scholarly journals Predicting the Habitat Suitability of Melaleuca cajuputi Based on the MaxEnt Species Distribution Model

Forests ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 1449
Author(s):  
Nor Zafirah Ab Ab Lah ◽  
Zulkifli Yusop ◽  
Mazlan Hashim ◽  
Jamilah Mohd Mohd Salim ◽  
Shinya Numata
Keyword(s):  
Species Distribution ◽  
Habitat Suitability ◽  
Local Economy ◽  
Suitable Habitat ◽  
Climate Change Scenarios ◽  
Important Species ◽  
Habitat Area ◽  
Potential Habitat ◽  
Melaleuca Cajuputi ◽  
The Future

Gelam tree or Melaleuca cajuputi (M. cajuputi) is an important species for the local economy as well as coastal ecosystem protection in Terengganu, Malaysia. This study aimed at producing a current habitat suitability map and predicting future potential habitat distribution for M. cajuputi in Terengganu based on Species distribution modeling (SDM) using the Maximum Entropy principle. Our modeling results show that for the current potential distribution of M. cajuputi species, only 10.82% (1346.5 km2) of Terengganu area is suitable habitat, which 0.96% of the areas are under high, 2.44% moderate and 7.42% poor habitat suitability. The model prediction for future projection shows that the habitat suitability for M. cajuputi would decrease significantly in the year 2050 under RCP 4.5 where the largest contraction from suitable to unsuitable habitat area is about 442.1 km2 and under RCP 2.6 is the highest expansion from unsuitable to suitable habitat area (267.5 km2). From the future habitat suitability projection, we found that the habitat suitability in Marang would degrade significantly under all climate scenarios, while in Setiu the habitat suitability for M. cajuputi remains stable throughout the climate change scenarios. The modeling prediction shows a significant influence on the soil properties, temperature, and precipitation during monsoon months. These results could benefit conservationist and policymakers for decision making. The present model could also give a perception into potential habitat suitability of M. cajuputi in the future and to improve our understanding of the species’ response under the changing climate.

scholarly journals Climate Change Can Drive a Significant Loss of Suitable Habitat for Polylepis quadrijuga, a Treeline Species in the Sky Islands of the Northern Andes

2021 ◽  
Vol 9 ◽  
Author(s):  
Lina Caballero-Villalobos ◽  
Francisco Fajardo-Gutiérrez ◽  
Mariasole Calbi ◽  
Gustavo A. Silva-Arias
Keyword(s):  
Climate Change ◽  
Species Distribution ◽  
Ex Situ ◽  
Future Climate Change ◽  
Suitable Habitat ◽  
Climate Change Scenarios ◽  
Sky Islands ◽  
Future Projections ◽  
Wide Range ◽  
The Future

It is predicted that climate change will strongly affect plant distributions in high elevation “sky islands” of tropical Andes. Polylepis forests are a dominant element of the treeline throughout the Andes Cordillera in South America. However, little is known about the climatic factors underlying the current distribution of Polylepis trees and the possible effect of global climate change. The species Polylepis quadrijuga is endemic to the Colombian Eastern Cordillera, where it plays a fundamental ecological role in high-altitude páramo-forest ecotones. We sought to evaluate the potential distribution of P. quadrijuga under future climate change scenarios using ensemble modeling approaches. We conducted a comprehensive assessment of future climatic projections deriving from 12 different general circulation models (GCMs), four Representative Concentration Pathways (R) emissions scenarios, and two different time frames (2041–2060 and 2061–2080). Additionally, based on the future projections, we evaluate the effectiveness of the National System of Protected Natural Areas of Colombia (SINAP) and Páramo Complexes of Colombia (PCC) in protecting P. quadrijuga woodlands. Here, we compiled a comprehensive set of observations of P. quadrijuga and study them in connection with climatic and topographic variables to identify environmental predictors of the species distribution, possible habitat differentiation throughout the geographic distribution of the species, and predict the effect of different climate change scenarios on the future distribution of P. quadrijuga. Our results predict a dramatic loss of suitable habitat due to climate change on this key tropical Andean treeline species. The ensemble Habitat Suitability Modeling (HSM) shows differences in suitable scores among north and south regions of the species distribution consistent with differences in topographic features throughout the available habitat of P. quadrijuga. Future projections of the HSM predicted the Páramo complex “Sumapaz-Cruz Verde” as a major area for the long-term conservation of P. quadrijuga because it provides a wide range of suitable habitats for the different evaluated climate change scenarios. We provide the first set of priority areas to perform both in situ and ex situ conservation efforts based on suitable habitat projections.

scholarly journals Potential suitable habitat of Eleusine coracana (L) Gaertn (Finger millet) under the climate change scenarios in Nepal

2020 ◽  
Author(s):  
Dol Raj Luitel ◽  
Mohan Siwakoti ◽  
Mohan D. Joshi ◽  
Muniappan Rangaswami ◽  
Pramod K. Jha
Keyword(s):  
Climate Change ◽  
Habitat Suitability ◽  
Finger Millet ◽  
Suitable Habitat ◽  
Climate Change Scenarios ◽  
Policy Framing ◽  
Maxent Model ◽  
Predictive Variables ◽  
Key Words Climate Change ◽  
The Future

Abstract Abstract Background: Finger millet is the fourth major crop in Nepal and is cultivated in a traditional integrated subsistence system. Timely rain and appropriate temperature predominately affects crop distribution and yield. Climate change is evident in Nepal and it is imperative to understand how it affects habitat suitability of finger millet. Main objective of this study was to map the current suitable habitat and predicting the potential changes in the future under different climate scenarios in Nepal. Habitat mapping is important for maximizing production and minimizing the loss of local landraces. Results: Maxent model was used in this study to quantify the current suitable habitat and changes in the future habitat suitability of finger millet, based on representative concentration pathways (RCP)(RCP 2.6, 4.5, 6.0 and 8.5) in two different time periods (2050 and 2070AD) using climatic predictive variables and species localities. The model shows that 39.7% (58512.71km2) area of Nepal is highly suitable for finger millet, with cultivation mostly between 96-2300m above sea level. Eastern and central parts of Nepal have more suitable areas than western parts. Our research clearly shows that the future climatic suitable area of finger millet would shrink by 4.3 to 8.9% in 2050 and 8.9-10.5% under different RCPs by 2070. Conclusion: Finger millet is mostly cultivated in mid-hill terraces. The substantial increase in temperature due to climate change may be one reason for decrease in habitat suitability of finger millet. This situation would further threat loss of local landraces of finger millet in the future. The findings can help in planning and policy framing for climate resilient smart agriculture practice. Key words: Climate change, finger millet, habitat suitability, Maxent model

scholarly journals Potential suitable habitat of Eleusine coracana (L) Gaertn (Finger millet) under the climate change scenarios in Nepal

2019 ◽  
Author(s):  
Dol Raj Luitel ◽  
Mohan Siwakoti ◽  
Mohan D. Joshi ◽  
Muniappan Rangaswami ◽  
Pramod K. Jha
Keyword(s):  
Climate Change ◽  
Habitat Suitability ◽  
Finger Millet ◽  
Suitable Habitat ◽  
Climate Change Scenarios ◽  
Policy Framing ◽  
Maxent Model ◽  
Predictive Variables ◽  
Key Words Climate Change ◽  
The Future

Abstract Background: Finger millet is the fourth major crop in Nepal and is cultivated in a traditional integrated subsistence system. Timely rain and appropriate temperature predominately affects crop distribution and yield. Climate change is evident in Nepal and it is imperative to understand how it affects habitat suitability of finger millet. Mapping the current suitable habitat and predicting the potential changes in the future is important for maximizing production and minimizing the loss of local landraces. Results: Maxent model was used in this study to quantify the current suitable habitat and changes in the future habitat suitability of finger millet under different climate scenarios, based on representative concentration pathways (RCP)(RCP 2.6, 4.5, 6.0 and 8.5) in two different time periods (2050 and 2070AD) using climatic predictive variables and species localities. The model shows that 39.7% (58512.71km 2 ) area of Nepal is highly suitable for finger millet, with cultivation mostly between 96-2300m above sea level. Eastern and central parts of Nepal have more suitable areas than western parts. Our research clearly shows that the future climatic suitable area of finger millet would shrink by 4.3 to 8.9% in 2050 and 8.9-10.5%under different RCPs by 2070. Conclusion: Finger millet is mostly cultivated in mid-hill terraces. The substantial increase in temperature due to climate change may be one reason for decrease in habitat suitability of finger millet. This situation would further threat loss of local landraces of finger millet in the future. The findings can help in planning and policy framing for climate resilient smart agriculture practice. Key words : Climate change, finger millet, habitat suitability, Maxent model

scholarly journals Modelling Distributions of Rove Beetles in Mountainous Areas Using Remote Sensing Data

2019 ◽  
Vol 12 (1) ◽  
pp. 80 ◽  
Author(s):  
Andreas Dittrich ◽  
Stephanie Roilo ◽  
Ruth Sonnenschein ◽  
Cristiana Cerrato ◽  
Michael Ewald ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Species Distribution ◽  
Monitoring Program ◽  
Predictor Variable ◽  
Species Distributions ◽  
Additive Models ◽  
Suitable Habitat ◽  
Operating Characteristics ◽  
Important Species ◽  
Rove Beetles

Mountain ecosystems are biodiversity hotspots that are increasingly threatened by climate and land use/land cover changes. Long-term biodiversity monitoring programs provide unique insights into resulting adverse impacts on plant and animal species distribution. Species distribution models (SDMs) in combination with satellite remote sensing (SRS) data offer the opportunity to analyze shifts of species distributions in response to these changes in a spatially explicit way. Here, we predicted the presence probability of three different rove beetles in a mountainous protected area (Gran Paradiso National Park, GPNP) using environmental variables derived from Landsat and Aster Global Digital Elevation Model data and an ensemble modelling approach based on five different model algorithms (maximum entropy, random forest, generalized boosting models, generalized additive models, and generalized linear models). The objectives of the study were (1) to evaluate the potential of SRS data for predicting the presence of species dependent on local-scale environmental parameters at two different time periods, (2) to analyze shifts in species distributions between the years, and (3) to identify the most important species-specific SRS predictor variables. All ensemble models showed area under curve (AUC) of the receiver operating characteristics values above 0.7 and true skills statistics (TSS) values above 0.4, highlighting the great potential of SRS data. While only a small proportion of the total area was predicted as highly suitable for each species, our results suggest an increase of suitable habitat over time for the species Platydracus stercorarius and Ocypus ophthalmicus, and an opposite trend for Dinothenarus fossor. Vegetation cover was the most important predictor variable in the majority of the SDMs across all three study species. To better account for intra- and inter-annual variability of population dynamics as well as environmental conditions, a continuation of the monitoring program in GPNP as well as the employment of SRS with higher spatial and temporal resolution is recommended.

Modeling Abiotic Niches of Crops and Wild Ancestors Using Deep Learning: A Generalized Approach

2019 ◽  
Author(s):  
W. G. Hulleman ◽  
R. A. Vos
Keyword(s):  
Deep Learning ◽  
Species Distribution ◽  
Habitat Suitability ◽  
Species Interactions ◽  
Method Development ◽  
Species Distribution Modeling ◽  
Crop Species ◽  
Data Set ◽  
Important Species ◽  
Distribution Modeling

AbstractIntroductionUnderstanding what interactions and environmental factors shape the geographic distribution of species is one of the fundamental questions in ecology and evolution. Insofar as the focus is on agriculturally important species, insight into this is also of applied importance. Species Distribution Modeling (SDM) comprises a spectrum of approaches for establishing correlative models of species (co-)occurrences and geospatial patterns of abiotic environmental variables.MethodsHere, we contribute to this field by presenting a generalized approach for SDM that utilizes deep learning, which offers some improvements over current methods, and by presenting a case study on the habitat suitability of staple crops and their wild ancestors. The approach we present is implemented in a reusable software toolkit, which we apply to an extensive data set of geo-referenced occurrence records for 52 species and 59 GIS layers. We compare the habitat suitability projections for selected, major crop species with the actual extent of their current cultivation.ResultsOur results show that the approach yields especially plausible projections for species with large numbers of occurrences (>500). For the analysis of such data sets, the toolkit provides a convenient interface for using deep neural networks in SDM, a relatively novel application of deep learning. The toolkit, the data, and the results are available as open source / open access packages.ConclusionsSpecies Distribution Modeling with deep learning is a promising avenue for method development. The niche projections that can be produced are plausible, and the general approach provides great flexibility for incorporating additional data such as species interactions.

scholarly journals The benefits of using topographic features to predict climate-resilient habitat for migratory forest landbirds: An example for the Rusty Blackbird, Olive-sided Flycatcher, and Canada Warbler

The Condor ◽  
2020 ◽  
Vol 122 (1) ◽  
Author(s):  
Shannon Bale ◽  
Karen F Beazley ◽  
Alana Westwood ◽  
Peter Bush
Keyword(s):  
Nova Scotia ◽  
Species Distribution ◽  
Habitat Suitability ◽  
Strong Association ◽  
Breeding Habitat ◽  
Important Predictor ◽  
Suitable Habitat ◽  
Topographic Features ◽  
Precipitation Regimes ◽  
Rusty Blackbird

Abstract Maintaining a functionally connected network of high-quality habitat is one of the most effective responses to biodiversity loss. However, the spatial distribution of suitable habitat may shift over time in response to climate change. Taxa such as migratory forest landbirds are already undergoing climate-driven range shifts. Therefore, patches of climate-resilient habitat (also known as “climate refugia”) are especially valuable from a conservation perspective. Here, we performed maximum entropy (Maxent) species distribution modeling to predict suitable and potentially climate-resilient habitat in Nova Scotia, Canada, for 3 migratory forest landbirds: Rusty Blackbird (Euphagus carolinus), Olive-sided Flycatcher (Contopus cooperi), and Canada Warbler (Cardellina canadensis). We used a reverse stepwise elimination technique to identify covariates that influence habitat suitability for the target species at broad scales, including abiotic (topographic control of moisture and nutrient accumulation) and biotic (forest characteristics) covariates. As topography should be relatively unaffected by a changing climate and helps regulate the structure and composition of forest habitat, we posit that the inclusion of appropriate topographic features may support the identification of climate-resilient habitat. Of all covariates, depth to water table was the most important predictor of relative habitat suitability for the Rusty Blackbird and Canada Warbler, with both species showing a strong association with wet areas. Mean canopy height was the most important predictor for the Olive-sided Flycatcher, whereby the species was associated with taller trees. Our models, which comprise the finest-scale species distribution models available for these species in this region, further indicated that, for all species, habitat (1) remains relatively abundant and well distributed in Nova Scotia and (2) is often located in wet lowlands (a climate-resilient topographic landform). These findings suggest that opportunities remain to conserve breeding habitat for these species despite changing temperature and precipitation regimes.

scholarly journals Predicting the Bioclimatic Habitat Suitability of Ginkgo biloba L. in China with Field-Test Validations

Forests ◽  
2019 ◽  
Vol 10 (8) ◽  
pp. 705 ◽  
Author(s):  
Ying Guo ◽  
Jing Guo ◽  
Xin Shen ◽  
Guibin Wang ◽  
Tongli Wang
Keyword(s):  
Climate Change ◽  
Field Test ◽  
Ginkgo Biloba ◽  
Habitat Suitability ◽  
Leaf Traits ◽  
Suitable Habitat ◽  
Climate Change Scenarios ◽  
Living Fossil ◽  
Model Predictions ◽  
The Impact

Ginkgo (Ginkgo biloba L.) is not only considered a ‘living fossil’, but also has important ecological, economic, and medicinal values. However, the impact of climate change on the performance and distribution of this plant is an increasing concern. In this study, we developed a bioclimatic model based on data about the occurrence of ginkgo from 277 locations, and validated model predictions using a wide-ranging field test (12 test sites, located at the areas from 22.49° N to 39.32° N, and 81.11° E to 123.53° E). We found that the degree-days below zero were the most important climate variable determining ginkgo distribution. Based on the model predictions, we classified the habitat suitability for ginkgo into four categories (high, medium, low, and unsuitable), accounting for 9.29%, 6.09%, 8.46%, and 76.16% of China’s land area, respectively. The ANOVA results of the validation test showed significant differences in observed leaf-traits among the four habitat types (p < 0.05), and importantly the rankings of the leaf traits were consistent with our classification of the habitat suitability, suggesting the effectiveness of our classification in terms of biological and economic significance. In addition, we projected that suitable (high and medium) habitats for ginkgo would shrink and shift northward under both the RCP4.5 and RCP8.5 climate change scenarios for three future periods (the 2020s, 2050s, and 2080s). However, the area of low-suitable habitat would increase, resulting in a slight decrease in unsuitable habitats. Our findings contribute to a better understanding of climate change impact on this plant and provide a scientific basis for developing adaptive strategies for future climate.

scholarly journals Estimating potential range shift of some wild bees in response to climate change scenarios in northwestern regions of Iran

2021 ◽  
Vol 45 (1) ◽  
Author(s):  
Ehsan Rahimi ◽  
Shahindokht Barghjelveh ◽  
Pinliang Dong
Keyword(s):  
Climate Change ◽  
Habitat Quality ◽  
Species Distribution ◽  
Range Shift ◽  
Potential Range ◽  
Climate Change Scenarios ◽  
Natural Ecosystem ◽  
Quality Changes ◽  
Wild Bees ◽  
The Future

Abstract Background Climate change is occurring rapidly around the world, and is predicted to have a large impact on biodiversity. Various studies have shown that climate change can alter the geographical distribution of wild bees. As climate change affects the species distribution and causes range shift, the degree of range shift and the quality of the habitats are becoming more important for securing the species diversity. In addition, those pollinator insects are contributing not only to shaping the natural ecosystem but also to increased crop production. The distributional and habitat quality changes of wild bees are of utmost importance in the climate change era. This study aims to investigate the impact of climate change on distributional and habitat quality changes of five wild bees in northwestern regions of Iran under two representative concentration pathway scenarios (RCP 4.5 and RCP 8.5). We used species distribution models to predict the potential range shift of these species in the year 2070. Result The effects of climate change on different species are different, and the increase in temperature mainly expands the distribution ranges of wild bees, except for one species that is estimated to have a reduced potential range. Therefore, the increase in temperature would force wild bees to shift to higher latitudes. There was also significant uncertainty in the use of different models and the number of environmental layers employed in the modeling of habitat suitability. Conclusion The increase in temperature caused the expansion of species distribution and wider areas would be available to the studied species in the future. However, not all of this possible range may include high-quality habitats, and wild bees may limit their niche to suitable habitats. On the other hand, the movement of species to higher latitudes will cause a mismatch between farms and suitable areas for wild bees, and as a result, farmers will face a shortage of pollination from wild bees. We suggest that farmers in these areas be aware of the effects of climate change on agricultural production and consider the use of managed bees in the future.

Identifying Potential Habitat for the Endangered Aleutian Shield Fern Using Topographical Characteristics

2012 ◽  
Vol 3 (2) ◽  
pp. 303-310
Author(s):  
Adam Duarte ◽  
Daniel M. Wolcott ◽  
T. Edwin Chow ◽  
Mark A. Ricca
Keyword(s):  
Habitat Suitability ◽  
Habitat Characteristics ◽  
Geographical Information ◽  
Slope Aspect ◽  
Suitable Habitat ◽  
Gis Model ◽  
Potential Habitat ◽  
Suitability Map ◽  
Habitat Suitability Map ◽  
The U.S

Abstract The Aleutian shield fern Polystichum aleuticum is endemic to the Aleutian archipelago of Alaska and is listed as endangered pursuant to the U.S. Endangered Species Act. Despite numerous efforts to discover new populations of this species, only four known populations are documented to date, and information is needed to prioritize locations for future surveys. Therefore, we incorporated topographical habitat characteristics (elevation, slope, aspect, distance from coastline, and anthropogenic footprint) found at known Aleutian shield fern locations into a Geographical Information System (GIS) model to create a habitat suitability map for the entirety of the Andreaonof Islands. A total of 18 islands contained 489.26 km2 of highly suitable and moderately suitable habitat when weighting each factor equally. This study reports a habitat suitability map for the endangered Aleutian shield fern using topographical characteristics, which can be used to assist current and future recovery efforts for the species.

scholarly journals Modeling Distribution and Habitat Suitability for the Snow Leopard in Bhutan

2021 ◽  
Vol 2 ◽  
Author(s):  
Dechen Lham ◽  
Gabriele Cozzi ◽  
Stefan Sommer ◽  
Phuntsho Thinley ◽  
Namgay Wangchuk ◽  
...  
Keyword(s):  
Protected Areas ◽  
Species Distribution ◽  
Habitat Suitability ◽  
Anthropogenic Factors ◽  
Suitable Habitat ◽  
Snow Leopard ◽  
Potential Contribution ◽  
Ensemble Model ◽  
Model Framework ◽  
Biological Corridors

The snow leopard (Panthera uncia) is one of the world's most elusive felids. In Bhutan, which is one of the 12 countries where the species still persists, reliable information on its distribution and habitat suitability is lacking, thus impeding effective conservation planning for the species. To fill this knowledge gap, we created a country-wide species distribution model using “presence-only” data from 420 snow leopard occurrences (345 from a sign survey and 77 from a camera-trapping survey) and 12 environmental covariates consisting of biophysical and anthropogenic factors. We analyzed the data in an ensemble model framework which combines the outputs from several species distribution models. To assess the adequacy of Bhutan's network of protected areas and their potential contribution toward the conservation of the species, we overlaid the output of the ensemble model on the spatial layers of protected areas and biological corridors. The ensemble model identified 7,206 km2 of Bhutan as suitable for the snow leopard: 3,647 km2 as highly suitable, 2,681 km2 as moderately suitable, and 878 km2 as marginally suitable. Forty percent of the total suitable habitat consisted of protected areas and a further 8% of biological corridors. These suitable habitats were characterized by a mean livestock density of 1.3 individuals per hectare, and a mean slope of 25°; they closely match the distribution of the snow leopard's main wild prey, the bharal (Pseudois nayaur). Our study shows that Bhutan's northern protected areas are a centre for snow leopard conservation both at the national and regional scale.

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