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

MaxEnt modeling of the potential risk of schistosomiasis in the Philippines using bioclimatic factors

Schistosomiasis is a parasitic infection caused by Schistosoma japonicum. It remains a principal local health issue in the Philippines, demonstrating endemicity in 28 provinces and afflicting thousands of Filipino individuals annually. Despite this, no clear distribution maps for the disease have been comprehensively reported. Therefore, species distribution modeling (SDM) employing the MaxEnt algorithm and GIS application techniques was utilized to denote the potential risk of schistosomiasis in the country. With a high AUC score of 0.846, the SDM yielded a favorable and reliable correlative map illustrating a predicted schistosomal temporal distribution concentrated primarily on the country's eastern portion with a more pronounced wet than dry season. The precipitation of the driest quarter was determined to be the most significant contributing factor among the bioclimatic variables evaluated. This suggests a possible increase in adaptations concerning the rainfall and thermal tolerances of the parasites' vectors. Moreover, socioeconomic status between Philippine regions revealed an inverse proportion with the number of schistosomiasis cases. This study also discussed the potential role of climate change on the range shifts and the potential risk of parasite infection in the Philippines.

Effects of Climatic Change on Potential Distribution of Spogostylum ocyale (Diptera: Bombyliidae) in the Middle East Using Maxent Modelling

Spogostylum ocyale (Wiedemann 1828) is a large robust species of bee fly (family Bombyliidae), known to be a larval ectoparasitoid as well as an important flower pollinator as an adult. This species has become extremely rare or has disappeared from many of its historic habitats due to substantial changes in floral and faunal compositions in recent years. Climate change and urbanisation, together with other anthropogenic activities, may be to blame for these changes. Distribution modelling based on environmental variables together with known occurrences is a powerful tool in analytical biology, with applications in ecology, evolution, conservation management, epidemiology and other fields. Based on climatological and topographic data, the current and future distributions of the parasitoid in the Middle East region was predicted using the maximum entropy model (Maxent). The model performance was satisfactory (AUC mean = 0.834; TSS mean = 0.606) and revealed a good potential distribution for S. ocyale featured by the selected factors. A set of seven predictors was chosen from 19 bioclimatic variables and one topographic variable. The results show that the distribution of S. ocyale is mainly affected by the maximum temperature of the warmest period (Bio5) and temperature annual range (Bio7). According to the habitat suitability map, coastal regions with warm summers and cold winters had high to medium suitability. However, future scenarios predict a progressive decline in the extent of suitable habitats with global climate warming. These findings lead to robust conservation management measures in current or future conservation planning.

Maximum Entropy (MaxEnt) as extreme distribution indicator of two Neotropical fruit fly parasitoids in irrigated drylands of Argentina

The figitid Ganaspis pelleranoi and the braconid Doryctobracon areolatus (Hym: Braconidae, Opiinae) are wide-ranging (from Florida, USA to Argentina) fruit fly parasitoids with tropical and subtropical distribution with a wet and temperate climate. In Argentina, both parasitoid species are thought to be restricted to the subtropical rainforests of the northwest and northeast, locally known as 'Yungas' and 'Paranaense' forests, respectively. However, these species recently have been recorded at the Monte and Thistle of the Prepuna eco-region, an arid region of central-western Argentina. Despite the extreme environmental conditions, anthropic artificial irrigation seems to be playing a fundamental role in fostering the presence and persistence of these species. Maximum Entropy (MaxEnt) models were developed to assess the suitability of these areas to harbor both species. The present work is a first approach to identify suitable areas for the distribution of these two fruit fly biological control agents in the American continent; based on 19 bioclimatic variables. Furthermore, the models resulting from including the new records in the 'Monte' eco-region suggest that local populations may become adapted to particular micro-environmental conditions generated by artificial irrigation. Models revealed that these artificial oases are suitable for G. pelleranoi but seem to be unsuitable for D. areolatus. This first and new approach to the area suitability of these species invites to produce models that reflect actual distribution including more records of presence in oases with similar conditions, thus decreasing the bias of the model generated by over reliance on areas with higher humidity (forest), which correspond to the distribution known before the inclusion of the new records.