Refining predictions of climate change impacts on plant species distribution through the use of local statistics

2008 ◽  
Vol 3 (3) ◽  
pp. 228-236 ◽  
Author(s):  
G.M. Foody
Plant Ecology ◽  
2008 ◽  
Vol 200 (1) ◽  
pp. 91-104 ◽  
Author(s):  
Christian Schöb ◽  
Peter M. Kammer ◽  
Philippe Choler ◽  
Heinz Veit

2015 ◽  
Vol 191 ◽  
pp. 322-330 ◽  
Author(s):  
Craig M. Costion ◽  
Lalita Simpson ◽  
Petina L. Pert ◽  
Monica M. Carlsen ◽  
W. John Kress ◽  
...  

2008 ◽  
Vol 4 (5) ◽  
pp. 573-576 ◽  
Author(s):  
Xavier Morin ◽  
Martin J Lechowicz

Pioneering efforts to predict shifts in species distribution under climate change used simple models based on the correlation between contemporary environmental factors and distributions. These models make predictions at coarse spatial scales and assume the constancy of present correlations between environment and distribution. Adaptive management of climate change impacts requires models that can make more robust predictions at finer spatio-temporal scales by accounting for processes that actually affect species distribution on heterogeneous landscapes. Mechanistic models of the distribution of both species and vegetation types have begun to emerge to meet these needs. We review these developments and highlight how recent advances in our understanding of relationships among the niche concept, species diversity and community assembly point the way towards more effective models for the impacts of global change on species distribution and community diversity.


2014 ◽  
Author(s):  
Kendra Garner ◽  
Michelle Chang ◽  
Matthew Fulda ◽  
Jon Berlin ◽  
Rachel Freed ◽  
...  

Local increases in sea level caused by global climate change pose a significant threat to the persistence of many coastal plant species through exacerbating inundation, flooding, and erosion. In addition to sea level rise (SLR), climate changes in the form of air temperature and precipitation regimes will also alter habitats of coastal plant species. Although numerous studies have analyzed the effect of climate change on future habitats through species distribution models (SDMs), none have incorporated the threat of exposure to SLR. We developed a model that quantified the effect of both SLR and climate change on habitat for 88 rare coastal plant species in San Luis Obispo, Santa Barbara, and Ventura Counties, California, USA. Our SLR model projects that by the year 2100, 60 of the 88 species will be threatened by SLR. We found that the probability of being threatened by SLR strongly correlates with a species’ area, elevation, and distance from the coast, and that ten species could lose their entire current habitat in the study region. We modeled the habitat suitability of these 10 species under future climate using a species distribution model (SDM). Our SDM projects that 4 of the 10 species will lose all suitable current habitats in the region as a result of climate change. While SLR accounts for up to 9.2 km2 loss in habitat, climate change accounts for habitat suitability changes ranging from a loss of 1439 km2 for one species to a gain of 9795 km2 for another species. For three species, SLR is projected to reduce future suitable area by as much as 28% of total area. This suggests that while SLR poses a higher risk, climate changes in precipitation and air temperature represents a lesser known but potentially larger risk and a small cumulative effect from both.


2014 ◽  
Author(s):  
Kendra Garner ◽  
Michelle Chang ◽  
Matthew Fulda ◽  
Jon Berlin ◽  
Rachel Freed ◽  
...  

Local increases in sea level caused by global climate change pose a significant threat to the persistence of many coastal plant species through exacerbating inundation, flooding, and erosion. In addition to sea level rise (SLR), climate changes in the form of air temperature and precipitation regimes will also alter habitats of coastal plant species. Although numerous studies have analyzed the effect of climate change on future habitats through species distribution models (SDMs), none have incorporated the threat of exposure to SLR. We developed a model that quantified the effect of both SLR and climate change on habitat for 88 rare coastal plant species in San Luis Obispo, Santa Barbara, and Ventura Counties, California, USA. Our SLR model projects that by the year 2100, 60 of the 88 species will be threatened by SLR. We found that the probability of being threatened by SLR strongly correlates with a species’ area, elevation, and distance from the coast, and that ten species could lose their entire current habitat in the study region. We modeled the habitat suitability of these 10 species under future climate using a species distribution model (SDM). Our SDM projects that 4 of the 10 species will lose all suitable current habitats in the region as a result of climate change. While SLR accounts for up to 9.2 km2 loss in habitat, climate change accounts for habitat suitability changes ranging from a loss of 1439 km2 for one species to a gain of 9795 km2 for another species. For three species, SLR is projected to reduce future suitable area by as much as 28% of total area. This suggests that while SLR poses a higher risk, climate changes in precipitation and air temperature represents a lesser known but potentially larger risk and a small cumulative effect from both.


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