Using MaxEnt Model to Predict Suitable Habitat Changes for Key Protected Species in Koshi Basin, Central Himalayas

SummaryThe Violet-throated MetaltailMetallura baroniis a high altitude hummingbird endemic to south-central Ecuador currently considered globally ‘Endangered’. Here we present the first detailed assessment of its distribution, ecology and conservation. We first used a maximum entropy model (Maxent model) to create a predicted distribution for this species based on very limited species occurrence data. We used this model to guide field surveys for the species between April and October 2006. We found a positive relationship between model values and species presence, indicating that the model was a useful tool to predict species occurrence and guide exploration. In the sites where the metaltail was found we gathered data on its habitat requirements, food resources and behaviour. Our results indicate that Violet-throated Metaltail is restricted to the Western Cordillera of the Andes Mountains in Azuay and Cañar provinces of Ecuador, with an area of extent of less than 2,000 km2. Deep river canyons to the north and south, lack of suitable habitat, and potential interspecific competition in the east may limit the bird's distribution. The species occurred in three distinct habitats, includingPolylepiswoodland, the upper edge of the montane forest, and in shrubby paramo, but we found no difference in relative abundance among these habitats. The metaltail seems to tolerate moderate human intervention in its habitats as long as some native brushy cover is maintained. We found thatBrachyotumsp.,Berberissp., andBarnadesiasp. were important nectar resources. The ‘Endangered’ status of this species is supported due to its restricted distribution in fragmented habitats which are under increasing human pressures.

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Estimated Density, Population Size and Distribution of the Endangered Western Hoolock Gibbon (Hoolock hoolock) in Forest Remnants in Bangladesh

Diversity ◽

10.3390/d13100490 ◽

2021 ◽

Vol 13 (10) ◽

pp. 490

Author(s):

Habibon Naher ◽

Hassan Al-Razi ◽

Tanvir Ahmed ◽

Sabit Hasan ◽

Areej Jaradat ◽

...

Keyword(s):

Population Size ◽

Tropical Forests ◽

Forest Regeneration ◽

Distance Sampling ◽

Suitable Habitat ◽

Careful Evaluation ◽

Maxent Model ◽

Maxent Modeling ◽

Forest Remnants ◽

Density Population

Tropical forests are threatened worldwide due to deforestation. In South and Southeast Asia, gibbons (Hylobatidae) are important to seed dispersal and forest regeneration. Most gibbons are threatened due to deforestation. We studied the western hoolock gibbon (Hoolock hoolock) in Bangladesh to determine population size and extent of suitable habitat. We used distance sampling to estimate density across 22 sites in northeastern and southeastern Bangladesh. We used Maxent modeling to determine areas of highly suitable habitat throughout Bangladesh. Density was estimated to be 0.39 ± 0.09groups/km2, and the total estimated population was 468.96 ± 45.56 individuals in 135.31 ± 2.23 groups. The Maxent model accurately predicted gibbon distribution. Vegetation cover, isothermality, annual precipitation, elevation and mean temperature of the warmest quarter influenced distribution. Two areas in the northeast and two areas in the southeast have high potential for gibbon conservation in Bangladesh. We also found significantly more gibbons in areas that had some level of official protection. Thus, we suggest careful evaluation, comprehensive surveys and restoration of habitats identified as suitable for gibbons. We recommend bringing specific sites in the northeastern and southeastern regions under protection to secure habitat for remaining gibbon populations.

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Global distribution of soapberries (Sapindus L.) habitats under current and future climate scenarios

Scientific Reports ◽

10.1038/s41598-021-98389-8 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Jiming Liu ◽

Lianchun Wang ◽

Caowen Sun ◽

Benye Xi ◽

Doudou Li ◽

...

Keyword(s):

Large Scale ◽

Global Climate ◽

Future Climate ◽

Environmental Data ◽

Climate Projections ◽

Suitable Habitat ◽

Maxent Model ◽

Mean Temperature ◽

Suitable Habitats ◽

Large Scale Cultivation

AbstractSapindus (Sapindus L.) is a widely distributed economically important tree genus that provides biodiesel, biomedical and biochemical products. However, with climate change, deforestation, and economic development, the diversity of Sapindus germplasms may face the risk of destruction. Therefore, utilising historical environmental data and future climate projections from the BCC-CSM2-MR global climate database, we simulated the current and future global distributions of suitable habitats for Sapindus using a Maximum Entropy (MaxEnt) model. The estimated ecological thresholds for critical environmental factors were: a minimum temperature of 0–20 °C in the coldest month, soil moisture levels of 40–140 mm, a mean temperature of 2–25 °C in the driest quarter, a mean temperature of 19–28 °C in the wettest quarter, and a soil pH of 5.6–7.6. The total suitable habitat area was 6059.97 × 104 km2, which was unevenly distributed across six continents. As greenhouse gas emissions increased over time, the area of suitable habitats contracted in lower latitudes and expanded in higher latitudes. Consequently, surveys and conservation should be prioritised in southern hemisphere areas which are in danger of becoming unsuitable. In contrast, other areas in northern and central America, China, and India can be used for conservation and large-scale cultivation in the future.

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Maxent modelling for habitat suitability of vulnerable tree Dalbergia latifolia in Nepal

Silva Fennica ◽

10.14214/sf.10441 ◽

2021 ◽

Vol 55 (4) ◽

Author(s):

Dipak Mahatara ◽

Amul Acharya ◽

Bishnu Dhakal ◽

Dipesh Sharma ◽

Sunita Ulak ◽

...

Keyword(s):

Model Prediction ◽

Habitat Suitability ◽

Habitat Management ◽

Natural Habitat ◽

Area Under The Curve ◽

Forest Conversion ◽

Suitable Habitat ◽

Timber Species ◽

Jackknife Test ◽

Maxent Model

Roxb., commonly known as rosewood, is one of the highly valuable tropical timber species of Nepal. The tree species was widely distributed in the past, however, over-exploitation of natural habitat, deforestation, forest conversion for agriculture, illegal logging and the invasion of alien species resulted in the classification of this species as vulnerable by the IUCN (International Union for Conservation of Nature) category. So, the prediction of habitat suitability and potential distribution of the species is required to develop restoration mechanisms and conservation interventions. In this study, we modelled the suitable habitat of over the entire possible range of Nepal using a Maxent model. We compiled 23 environmental variables (19 bioclimatic, 3 topographic and a vegetative layer), however, only 12 least correlated variables along with 43 spatially representative presence locations were retained for model prediction. We used a receiver operating characteristic (ROC) curve to assess the modelâs performance and a Jackknife procedure to evaluate the relative importance of predictor variables. The model was statistically significant with an area under the curve (AUC) value of 0.969. The internal Jackknife test indicated that elevation was the most important variable for the model prediction with 71.3% contribution followed by mean temperature of driest quarter (9.8%). The most (>0.6) suitable habitat for the was 235â484 hectares with large sections of area in two provinces whereas, the western most provinces were not suitable for as per Maxent model. The information presented here can provide a framework for nature conservation planning, monitoring and habitat management of this rare and endangered species.Dalbergia latifoliaD. latifoliaD. latifoliaD. latifolia

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Habitat Suitability Study of Hylomecon Japonica Based on Maxent Model in China

10.21203/rs.3.rs-76168/v1 ◽

2020 ◽

Author(s):

Cao Zhen ◽

Zhang Xiaoyan ◽

Xue Xuanji ◽

Zhang Lei ◽

Zhan Guanqun ◽

...

Keyword(s):

Habitat Suitability ◽

Potential Distribution ◽

Mean Annual Temperature ◽

Suitable Habitat ◽

Entropy Model ◽

Factors Affecting ◽

Jackknife Test ◽

Maxent Model ◽

Growth Area ◽

The Mean

Abstract Background: To understand the potential distribution and habitat suitability of H. japonica in China. And to provide guidance for the wild cultivation and standardized planting of H. japonica. Methods: The maximum entropy model (Maxent) and geographic information system (ArcGIS) were applied to predict the potential suitable habitat of H. japonica species, and the contribution of variables were evaluated by using the jackknife test. Results: The AUC value confirmed the accuracy of the model prediction based on 101 occurrence records. The potential distributions of H. japonica were mainly concentrated in Jilin, Liaoning, Shaanxi and other provinces (adaptability index>0.6). Jackknife experiment showed that the precipitation of driest month (35.6%), precipitation of wettest quarter (13.4%), the mean annual temperature (7.8%) and the subclass of soil (7.8%) were the most important factors affecting the potential distribution of H. japonica. Conclusion: The niche parameters of the most suitable growth area (adaptability index>0.8) for H. japonica were precipitation of driest month (5 mm), precipitation of wettest quarter (400-490 mm), the mean annual temperature (-2-4 °C) and the subclass of soil (Glossy Chernozem, Gleyic Lime, Haplic Gypsisols).

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Predicting the Potential Distribution of Hylomecon japonica in China under Current and Future Climate Change Based on Maxent Model

Sustainability ◽

10.3390/su132011253 ◽

2021 ◽

Vol 13 (20) ◽

pp. 11253

Author(s):

Zhen Cao ◽

Lei Zhang ◽

Xinxin Zhang ◽

Zengjun Guo

Keyword(s):

Climate Change ◽

Potential Distribution ◽

Characteristic Curve ◽

Future Climate Change ◽

Mean Annual Temperature ◽

Suitable Habitat ◽

Entropy Model ◽

Factors Affecting ◽

Jackknife Test ◽

Maxent Model

Hylomecon japonica is considered a natural medicinal plant with anti-inflammatory, anticancer and antibacterial activity. The assessment of climate change impact on its habitat suitability is important for the wild cultivation and standardized planting of H. japonica. In this study, the maximum entropy model (Maxent) and geographic information system (ArcGIS) were applied to predict the current and future distribution of H. japonica species, and the contributions of variables were evaluated by using the jackknife test. The area under the receiver operating characteristic curve (AUC) value confirmed the accuracy of the model prediction based on 102 occurrence records. The predicted potential distributions of H. japonica were mainly concentrated in Jilin, Liaoning, Shaanxi, Chongqing, Henan, Heilongjiang and other provinces (adaptability index > 0.6). The jackknife experiment showed that the precipitation of driest month (40.5%), mean annual temperature (12.4%), the precipitation of wettest quarter (11.6%) and the subclass of soil (9.7%) were the most important factors affecting the potential distribution of H. japonica. In the future, only under the shared socioeconomic Pathway 245 (SSP 245) scenario model in 2061–2080, the suitable habitat area for H. japonica is expected to show a significant upward trend. The area under other scenarios may not increase or decrease significantly.

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A prediction of suitable habitat mapping of Pinus roxburghii sarg. using maxent modeling

Environment Conservation Journal ◽

10.36953/ecj.2021.22319 ◽

2021 ◽

pp. 149-153

Author(s):

Leishangthem Chanu Langlentombi ◽

Manoj Kumar

Keyword(s):

Suitable Habitat ◽

Human Beings ◽

Future Prospects ◽

Pinus Roxburghii ◽

Maxent Model ◽

Potential Habitat ◽

Study Results ◽

Good Potential ◽

Chir Pine ◽

Temperature Seasonality

Prediction of the potential geographic distribution of species is essential concerning various purposes in protection and conservation. The present study focused on predicting the distribution of Pinus roxburghii Sarg. (chir pine) in Uttarakhand Himalayas using the MaxEnt model. The model produced AUC curve with significant value of 0.882 (± 0.023). The study results showed that 426200 ha (5.91%) cover highly potential habitat area for chir pine. Whereas 833900 ha (11.56%), 1019200 ha (14.13%) and 4936000 ha (68.41%) cover good potential, moderately potential and least potential habitat areas, respectively. Based on the jacknife test, it was observed that temperature seasonality (bio4), precipitation of seasonality (bio15) and precipitation of driest month (bio14) are the significant contributors to the occurrence of chir pine in Uttarakhand Himalayas. This study exemplifies the usefulness of the prediction model of species distribution and offers a more effective way to manage chir pine forest by all means, which is beneficial for both the wildlife and human beings for future prospects.

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Maxent modelling for predicting climate change effects on the potential planting area of tuber mustard in China

The Journal of Agricultural Science ◽

10.1017/s0021859619000686 ◽

2019 ◽

Vol 157 (5) ◽

pp. 375-381 ◽

Cited By ~ 2

Author(s):

H. Q. Li ◽

X. H. Liu ◽

J. H. Wang ◽

L.G. Xing ◽

Y. Y. Fu

Keyword(s):

Suitable Habitat ◽

Maxent Model ◽

Climate Change Effects ◽

Mean Temperature ◽

Chongqing City ◽

Diurnal Range ◽

Maxent Modelling ◽

Shanghai City ◽

Tuber Mustard ◽

Model Training

AbstractPotential planting area for tuber mustard was simulated using the Maxent model under current and future conditions based on 591 coordinates and 22 environmental layers. Model accuracy was excellent, with area under the receiving operator curve values of 0.967 and 0.958 for model training and testing, respectively. Dominant factors were mean diurnal range, mean temperature of the coldest quarter, annual mean temperature and minimum temperature of the coldest month, with thresholds of 6.5–7.5, 5.5–9, 16–19 and 2.0–6.5 °C, respectively. Under current conditions, suitable habitat areas (2.16% of total land in China) were concentrated mainly in Central, Southwest and East China, which can be defined as three occurrence and diffusion centres. In the 2050s and 2070s, suitable habitat areas are predicted to change to 3.72 and 3.92%, and 3.60 and 3.73% under scenarios RCP4.5 and RCP6.0, respectively, indicating that suitable habitat areas will increase slightly. However, future distribution of tuber mustard was predicted to differ among provinces or cities, i.e. predicted suitable habitat areas in Sichuan Province increased up to the 2050s but remained relatively unchanged between the 2050s and 2070s; in Chongqing city they first increased and then decreased; in Hunan, Anhui, Jiangsu, Zhejiang and Fujian Provinces they increased continuously; and in Guizhou, Hubei, Jiangxi Provinces and Shanghai city they first decreased, and then increased. The results from the current study provide useful information for management decisions of tuber mustard.

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Predicting the potential distribution of striped hyena Hyaena hyaena in Iran

Belgian Journal of Zoology ◽

10.26496/bjz.2020.80 ◽

2020 ◽

Vol 150 ◽

Author(s):

Amirhossein Dadashi-Jourdehi ◽

Bahman Shams-Esfandabad ◽

Abbas Ahmadi ◽

Hamid Reza Rezaei ◽

Hamid Toranj-Zar

Keyword(s):

Potential Distribution ◽

High Rate ◽

Suitable Habitat ◽

Distribution Models ◽

Distribution Modelling ◽

Maxent Model ◽

Eastern Iran ◽

Striped Hyena ◽

Management Priorities ◽

Hyaena Hyaena

Predictive potential distribution modelling is crucial in outlining habitat usage and establishing conservation management priorities. Association among species occurrence and environmental and spatial characteristics has been calculated with species distribution models. Herein, we used maximum entropy distribution modelling (MaxEnt) for predicting the potential distribution of striped hyena Hyaena hyaena in the entire country of Iran, using a number of occurrence records (i.e., 118) and environmental variables derived from remote sensing. The MaxEnt model showed a high rate of success according to AUC test scores (0.97). Our results are roughly congruent with previous studies suggesting that mountainous re-gions in northern and western Iran, and the plains in central and eastern Iran are a suitable habitat for H. hyaena.

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Modelling Potential Distribution of Snow Leopards in Pamir, Northern Pakistan: Implications for Human–Snow Leopard Conflicts

Sustainability ◽

10.3390/su132313229 ◽

2021 ◽

Vol 13 (23) ◽

pp. 13229

Author(s):

Wajid Rashid ◽

Jianbin Shi ◽

Inam ur Rahim ◽

Muhammad Qasim ◽

Muhammad Naveed Baloch ◽

...

Keyword(s):

Land Use ◽

Potential Distribution ◽

Model Performance ◽

Suitable Habitat ◽

Snow Leopard ◽

Northern Pakistan ◽

Human Presence ◽

Temperature Range ◽

Maxent Model ◽

Snow Leopards

The snow leopard (Panthera uncia) is a cryptic and rare big cat inhabiting Asia’s remote and harsh elevated areas. Its population has decreased across the globe for various reasons, including human–snow leopard conflicts (HSCs). Understanding the snow leopard’s distribution range and habitat interactions with human/livestock is essential for understanding the ecological context in which HSCs occur and thus gives insights into how to mitigate HSCs. In this study, a MaxEnt model predicted the snow leopard’s potential distribution and analyzed the land use/cover to determine the habitat interactions of snow leopards with human/livestock in Karakoram–Pamir, northern Pakistan. The results indicated an excellent model performance for predicting the species’ potential distribution. The variables with higher contributions to the model were the mean diurnal temperature range (51.7%), annual temperature range (18.5%), aspect (14.2%), and land cover (6.9%). The model predicted approximately 10% of the study area as a highly suitable habitat for snow leopards. Appropriate areas included those at an altitude ranging from 2721 to 4825 m, with a mean elevation of 3796.9 ± 432 m, overlapping between suitable snow leopard habitats and human presence. The human encroachment (human settlements and agriculture) in suitable snow leopard habitat increased by 115% between 2008 and 2018. Increasing encroachment and a clear overlap between snow leopard suitable habitat and human activities, signs of growing competition between wildlife and human/livestock for limited rangeland resources, may have contributed to increasing HSCs. A sound land use plan is needed to minimize overlaps between suitable snow leopard habitat and human presence to mitigate HSCs in the long run.

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