ensembles.Surprisingly, sensitivity to climate change is higher closer to the coast, on lower insolation, north-facing slopes and in areas of higher precipitation.The greater sensitivity of moist and low insolation sites is an unexpected outcome that challenges views on the location and stability of climate refugia.

View Article: PubMed Central - PubMed

Affiliation: Department of Integrative Biology, University of California, Berkeley, California, United States of America; Jepson Herbarium, University of California, Berkeley, California, United States of America.

ABSTRACT
Changes in climate projected for the 21st century are expected to trigger widespread and pervasive biotic impacts. Forecasting these changes and their implications for ecosystem services is a major research goal. Much of the research on biotic responses to climate change has focused on either projected shifts in individual species distributions or broad-scale changes in biome distributions. Here, we introduce a novel application of multinomial logistic regression as a powerful approach to model vegetation distributions and potential responses to 21st century climate change. We modeled the distribution of 22 major vegetation types, most defined by a single dominant woody species, across the San Francisco Bay Area. Predictor variables included climate and topographic variables. The novel aspect of our model is the output: a vector of relative probabilities for each vegetation type in each location within the study domain. The model was then projected for 54 future climate scenarios, spanning a representative range of temperature and precipitation projections from the CMIP3 and CMIP5 ensembles. We found that sensitivity of vegetation to climate change is highly heterogeneous across the region. Surprisingly, sensitivity to climate change is higher closer to the coast, on lower insolation, north-facing slopes and in areas of higher precipitation. While such sites may provide refugia for mesic and cool-adapted vegetation in the face of a warming climate, the model suggests they will still be highly dynamic and relatively sensitive to climate-driven vegetation transitions. The greater sensitivity of moist and low insolation sites is an unexpected outcome that challenges views on the location and stability of climate refugia. Projections provide a foundation for conservation planning and land management, and highlight the need for a greater understanding of the mechanisms and time scales of potential climate-driven vegetation transitions.

No MeSH data available.


Related in: MedlinePlus

Projected change in selected vegetation types.Changes in relative abundance of four vegetation types, plotted relative to mean annual temperature (MAT) of each of the climate scenarios. Colors indicate change in precipitation (see legend in Fig 4). See S6 Fig and S5 Table for results for all 22 vegetation types.
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pone.0130629.g005: Projected change in selected vegetation types.Changes in relative abundance of four vegetation types, plotted relative to mean annual temperature (MAT) of each of the climate scenarios. Colors indicate change in precipitation (see legend in Fig 4). See S6 Fig and S5 Table for results for all 22 vegetation types.

Mentions: Multiple regression was used to assess changes in landscape cover of each vegetation type, based on the sum of its predicted probability across all pixels, in response to average temperature (MAT) and PPT of future climate scenarios; CWD, DJF, and JJA all covary strongly with MAT, making it impractical to tease apart individual contributions. Non-linear relationships with MAT were evaluated, and if present either a quadratic or an exponential model was selected based on goodness-of-fit. All but one of the 22 vegetation types changed significantly with MAT: twelve declined, six increased, and three had hump-shaped responses with an initial increase followed by decline at higher temperatures (Fig 5, S6 FigS5 Table). Vegetation types projected to increase with temperature were generally those that occupy hot, interior portions of the study region (e.g., semi-desert scrub, chamise chaparral, blue oak woodland, interior live oak woodland, knobcone pine forest). Of the vegetation types projected to decline with temperature, four exhibited negative exponential patterns reaching values close to zero in response to about 2.5°C of warming (black oak forest/woodland, canyon live oak forest, tanoak forest, and non-maritime ponderosa pine forest). Seventeen of 22 types exhibited significant responses to precipitation, nine decreasing and eight increasing at higher rainfall (and vice versa in response to lower rainfall) (S6 Fig). It is important to remember that the multinominal logistic is a zero-sum model, so if some types increase others must decrease, placing a constraint on the range of responses across the individual vegetation types.


A Geographic Mosaic of Climate Change Impacts on Terrestrial Vegetation: Which Areas Are Most at Risk?

Ackerly DD, Cornwell WK, Weiss SB, Flint LE, Flint AL - PLoS ONE (2015)

Projected change in selected vegetation types.Changes in relative abundance of four vegetation types, plotted relative to mean annual temperature (MAT) of each of the climate scenarios. Colors indicate change in precipitation (see legend in Fig 4). See S6 Fig and S5 Table for results for all 22 vegetation types.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4482696&req=5

pone.0130629.g005: Projected change in selected vegetation types.Changes in relative abundance of four vegetation types, plotted relative to mean annual temperature (MAT) of each of the climate scenarios. Colors indicate change in precipitation (see legend in Fig 4). See S6 Fig and S5 Table for results for all 22 vegetation types.
Mentions: Multiple regression was used to assess changes in landscape cover of each vegetation type, based on the sum of its predicted probability across all pixels, in response to average temperature (MAT) and PPT of future climate scenarios; CWD, DJF, and JJA all covary strongly with MAT, making it impractical to tease apart individual contributions. Non-linear relationships with MAT were evaluated, and if present either a quadratic or an exponential model was selected based on goodness-of-fit. All but one of the 22 vegetation types changed significantly with MAT: twelve declined, six increased, and three had hump-shaped responses with an initial increase followed by decline at higher temperatures (Fig 5, S6 FigS5 Table). Vegetation types projected to increase with temperature were generally those that occupy hot, interior portions of the study region (e.g., semi-desert scrub, chamise chaparral, blue oak woodland, interior live oak woodland, knobcone pine forest). Of the vegetation types projected to decline with temperature, four exhibited negative exponential patterns reaching values close to zero in response to about 2.5°C of warming (black oak forest/woodland, canyon live oak forest, tanoak forest, and non-maritime ponderosa pine forest). Seventeen of 22 types exhibited significant responses to precipitation, nine decreasing and eight increasing at higher rainfall (and vice versa in response to lower rainfall) (S6 Fig). It is important to remember that the multinominal logistic is a zero-sum model, so if some types increase others must decrease, placing a constraint on the range of responses across the individual vegetation types.

Bottom Line: The model was then projected for 54 future climate scenarios, spanning a representative range of temperature and precipitation projections from the CMIP3 and CMIP5 ensembles.Surprisingly, sensitivity to climate change is higher closer to the coast, on lower insolation, north-facing slopes and in areas of higher precipitation.The greater sensitivity of moist and low insolation sites is an unexpected outcome that challenges views on the location and stability of climate refugia.

View Article: PubMed Central - PubMed

Affiliation: Department of Integrative Biology, University of California, Berkeley, California, United States of America; Jepson Herbarium, University of California, Berkeley, California, United States of America.

ABSTRACT
Changes in climate projected for the 21st century are expected to trigger widespread and pervasive biotic impacts. Forecasting these changes and their implications for ecosystem services is a major research goal. Much of the research on biotic responses to climate change has focused on either projected shifts in individual species distributions or broad-scale changes in biome distributions. Here, we introduce a novel application of multinomial logistic regression as a powerful approach to model vegetation distributions and potential responses to 21st century climate change. We modeled the distribution of 22 major vegetation types, most defined by a single dominant woody species, across the San Francisco Bay Area. Predictor variables included climate and topographic variables. The novel aspect of our model is the output: a vector of relative probabilities for each vegetation type in each location within the study domain. The model was then projected for 54 future climate scenarios, spanning a representative range of temperature and precipitation projections from the CMIP3 and CMIP5 ensembles. We found that sensitivity of vegetation to climate change is highly heterogeneous across the region. Surprisingly, sensitivity to climate change is higher closer to the coast, on lower insolation, north-facing slopes and in areas of higher precipitation. While such sites may provide refugia for mesic and cool-adapted vegetation in the face of a warming climate, the model suggests they will still be highly dynamic and relatively sensitive to climate-driven vegetation transitions. The greater sensitivity of moist and low insolation sites is an unexpected outcome that challenges views on the location and stability of climate refugia. Projections provide a foundation for conservation planning and land management, and highlight the need for a greater understanding of the mechanisms and time scales of potential climate-driven vegetation transitions.

No MeSH data available.


Related in: MedlinePlus