scholarly journals Challenges of predicting the potential distribution of a slow-spreading invader: a habitat suitability map for an invasive riparian tree

2010 ◽  
Vol 13 (1) ◽  
pp. 153-163 ◽  
Author(s):  
Catherine S. Jarnevich ◽  
Lindsay V. Reynolds
2019 ◽  
Vol 11 (12) ◽  
pp. 3452 ◽  
Author(s):  
Marjaneh Mousazade ◽  
Gholamabbas Ghanbarian ◽  
Hamid Reza Pourghasemi ◽  
Roja Safaeian ◽  
Artemi Cerdà

The identification of geographical distribution of a plant species is crucial for understanding the importance of environmental variables affecting plant habitat. In the present study, the spatial potential distribution of Astragalus fasciculifolius Boiss. as a key specie was mapped using maximum entropy (Maxent) as data mining technique and bivariate statistical model (FR: frequency ratio) in marl soils of southern Zagros, Iran. The A. fasciculifolius locations were identified and recorded by intensive field campaigns. Then, localities points were randomly split into a 70% training dataset and 30% for validation. Two climatic, four topographic, and eight edaphic variables were used to model the A. fasciculifolius distribution and its habitat potential. Maps of environmental variables were generated using Geographic Information System (GIS). Next, the habitat suitability index (HSI) maps were produced and classified by means of Maxent and FR approaches. Finally, the area under the receiver operating characteristic (AUC-ROC) curve was used to compare the performance of maps produced by Maxent and FR models. The interpretation of environmental variables revealed that the climatic and topographic parameters had less impact compared to edaphic variables in habitat distribution of A. fasciculifolius. The results showed that bulk density, nitrogen, acidity (pH), sand, and electrical conductivity (EC) of soil are the most significant variables that affect distribution of A. fasciculifolius. The validation of results showed that AUC values of Maxent and FR models are 0.83 and 0.76, respectively. The habitat suitability map by the better model (Maxent) showed that areas with high and very high suitable classes cover approximately 22% of the study area. Generally, the habitat suitability map produced using Maxent model could provide important information for conservation planning and a reclamation project of the degraded habitat of intended plant species. The distribution of the plants identifies the water, soil, and nutrient resources and affects the fauna distribution, and this is why it is relevant to research and to understand the plant distribution to properly improve the management and to achieve a sustainable management.


2012 ◽  
Vol 3 (2) ◽  
pp. 303-310
Author(s):  
Adam Duarte ◽  
Daniel M. Wolcott ◽  
T. Edwin Chow ◽  
Mark A. Ricca

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.


Author(s):  
Jeffrey T. Morisette ◽  
Catherine S. Jarnevich ◽  
Asad Ullah ◽  
Weijie Cai ◽  
Jeffrey A. Pedelty ◽  
...  

Author(s):  
M. A. H. Muhamad ◽  
R. Che Hasan

Abstract. In recent years, there has been an increasing interest to use high-resolution multibeam dataset and Species Distribution Modelling (SDM) for seagrass habitat suitability model. This requires a specific variable derived from multibeam data and in-situ seagrass occurrence samples. The purpose of this study was (1) to derive variables from multibeam bathymetry data to be used in seagrass habitat suitability model, (2) to produce seagrass habitat suitability model using Maximum Entropy (MaxEnt), and (3) to quantify the contribution of each variable for predicting seagrass habitat suitability map. The study area was located at Merambong Shoal, covering an area of 0.04 km2, situated along Johor Strait. First, twelve (12) variables were derived from bathymetry data collected from multibeam echosounder using Benthic Terrain Modeller (BTM) tool. Secondly, all variables and seagrass occurrence samples were integrated in MaxEnt to produce seagrass habitat suitability map. The results showed that the Area Under Curve (AUC) values based on training and test data were 0.88 and 0.65, respectively. The northwest region of survey area indicated higher habitat suitability of seagrass, while the southeast region of survey area indicated lower suitability. Bathymetry mean found to be the most contributed variables among others. The spatial distribution of seagrass from modelling technique agreed with the previous studies and they are found to be distributed at depths ranging from 2.2 to 3.4 meters whilst less suitable with increasing of water depth. This study concludes that seagrass habitat suitability map with high-resolution pixel size (0.5 meter) can be produced at Merambong Shoal using acoustic data from multibeam echosounder coupled with MaxEnt and underwater video observations.


Forests ◽  
2020 ◽  
Vol 11 (5) ◽  
pp. 530 ◽  
Author(s):  
Gonzalo Vargas-Piedra ◽  
Ricardo David Valdez-Cepeda ◽  
Armando López-Santos ◽  
Arnoldo Flores-Hernández ◽  
Nathalie S. Hernández-Quiroz ◽  
...  

Candelilla (Euphorbia antisyphilitica Zucc.) is a shrub species distributed throughout the Chihuahuan Desert in northern Mexico and southern of the United States of America. Candelilla has an economic importance due to natural wax it produces. The economic importance and the intense harvest of the wax from candelilla seems to gradually reduce the natural populations of this species. The essence of this research was to project the potential distribution of candelilla populations under different climate change scenarios in its natural distribution area in North America. We created a spatial database with points of candelilla presence, according to the Global Biodiversity Information Facility (GBIF). A spatial analysis to predict the potential distribution of the species using Maxent software was performed. Thirteen of 19 variables from the WorldClim database were used for two scenarios of representative concentration pathways (RCPs) (4.5 as a conservative and 8.5 as extreme). We used climate projections from three global climate models (GCMs) (Max Planck institute, the Geophysical Fluid Dynamics Laboratory and the Met Office Hadley), each simulating the two scenarios. The final predicted distribution areas were classified in five on-site possible candelilla habitat suitability categories: none (< 19%), low (20–38%), medium (39–57%), high (58–76%) and very high (> 77%). According to the area under the curve (0.970), the models and scenarios used showed an adequate fit to project the current and future distribution of candelilla. The variable that contributed the most in the three GCMs and the two RCPs was the mean temperature of the coldest quarter with an influence of 45.7% (Jackknife test). The candelilla’s distribution area for North America was predicted as approximately 19.1 million hectares under the current conditions for the high habitat suitability; however, the projection for the next fifty years is not promising because the GCMs projected a reduction of more than 6.9 million hectares using either the conservative or extreme scenarios. The results are useful for conservation of the species in the area with vulnerable wild populations, as well as for the selection of new sites suitable for the species growth and cultivation while facing climate change.


2021 ◽  
Author(s):  
Andri Wibowo

AbstractMalaria remains a major public health problem mainly in particular South East Asian countries. As malaria transmission and Anopheles spp. continues to spread, control interventions should emphasize on the ability to define potential areas that can favor Anopheles spp. distribution. Then there is an urgent need to use novel approach capable to predict potential spatial patterns of Anopheles spp. and delineate malaria potential hotspots for better environmental health planning and management. Here, this study modeled Anopheles spp. potential distribution as a function of 15 bioclimatic variables using Species Distribution Modeling (SDM) in South Coast of West Java Province spans over 20 km from West to East. Findings of this study show that bioclimatic variables and SDM can be used to predict Anopheles spp. habitat suitability, suggesting the possibility of developing models for malaria early warning based on habitat suitability model. The resulting model shows that the potential distributions of Anopheles spp. encompassed areas from West to Central parts of the coasts, with Central parts were the most potential prevalence areas of Anopheles spp. considering this area has higher precipitation. The less potential prevalence areas of Anopheles spp. were observed in the East parts of the coast. The model also shows that inland areas adjacent to the settlements were more potential in comparison to the areas near coast and in the beach. Land cover conditions dominated by cropland, herbaceous wetland, and inundated land were also influencing the Anopheles spp. potential distribution.


2020 ◽  
Author(s):  
Cao Zhen ◽  
Zhang Xiaoyan ◽  
Xue Xuanji ◽  
Zhang Lei ◽  
Zhan Guanqun ◽  
...  

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).


2021 ◽  
Vol 45 (2) ◽  
pp. 241-250
Author(s):  
Ciprian Bîrsan ◽  
Constantin Mardari ◽  
Ovidiu Copoţ ◽  
Cătălin Tănase

Clathrus archeri is a saprophytic fungus native to the southern hemisphere which was introduced in Europe in the early twentieth century. Although it is naturalized in most regions of Central Europe, in Romania it is considered rather a rare species because it has been identified in only a few localities. Because of the rapid expansion of its range throughout Europe some authors assign this species an invasive potential. The objective of the paper was to identify both the potential distribution area and the potential suitable habitats for expansion in Romania and to highlight the environmental variables driving the probability of its occurrence. The maximum entropy model approach implemented in Maxent was used to model the species? potential distribution. The results highlighted altitude, snow cover length, the mean temperature of the driest quarter, and precipitation in the coldest quarter as the most important predictors of species? potential distribution in Romania. The map of the predicted distribution showed that the highest probability of occurrence for this species is in the mountainous and adjacent areas, while the map of habitat suitability confirmed that the best environmental conditions are in the Carpathians, while the most unfavourable are in the south-eastern regions of the country.


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