Predicting geographic distribution and habitat suitability due to climate change of selected threatened forest tree species in the Philippines

Garcia, Kristine L.P.; Lasco, Rodel D.; Ines, Amor Valeriano M.; Lyon, Bradfield; Pulhin, Florencia B.

doi:10.1016/j.apgeog.2013.07.005

Cited by 91 publications

(52 citation statements)

References 29 publications

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“…Maxent ecological niche model was used to assess the present distribution pattern of rubber trees in the WG and NE regions of India. The niche modelling approach has been adapted to incorporate various climate and other factors thereby evaluating the results from a habitat suitability point of view (Slater and Michael 2012;Garcia et al 2013). Here, our focus is also to find out the contribution of other factors in rubber tree distribution in both the WG and NE regions.…”

Section: Introductionmentioning

confidence: 99%

Predicting the distribution of rubber trees (Hevea brasiliensis) through ecological niche modelling with climate, soil, topography and socioeconomic factors

Ray

Behera

Jacob

2015

Ecological Research

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Identifying the factors that contribute to species distribution will help determine the impact of the changing climate on species’ range contraction and expansion. Ecological niche modelling is used to analyze the present and potential future distribution of rubber trees (Hevea brasiliensis) in two biogeographically distinct regions of India i.e., the Western Ghats (WG) and Northeast (NE). The rubber tree is an economically important plantation species, and therefore factors other than climate may play a significant role in determining its occurrence. To assist in future planning, we used the maximum entropy model to predict plausible areas for the expansion of rubber tree plantations under a changing climate scenario. Inclusion of elevation, soil and socioeconomic factors into the model did not result in a significant increase in the model accuracy estimates over the bioclimatic model (AUC > 0.92), but their effect was pronounced in the predicted probability scoring of species occurrence. Among various factors, elevation, rooting condition, village population and agricultural labour availability contributed substantially to the model in the NE region, whereas for the WG region, climate was the most important contributing factor for rubber tree distribution. We found that more areas would be suitable for rubber tree plantation in the NE region, whereas further expansion would be limited in the WG region under the projected climate scenario for 2050.

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Section: Introductionmentioning

confidence: 99%

Predicting the distribution of rubber trees (Hevea brasiliensis) through ecological niche modelling with climate, soil, topography and socioeconomic factors

Ray

Behera

Jacob

2015

Ecological Research

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“…To predict the current potential distribution of S. mukorossi, the compiled occurrence data were randomly split into 70% for training model and 30% for validating model results. To reduce the collinearity of variables, pre-model runs were conducted using all variables, and highly crosscorrelated variables were removed following the method used by Garcia et al [41].…”

Section: Model Simulationmentioning

confidence: 99%

The Effects of Climate Change on the Development of Tree Plantations for Biodiesel Production in China

Dai

Yang

Huang

et al. 2017

Forests

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Biodiesel produced from woody oil plants is a promising form of renewable energy but a combination of tree plantations' long cultivation time and rapid climate change may put large-scale production at risk. If plantations are located in future-unsuitable places, plantations may fail or yield may be poor, then significant financial, labor, and land resources invested in planting programs will be wasted. Incorporating climate change information into the planning and management of forest-based biodiesel production therefore can increase its chances of success. However, species distribution models, the main tool used to predict the influence of future climate-species distribution modeling, often contain considerable uncertainties. In this study we evaluated how these uncertainties could affect the assessment of climate suitability of the long-term development plans for forest-based biodiesel in China by using Sapindus mukorossi Gaertn as an example. The results showed that only between 59% and 75% of the planned growing areas were projected suitable habitats for the species, depending on the set-up of simulation. Our results showed the necessity for explicitly addressing the uncertainty of species distribution modeling when using it to inform forest-based bioenergy planning. We also recommend the growing area specified in China's national development plan be modified to lower the risk associated with climate change.

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“…Species distribution models such as Maxent have been criticized for being overly simplistic, since they do not incorporate external biotic factors such as species interactions [20,27,29]. However, such bioclimate envelope models have been used to project with reasonable accuracy whether species ranges will increase or decrease under a changing climate [19,[30][31][32], which was the primary objective of this study.…”

Section: Introductionmentioning

confidence: 99%

“…Bioclimate envelope models work by identifying the climatic bounds within which a species currently occurs, and then delineating how those climatic bounds will shift under various future climate projections [20][21][22][23] Most often, researchers are limited to presence-only occurrence data, requiring the use of indirect methods to infer a species' climatic requirements [8,[24][25]. One of the best performing models using presence-only data is maximum entropy modeling, or Maxent [26], which performs well even with low sample sizes typical of rare species [19,[27][28]. Maxent works by comparing climate data from occurrence sites with those from a random sample of sites from the larger landscape to minimize the relative entropy of statistical models' fit to each data set.…”

Section: Introductionmentioning

confidence: 99%

“…Such range shifts have been documented in a number of taxa [5][6][7], including alpine plants [8], marine invertebrates [9], marine fishes [10], mosquitoes [11], birds [12,13], and butterflies [1,[14][15][16][17][18]. A number of species distribution models have been developed to predict the impacts of climate change on species distributions, including bioclimate envelope models, which are useful first estimates of the potential effects of climate change on altering species' ranges [19]. Bioclimate envelope models work by identifying the climatic bounds within which a species currently occurs, and then delineating how those climatic bounds will shift under various future climate projections [20][21][22][23] Most often, researchers are limited to presence-only occurrence data, requiring the use of indirect methods to infer a species' climatic requirements [8,[24][25].…”

Section: Introductionmentioning

confidence: 99%

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Changes in the Geographic Distribution of the Diana Fritillary (<em>Speyeria diana</em>: Nymphalidae) Under Forecasted Predictions of Climate Change

Wells

Tonkyn

2018

Preprint

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Climate change is predicted to alter the geographic distribution of a wide variety of taxa, including butterfly species. Research has focused primarily on high latitude species in North America, with no known studies examining responses of taxa in the southeastern US. The Diana fritillary (Speyeria diana) has experienced a recent range retraction in that region, disappearing from lowland sites and now persisting in two, phylogenetically disjunct mountainous regions. These findings are consistent with the predicted effects of a warming climate on numerous taxa, including other butterfly species in North America and Europe. We used ecological niche modeling to predict future changes to the distribution of S. diana under several climate models. To evaluate how climate change might influence the geographic distribution of this butterfly, we developed ecological niche models using Maxent. We used two global circulation models, CCSM and MIROC, under low and high emissions scenarios to predict the future distribution of S. diana. Models were evaluated using the Receiver Operating Characteristics Area Under Curve test and the True Skill Statistics (mean AUC = 0.91± 0.0028 SE, TSS = 0.87 ± 0.0032 SE for RCP = 4.5, and mean AUC = 0.87± 0.0031SE, TSS = 0.84 ± 0.0032 SE for RCP = 8.5), which both indicate that the models we produced were significantly better than random (0.5). The four modeled climate scenarios resulted in an average loss of 91% of suitable habitat for S. diana by 2050. Populations in the Southern Appalachian Mountains were predicted to suffer the most severe fragmentation and reduction in suitable habitat, threatening an important source of genetic diversity for the species. The geographic and genetic isolation of populations in the west suggest that those populations are equally as vulnerable to decline in the future, warranting ongoing conservation of those populations as well. Our results suggest that the Diana fritillary is under threat of decline by 2050 across its entire distribution from climate change, and is likely to be negatively affected by other human-induced factors as well.

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Predicting geographic distribution and habitat suitability due to climate change of selected threatened forest tree species in the Philippines

Cited by 91 publications

References 29 publications

Predicting the distribution of rubber trees (Hevea brasiliensis) through ecological niche modelling with climate, soil, topography and socioeconomic factors

Predicting the distribution of rubber trees (Hevea brasiliensis) through ecological niche modelling with climate, soil, topography and socioeconomic factors

The Effects of Climate Change on the Development of Tree Plantations for Biodiesel Production in China

Changes in the Geographic Distribution of the Diana Fritillary (<em>Speyeria diana</em>: Nymphalidae) Under Forecasted Predictions of Climate Change

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