Predicting the Potential Global Distribution of Amblyomma americanum (Acari: Ixodidae) under Near Current and Future Climatic Conditions, Using the Maximum Entropy Model

Amblyomma americanum (the lone star tick) is a pathogen vector, mainly from eastern North America, that bites humans. With global integration and climate change, some ticks that are currently confined to a certain place may begin to spread out; some reports have shown that they are undergoing rapid range expansion. The difference in the potential geographic distribution of A. americanum under current and future climatic conditions is dependent on environment variables such as temperature and precipitation, which can affect their survival. In this study, we used a maximum entropy (MaxEnt) model to predict the potential geographic distribution of A. americanum. The MaxEnt model was calibrated at the native range of A. americanum using occurrence data and the current climatic conditions. Seven WorldClim climatic variables were selected by the jackknife method and tested in MaxEnt using different combinations of model feature class functions and regularization multiplier values. The best model was chosen based on the omission rate and the lowest Akaike information criterion. The resulting model was then projected onto the global scale using the current and future climate conditions modeled under four greenhouse gas emission scenarios.

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Application of a Maximum Entropy Model for Mineral Prospectivity Maps

Minerals ◽

10.3390/min9090556 ◽

2019 ◽

Vol 9 (9) ◽

pp. 556 ◽

Cited By ~ 3

Author(s):

Binbin Li ◽

Bingli Liu ◽

Ke Guo ◽

Cheng Li ◽

Bin Wang

Keyword(s):

Maximum Entropy ◽

Controlling Factors ◽

Controlling Factor ◽

Geochemical Data ◽

Potential Zone ◽

Maximum Entropy Model ◽

Entropy Model ◽

Copper Deposits ◽

Maxent Model ◽

Mineral Prospectivity

The effective integration of geochemical data with multisource geoscience data is a necessary condition for mapping mineral prospects. In the present study, based on the maximum entropy principle, a maximum entropy model (MaxEnt model) was established to predict the potential distribution of copper deposits by integrating 43 ore-controlling factors from geological, geochemical and geophysical data. The MaxEnt model was used to screen the ore-controlling factors, and eight ore-controlling factors (i.e., stratigraphic combination entropy, structural iso-density, Cu, Hg, Li, La, U, Na2O) were selected to establish the MaxEnt model to determine the highest potential zone of copper deposits. The spatial correlation between each ore-controlling factor and the occurrence of a copper mine was studied using a response curve, and the relative importance of each ore-controlling factor was determined by jackknife analysis in the MaxEnt model. The results show that the occurrence of copper ore is positively correlated with the content of Cu, Hg, La, structural iso-density and stratigraphic combination entropy, and negatively correlated with the content of Na2O, Li and U. The model’s performance was evaluated by the area under the receiver operating characteristic curve (AUC), Cohen’s maximized Kappa and true skill statistic (TSS) (training AUC = 0.84, test AUC = 0.8, maximum Kappa = 0.5 and maximum TSS = 0.6). The results indicate that the model can effectively integrate multi-source geospatial data to map mineral prospectivity.

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Predicting the Potential Distribution of Two Varieties of Litsea coreana (Leopard-Skin Camphor) in China under Climate Change

Forests ◽

10.3390/f11111159 ◽

2020 ◽

Vol 11 (11) ◽

pp. 1159

Author(s):

Jinwen Pan ◽

Xin Fan ◽

Siqiong Luo ◽

Yaqin Zhang ◽

Shan Yao ◽

...

Keyword(s):

Climate Change ◽

Potential Distribution ◽

Greenhouse Gas Emission ◽

Climatic Conditions ◽

Raw Material ◽

Vegetation Growth ◽

Maxent Model ◽

Diurnal Range ◽

Huai River ◽

Suitable Area

Climate change considerably affects vegetation growth and may lead to changes in vegetation distribution. Leopard-skin camphor is an endangered species, and the main raw material for hawk tea, and has various pharmacodynamic functions. Studying the potential distribution of two leopard-skin camphor varieties under climate change should assist in the effective protection of these species. We collected the distribution point data for 130 and 89 Litsea coreana Levl. var. sinensis and L. coreana Levl. var. lanuginosa, respectively, and data for 22 environmental variables. We also predicted the potential distribution of the two varieties in China using the maximum entropy (MaxEnt) model and analyzed the key environmental factors affecting their distribution. Results showed that the two varieties are mainly located in the subtropical area south of the Qinling Mountains–Huai River line in the current and future climate scenarios, and the potentially suitable area for L. coreana Levl. var. lanuginosa is larger than that of L. coreana Levl. var. sinensis. Compared with current climatic conditions, the potentially suitable areas of the two leopard-skin camphor varieties will move to high-latitude and -altitude areas and the total suitable area will increase slightly, while moderately and highly suitable areas will be significantly reduced under future climatic scenarios. For example, under a 2070-RCP8.5 (representative of a high greenhouse gas emission scenario in the 2070s) climatic scenario, the highly suitable areas of L. coreana Levl. var. sinensis and L. coreana Levl. var. lanuginosa are 6900 and 300 km2, and account for only 10.27% and 0.21% of the current area, respectively. Temperature is the key environmental factor affecting the potential distribution of the two varieties, especially the mean daily diurnal range (Bio2) and the min temperature of the coldest month (Bio6). The results can provide a reference for relevant departments in taking protective measures to prevent the decrease or extinction of the species under climate change.

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Predicting the Potential Geographic Distribution and Habitat Suitability of Two Economic Forest Trees on the Loess Plateau, China

Forests ◽

10.3390/f12060747 ◽

2021 ◽

Vol 12 (6) ◽

pp. 747

Author(s):

Wei Xu ◽

Jingwei Jin ◽

Jimin Cheng

Keyword(s):

Loess Plateau ◽

Geographic Distribution ◽

Habitat Suitability ◽

Prunus Armeniaca ◽

Forest Trees ◽

The Loess Plateau ◽

Entropy Model ◽

Bioclimatic Variables ◽

Suitable Habitats ◽

Potential Geographic Distribution

The Loess Plateau is one of the most fragile ecosystems in the world. In order to increase the biodiversity in the area, develop sustainable agriculture and increase the income of the local people, we simulated the potential geographic distribution of two economic forest trees (Malus pumila Mill and Prunus armeniaca L.) in the present and future under two climate scenarios, using the maximum entropy model. In this study, the importance and contributions of environmental variables, areas of suitable habitats, changes in habitat suitability, the direction and distance of habitat range shifts, the change ratios for habitat area and land use proportions, were measured. According to our results, bioclimatic variables, topographic variables and soil variables play a significant role in defining the distribution of M. pumila and P. armeniaca. The min temperature of coldest month (bio6) was the most important environmental variable for the distribution of the two economic forest trees. The second most important factors for M. pumila and P. armeniaca were, respectively, the elevation and precipitation of the driest quarter (bio17). At the time of the study, the area of above moderately suitable habitats (AMSH) was 8.7967 × 104 km2 and 11.4631 × 104 km2 for M. pumila and P. armeniaca. The effect of Shared Socioeconomic Pathway (SSP) 5-85 was more dramatic than that of SSP1-26. Between now and the 2090s (SSP 5-85), the AMSH area of M. pumila is expected to decrease to 7.5957 × 104 km2, while that of P. armeniaca will increase to 34.6465 × 104 km2. The suitability of M. pumila decreased dramatically in the south and southeast regions of the Loess Plateau, increased in the middle and west and resulted in a shift in distance in the range of 78.61~190.63 km to the northwest, while P. armeniaca shifted to the northwest by 64.77~139.85 km. This study provides information for future policymaking regarding economic forest trees in the Loess Plateau.

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Spatial-temporal habitat suitability for lemuru fish (Sardinella lemuru) using the Second-generation Global Imager (SGLI) and Maximum Entropy model in the Bali Strait, Indonesia

IOP Conference Series Earth and Environmental Science ◽

10.1088/1755-1315/944/1/012066 ◽

2021 ◽

Vol 944 (1) ◽

pp. 012066

Author(s):

N Gustantia ◽

T Osawa ◽

I W S Adnyana ◽

D Novianto ◽

Chonnaniyah

Keyword(s):

Maximum Entropy ◽

Habitat Suitability ◽

Second Generation ◽

Maximum Entropy Model ◽

Entropy Model ◽

Essential Information ◽

Fishery Resource ◽

Chl A ◽

Maxent Model ◽

Temporal Prediction

Abstract Lemuru fish (Sardinella lemuru), the most dominant fishery resource, has economic values for the fisherman fishing activities in the Bali Strait (between Jawa and Bali islands), Indonesia. Spatial and temporal prediction for the fishing location is essential information for effective fisheries management. The high spatial resolution of sea surface temperature (SST) and Chlorophyll-a (Chl-a) by the second-generation global imager (SGLI) on the global change observation mission (GCOM-C) satellite was employed for the input of the Maximum Entropy Model (MaxEnt) to predict the potential fishing area of lemuru fish in 2020. This study analyzed SST and Chl-a using the SGLI data and shows the variability of SST and Chl-a for lemuru fish-catching data. The MaxEnt model performance to predict the habitat suitability for lemuru fish in the Bali Strait has been shown in this study. As a result, the maximum average Chl-a estimated in August 2020 was around 1.62 mg m−3 and maximum SST in March 2020 around 28.12°C. The correlation between SST and Chl-a with total lemuru fish-catching were -0.209 and 0.375 for SST and Chl-a, respectively. The prediction of lemuru fishing areas using the MaxEnt model showed excellent model evaluations with a correlation value higher than 0.80.

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Predicting the potential distribution of the endemic seabird Pelecanus thagus in the Humboldt Current Large Marine Ecosystem under different climate change scenarios

PeerJ ◽

10.7717/peerj.7642 ◽

2019 ◽

Vol 7 ◽

pp. e7642

Author(s):

Jaime A. Cursach ◽

Aldo Arriagada ◽

Jaime R. Rau ◽

Jaime Ojeda ◽

Gustavo Bizama ◽

...

Keyword(s):

Climate Change ◽

Geographic Distribution ◽

Primary Productivity ◽

Climatic Conditions ◽

Future Climate Change ◽

Climate Change Scenarios ◽

Southern Chile ◽

Breeding Distribution ◽

Current Potential ◽

Potential Geographic Distribution

Background The effects of global climate change on species inhabiting marine ecosystems are of growing concern, especially for endemic species that are sensitive due to restricted distribution. One method employed for determining the effects of climate change on the distribution of these organisms is species distribution modeling. Methods We generated a model to evaluate the potential geographic distribution and breeding distribution of the Peruvian pelican (Pelecanus thagus). Based on maximum entropy modeling (MaxEnt), we identified the environmental factors that currently affect its geographic distribution and breeding. Then we predicted its future distribution range under two climate change scenarios: moderate (rcp 2.6) and severe (rcp 8.5). Results The mean daytime temperature range and marine primary productivity explain the current potential distribution and breeding of the pelican. Under the future climate change scenarios, the spatial distribution of the pelican is predicted to slightly change. While the breeding distribution of the pelican can benefit in the moderate scenario, it is predicted to decrease (near −20 %) in the severe scenario. Discussion The current potential geographic distribution of the pelican is influenced to a large extent by thermal conditions and primary productivity. Under the moderate scenario, a slight increase in pelican breeding distribution is predicted. This increase in habitable area is explained by the climatic conditions in southern Chile, and those climatic conditions will likely be similar to the current conditions of the central coast of Chile. We predict that the coasts of southern Chile will constitute an important refuge for the conservation of the Peruvian pelican under future climate change scenarios.

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Projecting the Potential Distribution of Glossina morsitans (Diptera: Glossinidae) under Climate Change Using the MaxEnt Model

Biology ◽

10.3390/biology10111150 ◽

2021 ◽

Vol 10 (11) ◽

pp. 1150

Author(s):

Ruobing Zhou ◽

Yuan Gao ◽

Nan Chang ◽

Tai Gao ◽

Delong Ma ◽

...

Keyword(s):

Human African Trypanosomiasis ◽

Climatic Factors ◽

Sub Saharan Africa ◽

Large Area ◽

Glossina Morsitans ◽

Entropy Model ◽

Climate Conditions ◽

Maxent Model ◽

Sub Saharan ◽

Suitable Habitats

Glossina morsitans is a vector for Human African Trypanosomiasis (HAT), which is mainly distributed in sub-Saharan Africa at present. Our objective was to project the historical and future potentially suitable areas globally and explore the influence of climatic factors. The maximum entropy model (MaxEnt) was utilized to evaluate the contribution rates of bio-climatic factors and to project suitable habitats for G. morsitans. We found that Isothermality and Precipitation of Wettest Quarter contributed most to the distribution of G. morsitans. The predicted potentially suitable areas for G. morsitans under historical climate conditions would be 14.5 million km2, including a large area of Africa which is near and below the equator, small equatorial regions of southern Asia, America, and Oceania. Under future climate conditions, the potentially suitable areas are expected to decline by about −5.38 ± 1.00% overall, under all shared socioeconomic pathways, compared with 1970–2000. The potentially suitable habitats of G. morsitans may not be limited to Africa. Necessary surveillance and preventive measures should be taken in high-risk regions.

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Predicting the Potential Geographic Distribution of Sirex nitobei in China under Climate Change Using Maximum Entropy Model

Forests ◽

10.3390/f12020151 ◽

2021 ◽

Vol 12 (2) ◽

pp. 151

Author(s):

Tai Gao ◽

Qiang Xu ◽

Yang Liu ◽

Jiaqiang Zhao ◽

Juan Shi

Keyword(s):

Climate Change ◽

Maximum Entropy ◽

Geographic Distribution ◽

Maximum Temperature ◽

Total Precipitation ◽

Maximum Entropy Model ◽

Entropy Model ◽

Monthly Average ◽

Monthly Total Precipitation ◽

Monthly Total

Sirex nitobei, an Asian native wood wasp species, is a major pest in coniferous commercial forestry, infesting and weakening conifers through its obligate mutualism with a wood-rotting fungus species. The combination of wood wasp larvae and obligate mutualistic fungus causes the breakdown of plant vascular tissue, leading to the weakening of the plant and eventually to death, as well as a high economic cost in commercial forestry. Since it was first recorded in China in the early 1980s, S. nitobei has widely spread and become successfully established. Despite its extensive distribution range, little is known about the factors influencing current and future distribution patterns for potential pest control and monitoring. We used a maximum entropy model in conjunction with climate variables and shared socio-economic pathways to predict the current and future distribution of S. nitobei in China. We used the jackknife method and correlation analysis to select the bioclimatic and environmental variables that influence the geographic distribution of S. nitobei, which resulted in the inclusion of the monthly total precipitation in July (prec7), the monthly average maximum temperature in February (tmax2), the monthly average minimum temperature in July (tmin7), the monthly total precipitation in December (prec12), and isothermality (bio3). We found that precipitation and temperature influenced the potentially suitable areas, as predicted by the maximum entropy model. Moreover, the association of the fungus, the wood wasp, and the host plant impacts are related to availability of moisture and temperature, where moisture affects the growth of the fungus, and temperature influences the emergence, development and growth of larvae. Under the current climate conditions, the total potential suitable areas increased by 18.74%, while highly suitable and moderately suitable areas increased by 28.35 and 44.05%, respectively, under the 2081–2100 ssp245, 370 scenarios. Favorable conditions under climate change, low rainfall, and high temperature will favor the speedy larval development, the growth of its obligate nutritional fungal mutualist and the ability of S. nitobei to rapidly spread in previously unsuitable areas.

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Spatial Distribution of the Mexican Daisy, Erigeron karvinskianus, in New Zealand under Climate Change

Climate ◽

10.3390/cli7020024 ◽

2019 ◽

Vol 7 (2) ◽

pp. 24 ◽

Cited By ~ 3

Author(s):

Lauren Hannah ◽

Glenn Aguilar ◽

Dan Blanchon

Keyword(s):

Spatial Distribution ◽

New Zealand ◽

Species Distribution ◽

Forest Restoration ◽

Greenhouse Gas Emission ◽

Species Distribution Modeling ◽

Climatic Conditions ◽

Native Forest ◽

Climate Conditions ◽

Distribution Modeling

The invasive species Erigeron karvinskianus or Mexican daisy is considered a significant weed that impacts native forest restoration efforts in New Zealand. Mapping the potential distribution of this species under current and future predicted climatic conditions provides managers with relevant information for developing appropriate management strategies. Using occurrences available from global and local databases, spatial distribution characteristics were analyzed using geostatistical tools in ArcMap to characterize current distribution. Species distribution modeling (SDM) using Maxent was conducted to determine the potential spatial distribution of E. karvinskianus worldwide and in New Zealand with projections into future climate conditions. Potential habitat suitability under future climatic conditions were simulated using greenhouse gas emission trajectories under the Representative Concentration Pathway (RCP) models RCP2.6, RCP4.5, RCP6.0 and RCP8.5 for years 2050 and 2070. Occurrence data were processed to minimize redundancy and spatial autocorrelation; non-correlated environmental variables were determined to minimize bias and ensure robust models. Kernel density, hotspot and cluster analysis of outliers show that populated areas of Auckland, Wellington and Christchurch have significantly greater concentrations of E. karvinskianus. Species distribution modeling results find an increase in the expansion of range with higher RCP values, and plots of centroids show a southward movement of predicted range for the species.

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New records and potential geographic distribution of Elongated Caecilian, Ichthyophis elongatus Taylor, 1965 (Amphibia, Gymnophiona, Ichthyophiidae), endemic to West Sumatra, Indonesia

Check List ◽

10.15560/16.6.1695 ◽

2020 ◽

Vol 16 (6) ◽

pp. 1695-1701

Author(s):

Try Surya Harapan ◽

Ade Prasetyo Agung ◽

Heru Handika ◽

Wilson Novarino ◽

Djong Hon Tjong ◽

...

Keyword(s):

Maximum Entropy ◽

Sea Level ◽

Geographic Distribution ◽

New Records ◽

Paddy Fields ◽

Suitable Habitat ◽

Secondary Forests ◽

Maximum Entropy Modeling ◽

West Sumatra ◽

Potential Geographic Distribution

We present new records of Ichthyophis elongatus Taylor, 1965 in West Sumatra. These records extend the known distribution of the species which was previously only known from the type locality in Padang, West Sumatra. We assess the morphology and habitats of this species and estimate its distribution. Predicted distribution based on maximum entropy modeling suggests a highly suitable habitat for the species throughout the Barisan Mountains at 500–1000 m above sea level. Our models suggest swamps, paddy fields, and secondary forests that are 100–150 m from rivers as the highest possible habitats for the species. Further surveys in two predicted areas based on the models discovered new populations of the species.

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Ecological specificities of the interaction between animal breeding and climate changes, caused by greenhouse gas emissions

Agricultural science and practice ◽

10.15407/agrisp4.03.062 ◽

2017 ◽

Vol 4 (3) ◽

pp. 62-72

Author(s):

O. Zhukorsky ◽

O. Nykyforuk ◽

N. Boltyk

Keyword(s):

Greenhouse Gases ◽

Greenhouse Gas Emissions ◽

Greenhouse Gas ◽

Climatic Conditions ◽

Animal Breeding ◽

Gas Emissions ◽

Climate Conditions ◽

Emissions Inventory ◽

Theoretical Substantiation ◽

Global Problems

Aim. Proper development of animal breeding in the conditions of current global problems and the decrease of anthropogenic burden on environment due to greenhouse gas emissions, caused by animal breeding activity, require the study of interaction processes between animal breeding and external climatic conditions. Methods. The theoretical substantiation of the problem was performed based on scientifi c literature, statistical informa- tion of the UN Food and Agriculture Organization and the data of the National greenhouse gas emissions inventory in Ukraine. Theoretically possible emissions of greenhouse gases into atmosphere due to animal breeding in Ukraine and specifi c farms are calculated by the international methods using the statistical infor- mation about animal breeding in Ukraine and the economic-technological information of the activity of the investigated farms. Results. The interaction between the animal breeding production and weather-and-climate conditions of environment was analyzed. Possible vectors of activity for the industry, which promote global warming and negative processes, related to it, were determined. The main factors, affecting the formation of greenhouse gases from the activity of enterprises, aimed at animal breeding production, were characterized. Literature data, statistical data and calculations were used to analyze the role of animal breeding in the green- house gas emissions in global and national framework as well as at the level of specifi c farms with the consid- eration of individual specifi cities of these farms. Conclusions. Current global problems require clear balance between constant development of sustainable animal breeding and the decrease of the carbon footprint due to the activity of animal breeding.

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