scholarly journals A Bioclimate-Based Maximum Entropy Model for Comperiella calauanica Barrion, Almarinez and Amalin (Hymenoptera: Encyrtidae) in the Philippines

Insects ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 26
Author(s):  
Billy Joel M. Almarinez ◽  
Mary Jane A. Fadri ◽  
Richard Lasina ◽  
Mary Angelique A. Tavera ◽  
Thaddeus M. Carvajal ◽  
...  
Keyword(s):  
Maximum Entropy ◽  
Habitat Suitability ◽  
Species Distribution Model ◽  
Biological Control Agent ◽  
The Philippines ◽  
Distribution Model ◽  
Field Surveys ◽  
Probability Of Occurrence ◽  
Precipitation Seasonality ◽  
Bioclimatic Variables

Comperiella calauanica is a host-specific endoparasitoid and effective biological control agent of the diaspidid Aspidiotus rigidus, whose outbreak from 2010 to 2015 severely threatened the coconut industry in the Philippines. Using the maximum entropy (Maxent) algorithm, we developed a species distribution model (SDM) for C. calauanica based on 19 bioclimatic variables, using occurrence data obtained mostly from field surveys conducted in A. rigidus-infested areas in Luzon Island from 2014 to 2016. The calculated the area under the ROC curve (AUC) values for the model were very high (0.966, standard deviation = 0.005), indicating the model’s high predictive power. Precipitation seasonality was found to have the highest relative contribution to model development. Response curves produced by Maxent suggested the positive influence of mean temperature of the driest quarter, and negative influence of precipitation of the driest and coldest quarters on habitat suitability. Given that C. calauanica has been found to always occur with A. rigidus in Luzon Island due to high host-specificity, the SDM for the parasitoid may also be considered and used as a predictive model for its host. This was confirmed through field surveys conducted between late 2016 and early 2018, which found and confirmed the occurrence of A. rigidus in three areas predicted by the SDM to have moderate to high habitat suitability or probability of occurrence of C. calauanica: Zamboanga City in Mindanao; Isabela City in Basilan Island; and Tablas Island in Romblon. This validation in the field demonstrated the utility of the bioclimate-based SDM for C. calauanica in predicting habitat suitability or probability of occurrence of A. rigidus in the Philippines.

scholarly journals SPECIES DISTRIBUTION MODELLING OF TWO SPECIES ENDEMIC TO THE PHILIPPINES TO SHOW THE APPLICABILITY OF MAXENT

2019 ◽  
Vol XLII-4/W19 ◽  
pp. 449-454
Author(s):  
M. Z. G. Untalan ◽  
D. F. M. Burgos ◽  
K. P. Martinez
Keyword(s):  
Species Distribution ◽  
Endemic Species ◽  
Species Distribution Model ◽  
Species Distribution Modelling ◽  
The Philippines ◽  
Distribution Model ◽  
Distribution Modelling ◽  
Machine Learning Model ◽  
Monitor Lizard ◽  
Bioclimatic Variables

Abstract. Maxent is a machine learning model used for species distribution modelling (SDM) that is rising in popularity. As with any species distribution model, it needs to be validated for certain species before being used to generate insights and trusted predictions. Using Maxent, SDM of two endemic species in the Philippines, Varanus palawanensis (Palawan monitor lizard) and Caprimulgus manillensis (Philippine nightjar), were created using presence-only data, with 14 V. palawanensis and 771 C. manillensis occurrences, and 19 bioclimatic variables from BIOCLIM. This study shows the consistency to historical facts of Maxent on two endemic species of the Philippines of varying nature. The applicability of Maxent on the two very different species show that Maxent has high likelihood to give good results for other species. Showing that Maxent is applicable to the species of the Philippines gives additional tools for ecologists and national administrators to lead the development of the Philippines in the direction that conserves the biodiversity of the Philippines and that increases the productivity and quality of life in the Philippines.

scholarly journals Optimization of the Fuzzy Matter Element Method for Predicting Species Suitability Distribution Based on Environmental Data

2018 ◽  
Vol 10 (10) ◽  
pp. 3444 ◽  
Author(s):  
Quanzhong Zhang ◽  
Haiyan Wei ◽  
Zefang Zhao ◽  
Jing Liu ◽  
Qiao Ran ◽  
...  
Keyword(s):  
Species Distribution ◽  
Habitat Suitability ◽  
Species Distribution Model ◽  
Environmental Data ◽  
Distribution Model ◽  
New Approach ◽  
Suitability Index ◽  
Biological Laws ◽  
Experimental Process ◽  
Key Variables

Over the years, with the efforts of many researchers, the field of species distribution model (SDM) has been well explored. The model of fuzzy matter elements (FME), which, combined with GIS to predict species distribution, has received extensive attention since its emergence. Based on previous studies, this paper improved FME, extended the scope of the membership degree and habitat suitability index, and explored the unsuitable areas of species. We have enhanced the limitation effect of key variables on species habitats, making the operation of FME more consistent with biological laws. By optimizing the FME, it could avoid the accumulation of predicted errors with multi-variables, and make the predicted results more reasonable. In this study, Gynostemma pentaphyllum (Thunb.) Makino was used as an example. The experimental process used several major environmental variables (climate, soil, and terrain variables) to predict the habitat suitability distribution of G. pentaphyllum in China for its current and future period, which includes the period of 2050s (average for 2041–2060) and 2070s (average for 2061–2080) under representative concentration pathways 4.5 (RCP4.5). The results of the analysis showed that the model performed well with a high accuracy by reducing the redundancy of the environmental data. The study could relieve the reliance on a large database of environmental information and propose a new approach for protecting the G. pentaphyllum in unsuitable areas under climate change.

scholarly journals POTENTIAL HABITAT MODELING OF WATER HYACINTH IN LAKES OF NEPAL USING MAXENT ALGORITHM

2019 ◽  
Vol IV-5/W2 ◽  
pp. 103-110
Author(s):  
S. S. Thakuri ◽  
P. Shrestha ◽  
M. Deuba ◽  
P. Shah ◽  
O. P. Bhandari ◽  
...  
Keyword(s):  
Water Hyacinth ◽  
Species Distribution Model ◽  
Habitat Modeling ◽  
Distribution Model ◽  
Primary Data ◽  
Suitable Habitat ◽  
Alien Plant ◽  
Potential Habitat ◽  
Bioclimatic Variables ◽  
Maxent Algorithm

Abstract. Invasive Alien Plant Species are spreading outside of their natural geographic range. Water hyacinth (Eichhornia crassipes) is one of the most widely and rapidly spreading invasive species throughout the tropical and subtropical regions of Nepal. In the last decade, water hyacinth has become a chronic problem in many major lakes of Nepal which have affected the habitat aquatic plants and animals. Our study focuses on potential habitat modeling of Water hyacinth over the major lakes of Nepal using Maxent algorithm. Primary data used for modeling were 19 bioclimatic variables and Shuttle Radar Topography Model (SRTM) Digital Elevation Model (DEM). After preparation of the species distribution model, major lakes of Nepal were overlaid over the model to prepare potential invasive map. The performance and accuracy of potential habitat distribution model was evaluated using parameter Area under the Receiver Operating Characteristic Curve (AUC) which was within the range of 0.9–1. Validation of the model was done for the year 2015 with precision and recall, overall accuracy and F-measure and its values are 93% and 85%, 87% and 89% respectively. The model prepared for 2030 and 2050 shows the most suitable habitat for water hyacinth is in province 2 of Nepal and the moderately suitable habitat for this species is plain area of Province 4, 7 and 5. Similarly, the area of potential habitat has been increasing from current scenario to 2030 and 2050. From the potential invasion map, it can be observed that lakes in the Terai and Churey regions have the high risk of invasion of water hyacinth.

scholarly journals Habitat suitability modelling to assess the introductions of Aedes albopictus (Diptera, Culicidae) in the Netherlands

2020 ◽  
Author(s):  
Adolfo Ibañez-Justicia ◽  
Juan Diego Alcaraz-Hernández ◽  
Ron van Lammeren ◽  
Constantianus J.M. Koenraadt ◽  
Aldo Bergsma ◽  
...  
Keyword(s):  
The Netherlands ◽  
Aedes Albopictus ◽  
Habitat Suitability ◽  
Species Distribution Model ◽  
Climatic Conditions ◽  
Distribution Model ◽  
Adult Survival ◽  
Climatic Data ◽  
Model Based ◽  
Lst Model

Abstract Background In the Netherlands, Aedes albopictus has been found each year since 2010 during routine exotic mosquito species surveillance at companies that import used tires. We developed habitat suitability models to investigate the potential risk of establishment and spread of this invasive species at these locations. Methods We used two methodologies: first, a species distribution model based on the maximum entropy modelling approach (MaxEnt) taking into consideration updated occurrence data of the species in Europe, and second, a spatial logic conditional model based on the temperature requirements of the species and using land surface temperature data (LST model). Results Suitability assessment obtained with the MaxEnt model at European level accurately reflect the current distribution of the species and these results also depict moderately low values in parts of the Netherlands, Belgium, Denmark, the British islands and southern parts of Scandinavia. Winter temperature was the variable that contributed most to the performance of the model (47.3%). The results of the LST model show that 1) coastal areas are suitable for overwintering of eggs, 2) large areas in the northern part of the country have a low suitability for adult survival, and 3) the entire country is suitable for successful completion of the life cycle if the species is introduced after the winter months. Results of the LST model reveal that temperatures in 2012 and 2014 did not limit the overwintering of eggs or survival of adults at the locations where the species was found. By contrast, for the years 2010, 2011 and 2013, overwintering of eggs at these locations is considered unlikely. Conclusions Results using two modelling methodologies show differences in predicted habitat suitability values. Based on the results of both models, the climatic conditions could hamper the successful overwintering of eggs of Ae. albopictus and their survival as adults in many areas of the country. However, during warm years with mild winters, many areas of the Netherlands offer climatic conditions suitable for developing populations. Regular updates of the models, using updated occurrence and climatic data, are recommended to study the areas at risk.

scholarly journals Associations Between Habitat Quality And Body Size In The Carpathian Land Snail Vestia turgida: Species Distribution Model Selection And Assessment Of Performance

2020 ◽  
Author(s):  
V. Tytar ◽  
O. Baidashnikov
Keyword(s):  
Body Size ◽  
Habitat Quality ◽  
Species Distribution ◽  
Habitat Suitability ◽  
Species Distribution Model ◽  
Land Snail ◽  
Distribution Model ◽  
Distribution Models ◽  
Data Set ◽  
Additive Regression

Species distribution models (SDMs) are generally thought to be good indicators of habitat suitability, and thus of species’ performance, consequently SDMs can be validated by checking whether the areas projected to have the greatest habitat quality are occupied by individuals or populations with higher than average fitness. We hypothesized a positive and statistically significant relationship between observed in the field body size of the snail V. turgida and modelled habitat suitability, tested this relationship with linear mixed models, and found that indeed, larger individuals tend to occupy high-quality areas, as predicted by the SDMs. However, by testing several SDM algorithms, we found varied levels of performance in terms of expounding this relationship. Marginal R2, expressing the variance explained by the fixed terms in the regression models, was adopted as a measure of functional accuracy, and used to rank the SDMs accordingly. In this respect, the Bayesian additive regression trees (BART) algorithm (Carlson, 2020) gave the best result, despite the low AUC and TSS. By restricting our analysis to the BART algorithm only, a variety of sets of environmental variables commonly or less used in the construction of SDMs were explored and tested according to their functional accuracy. In this respect, the SDM produced using the ENVIREM data set (Title, Bemmels, 2018) gave the best result.

scholarly journals Predicting invasion potential of Senna didymobotrya (Fresen.) Irwin & Barneby under the changing climate in Africa

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Elias Ch. Weldemariam ◽  
Sintayehu W. Dejene
Keyword(s):  
Climate Change ◽  
Species Distribution Model ◽  
Characteristic Curve ◽  
Climatic Conditions ◽  
Eastern Africa ◽  
Distribution Model ◽  
Climate Conditions ◽  
Changing Climate ◽  
Bioclimatic Variables ◽  
Suitable Area

Abstract Background Senna didymobotrya is a native African flowering shrub. It is suspected that climate change encourages the introduction and spread of invasive alien species. The possible invasion of S. didymobotrya across the continent is expected to increase in the future due to ongoing climate change. Nonetheless, there is still paucity of empirical evidence on the extent to which the changing climate contributes to the surge of the flowering shrub. This study, therefore, investigated the present and potential invasion of S. didymobotrya using the species distribution model under changing climate conditions. The two representative concentration pathways (RCP4.5 and RCP8.5) and eight bioclimatic variables and one topographic variable were used to simulate the current and future (2050s and 2070s) invasion of S. didymobotrya in Africa. The model performance was assessed using the area under the receiver operating characteristic curve (AUC) and true skill statistics (TSS). Results The results of the study showed that under the current climatic conditions, 18% of Africa is suitable for the establishment and invasion of S. didymobotrya. The most suitable hotspot for S. didymobotrya invasion is eastern Africa, followed by southern Africa. The predicted model showed that by 2050, 3.3% and 3.12% of the continent would be highly suitable areas for the invasion of the species under RCP4.5 and RCP8.5, respectively. In the 2070s, under RCP4.5 and RCP8.5, the highly suitable area would be 3.13% and 2.7%, respectively. In relation to the current suitability, the cumulative projected areas of the low and moderate suitability class under RCP4.5 and RCP8.5 will rise by the years 2050 and 2070. However, under both RCPs, the non-suitable area for S. didymobotrya invasion would gradually decrease. Conclusions From the findings, it can be concluded that the ecosystem’s vulnerability to S. didymobotrya invasion under future climatic conditions will proliferate significantly. Hence, to prevent the projected harm to biodiversity and ecosystem services, governments need to focus their future biodiversity management and policy directions on the means and strategies of minimizing the invasion and the distribution rate of S. didymobotrya across habitat types.

scholarly journals Possible changes in spatial distribution of walnut (Juglans regia L.) in Europe under warming climate

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Sonia Paź-Dyderska ◽  
Andrzej M. Jagodziński ◽  
Marcin K. Dyderski
Keyword(s):  
Environmental Management ◽  
Species Distribution Model ◽  
Juglans Regia ◽  
Range Shift ◽  
Distribution Model ◽  
Distribution Area ◽  
Distribution Data ◽  
Global Circulation Models ◽  
Annual Range ◽  
Bioclimatic Variables

AbstractJuglans regia L. is a species of great importance for environmental management due to attractive wood and nutritious fruits, but also high invasive potential. Thus, uncertainties connected with its range shift are essential for environmental management. We aimed to predict the future climatic optimum of J. regia in Europe under changing climate, to assess the most important climatic factors that determine its potential distribution, and to compare the results obtained among three different global circulation models (GCMs). We used distribution data from the Global Biodiversity Information Facility and completed it with data from the literature. Using the MaxEnt algorithm, we prepared a species distribution model for the years 2061–2080 using 19 bioclimatic variables. We applied three emission scenarios, expressed by representative concentration pathways (RCPs): RCP2.6, RCP4.5, and RCP8.5 and three GCMs: HadGEM2-ES, IPSL-CM5A-LR, and MPI-SM-LR. Our study predicted northward shift of the species, with simultaneous distribution loss at the southern edge of the current range, driven by increasing climate seasonality. Temperature seasonality and temperature annual range were the predictors of highest importance. General trends are common for the projections presented, but the variability of our projections among the GCMs or RCPs applied (predicted range will contract from 17.4 to 84.6% of the current distribution area) shows that caution should be maintained while managing J. regia populations. Adaptive measures should focus on maintaining genetic resources and assisted migration at the southern range edge, due to range contraction. Simultaneously, at the northern edge of the range, J. regia turns into an invasive species, which may need risk assessments and control of unintended spread.

scholarly journals Associations Between Habitat Quality and Body Size in the Carpathian-Podolian Land Snail Vestia turgida (Gastropoda, Clausiliidae): Species Distribution Model Selection and Assessment of Performance

Zoodiversity ◽  
2021 ◽  
Vol 55 (1) ◽  
pp. 25-40
Author(s):  
V. Tytar
Keyword(s):  
Body Size ◽  
Habitat Quality ◽  
Species Distribution ◽  
Habitat Suitability ◽  
Species Distribution Model ◽  
Land Snail ◽  
Distribution Model ◽  
Distribution Models ◽  
Data Set ◽  
Additive Regression

Species distribution models (SDMs) are generally thought to be good indicators of habitat suitability, and thus of species’ performance. Consequently SDMs can be validated by checking whether the areas projected to have the greatest habitat quality are occupied by individuals or populations with higher than average fi tness. We hypothesized a positive and statistically signifi cant relationship between observed in the fi eld body size of the snail V. turgida (Rossmässler, 1836) and modelled habitat suitability, tested this relationship with linear mixed models, and found that indeed, larger individuals tend to occupy high-quality areas, as predicted by the SDMs. However, by testing several SDM algorithms, we found varied levels of performance in terms of expounding this relationship. Marginal R2 expressing the variance explained by the fi xed terms in the regression models, was adopted as a measure of functional accuracy, and used to rank the SDMs accordingly. In this respect, the Bayesian additive regression trees (BART) algorithm gave the best result, despite the low AUC and TSS. By restricting our analysis to the BART algorithm only, a variety of sets of environmental variables commonly or less used in the construction of SDMs were explored and tested according to their functional accuracy. In this respect, the SDM produced using the ENVIREM data set gave the best result.

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