Maximum Entropy Ecological Niche Modeling Research Articles

Using iNaturalist presence data to produce suitability maps for Triatoma protracta, T. rubida and T. recurva in the American Southwest, Texas and northern Mexico, to identify potential transmission zones of Chagas disease.

There are 11 species of triatomines in the USA, with seven reported in the American Southwest. These species are capable of transmitting Trypanosoma cruzi, the etiological agent of Chagas disease, but are generally sylvatic and rarely infect humans in the USA. iNaturalist is one of the most popular citizen science data portals, where users record encounters with any individual organism. As of November 2023, iNaturalist reported 722 confirmed triatomine observations in the American Southwest. Maximum entropy ecological niche modelling and bioclimatic environmental variables were used to predict zones of highest human-triatomine interaction. Models fit well for Triatoma protracta (0.85), T. rubida (0.94), and T. recurva (0.96). Precipitation in the warmest quarter was most predictive of T. protracta presence, while precipitation in the driest quarter was most predictive of T. rubida and T. recurva. Locations identified in the American Southwest with highest potential for human-triatomine interaction, and potential T. cruzi transmission, were coastal California, the Sierra Nevada foothills, southern Arizona and border areas of northern Mexico. Study findings can be used for targeted surveillance efforts to address the paucity of contemporary information regarding triatomine species diversity and geographical and ecological associations in the American Southwest.

Neospora caninum antibodies in bulk tank milk from dairy cattle herds in Italy in relation to reproductive and productive parameters and spatial analysis

Among the available diagnostic techniques, antibody detection in bulk tank milk (BTM) represents a useful tool to estimate and monitor Neospora caninum herd prevalence.To evaluate the prevalence of N. caninum and the effect of parasite infection on herd performances, BTM samples collected from 586 dairy herds located in one of the largest dairy production areas in Italy (Lombardy) were analyzed by an indirect ELISA to detect anti-N. caninum specific antibodies. Generalized linear models (GLMs) were developed. A purely spatial analysis scanning for clusters with high or low rates for N. caninum using the Bernoulli model was performed. A maximum entropy approach was used to estimate the probability of distribution of the parasite based on occurrence records together with environmental variables.Overall, 180 herds resulted positive for N. caninum antibodies on bulk tank milk (P = 30.7 %). A higher risk of seropositivity was evidenced in the provinces of Milano, Cremona, Brescia, and Bergamo (P = 32–40 %); a lower risk was evidenced in Lodi, Pavia, and Mantova (P = 13–24 %). A higher risk of seropositivity was revealed for small-medium farms (101–300 animals) (O.R.=2.8) and for older animals with more than 4 years (O.R.=4.4).Regarding the effect of N. caninum infection on herd performances, the number of inseminations for conception was higher (> 3 inseminations), and the period from calving to conception was longer (> 150 days) for positive farms (O.R.=2.0 and O.R.=2.3, respectively); besides, lower head daily milk production (<20 kg and 21–25 kg) and mature equivalent milk yield (<11,000), and somatic cell counts higher than 300,000 cells/ml were observed for N. caninum positive herds (O.R.=0.4, O.R.=0.4 and O.R.=1.9 respectively).The geographical distribution of N. caninum positive farms with the highest level of probability covers the central sector of the Po Plain where a significant cluster for high risk of parasite infection was shown by spatial scan statistic and Maximum entropy ecological niche modelling. A further significant cluster of low risk occurred in the southern. The climatic and environmental variables with the highest training gain when used in isolation resulted altitude, land use/land cover, and other variables related to temperature and precipitation.Neosporosis is widely distributed in Italian dairy herds and an impact of the parasite on herd performances could be hypothesized. Even if the role of N. caninum in alterations of reproductive and productive parameters should be further explored, veterinarians and farmers should be aware of neosporosis, and control plans should be adopted.

Predicting Current and Future Potential Distributions of Parthenium hysterophorus in Bangladesh Using Maximum Entropy Ecological Niche Modelling

Parthenium weed (Parthenium hysterophorus L.) is among the most noxious invasive alien plant species, which can pose a threat to agro- and native-ecosystems. Despite potential parthenium infestation risks at the south-western regions of the Ganges–Brahmaputra floodplains of Bangladesh, no studies exist that document parthenium infestation. Using field surveys and a maximum entropy (Maxent) modelling approach, the present study tries to address the problem in the concerned region comprised of five Districts: Jashore, Jhenaidah, Chuadanga, Meherpur, and Khustia. The results revealed high infestation in the Jashore, Jhenaidah, and Chuadanga Districts, mainly along roadsides, in grasslands, and in fallow and cropped fields. The greatest abundance of the weed (ca. 30 plants m−2) occurred at the Indian border area, suggesting cross-border spreading, possibly through the linking road systems. Furthermore, we found that under both low and high emissions scenarios (Representative Concentration Pathways 2.6 and 8.5), parthenium weed suitability areas were likely to expand, suggesting an increased threat to the agro-ecosystems of Bangladesh. The present study is the first attempt to survey and model potential parthenium weed distribution affecting one of the major hubs of agricultural production in Bangladesh. The findings of this study can help land managers to make judicious decisions towards the future management of these agro-ecosystems.

Predicted distribution of sand fly (Diptera: Psychodidae) species involved in the transmission of Leishmaniasis in São Paulo state, Brazil, utilizing maximum entropy ecological niche modeling

ABSTRACT Leishmaniasis is a public health problem worldwide. We aimed to predict ecological niche models (ENMs) for visceral (VL) and cutaneous (CL) leishmaniasis and the sand flies involved in the transmission of leishmaniasis in São Paulo, Brazil. Phlebotomine sand flies were collected between 1985 and 2015. ENMs were created for each sand fly species using Maximum Entropy Species Distribution Modeling software, and 20 climatic variables were determined. Nyssomyia intermedia (Lutz & Neiva, 1912) and Lutzomyia longipalpis (Lutz & Neiva, 1912), the primary vectors involved in CL and VL, displayed the highest suitability across the various regions, climates, and topographies. L. longipalpis was found in the border of Paraná an area currently free of VL. The variables with the greatest impact were temperature seasonality, precipitation, and altitude. Co-presence of multiple sand fly species was observed in the cuestas and coastal areas along the border of Paraná and in the western basalt areas along the border of Mato Grosso do Sul. Human CL and VL were found in 475 of 546 (86.7%) and 106 of 645 (16.4%) of municipalities, respectively. Niche overlap between N. intermedia and L. longipalpis was found with 9208 human cases of CL and 2952 cases of VL. ENMs demonstrated that each phlebotomine sand fly species has a unique geographic distribution pattern, and the occurrence of the primary vectors of CL and VL overlapped. These data can be used by public authorities to monitor the dispersion and expansion of CL and VL vectors in São Paulo state.

Predicting Habitat Suitability of Snow Leopards in the Western Himalayan Mountains, India

The population of snow leopard (Panthera uncia) is declining across their range, due to poaching, habitat fragmentation, retaliatory killing, and a decrease of wild prey species. Obtaining information on rare and cryptic predators living in remote and rugged terrain is important for making conservation and management strategies. We used the Maximum Entropy (MaxEnt) ecological niche modeling framework to predict the potential habitat of snow leopards across the western Himalayan region, India. The model was developed using 34 spatial species occurrence points in the western Himalaya, and 26 parameters including, prey species distribution, temperature, precipitation, land use and land cover (LULC), slope, aspect, terrain ruggedness and altitude. Thirteen variables contributed 98.6% towards predicting the distribution of snow leopards. The area under the curve (AUC) score was high (0.994) for the training data from our model, which indicates predictive ability of the model. The model predicted that there was 42 432 km2 of potential habitat for snow leopards in the western Himalaya region. Protected status was available for 11 247 km2 (26.5%), but the other 31 185 km2 (73.5%) of potential habitat did not have any protected status. Thus, our approach is useful for predicting the distribution and suitable habitats and can focus field surveys in selected areas to save resources, increase survey success, and improve conservation efforts for snow leopards.

Modeling the lumpy skin disease risk probability in central Zagros Mountains of Iran

BackgroundNew Lumpy Skin Disease (LSD) outbreaks are currently circulating in Chaharmahal and Bakhtiari province, (western Iran, in central Zagros Mountains). ObjectivesThe aim of this study was to model the risk probability of LSD in this area. MethodData were collected from veterinary organizations between 2012 and 2016. During this period, 290 outbreaks were registered. The herds were grazing and zero grazing. The average size of herds was 2958. We analyzed the potential for an outbreak of LSD in this area basing on the grid maps with the resolution of 1 km. In this study, 22 environmental variables (19 bioclimatic and 3 topography variables) were used to explore the environmental influences on LSD outbreak by maximum entropy ecological niche modeling (MaxEnt). ResultsThe results showed that mainly the central, northern, northeast and southern parts of Charmahal and Bakhtiari were the most very high risk areas for LSD. The MaxEnt model performed, with an area under the receiver operating characteristic curve (AUC) of 0.977 and 0.972 for training and test data, respectively. It showed high accuracy for predicting the prevalence of LSD (AUC close to 1). The precipitation of coldest season, isothermality and mean temperature of wettest season made the greatest contribution to the model (68.1%). Evaluating the importance of environmental variables, which were derived from the jackknife test, stated the precipitation of the wettest period and the coldest season and isothermality as the bioclimatic variables in explaining LSD prevalence compared to the other variables. ConclusionThe MaxEnt model could be applied to predict the LSD risk probability of occurrence in central Zagros Mountains of Iran based on the current prevalence data of the disease. Also, the model confirmed that coexistence of weather conditions including defined humidity and temperature is necessary for the disease occurrence.

A interface entre saúde, mudanças climáticas e uso do solo no Brasil: uma análise da evolução da produção científica internacional entre 1990 e 2019

Abstract O objetivo deste estudo é analisar a evolução da produção científica internacional sobre a interface entre saúde, mudanças climáticas e uso do solo nas últimas décadas, enfatizando a compreensão da saúde em seu sentido amplo, com destaque às dimensões ambientais, sociais e climáticas, a partir das publicações indexadas na base de dados Scopus. Para alcançar esse objetivo, aplicamos duas metodologias: (1) revisão sistemática da literatura internacional, do tipo descritivo-analítica, incorporando métodos qualitativos e quantitativos; e (2) análise de redes, partindo da categorização da dinâmica de palavras-chave com o uso do software VOSviewer. Aplicando filtros de busca na base de dados, resultaram 283 artigos, dos quais 162 representam a interface entre saúde e mudanças climáticas; 86, entre saúde e uso do solo; 13, entre uso do solo e mudanças climáticas; e, por fim, 22 representaram a intersecção dos três temas. Verifica-se aumento crescente no número de publicações na última década, com destaque aos anos de 2008, 2014 e 2018. Prevalece o uso de metodologias multivariadas, como modelagem de nicho ecológico, modelagem de nicho de entropia máxima, avaliação de ciclo de vida, análise de áreas sentinelas, análise de múltiplos resíduos, sensoriamento remoto e análise de regressão linear, dentre outras, que evidenciam a existência de múltiplos drivers e vulnerabilidades socioambientais ao tratar da relação entre mudanças climáticas, saúde e uso do solo. O maior desafio ao agregar variáveis climáticas, socioambientais e epidemiológicas é a disponibilidade de dados primários e secundários em escala municipal com abrangência nacional e série temporal mínima de 20 anos.

Environmental factors affecting ecological niche of Coccidioides species and spatial dynamics of valley fever in the United States

Coccidioidomycosis is an understudied infectious disease acquired by inhaling fungal spores of Coccidioides species. While historically connected to the southwestern United States, the endemic region for this disease is not well defined. This study's objective was to estimate the impact of climate, soil, elevation and land cover on the Coccidioides species’ ecological niche. This research used maximum entropy ecological niche modeling based on disease case data from 2015 to 2016. Results found mean temperature of the driest quarter, and barren, shrub, and cultivated land covers influential in characterizing the niche. In addition to hotspots in central California and Arizona, the Columbia Plateau ecoregion of Washington and Oregon showed more favorable conditions for fungus presence than surrounding areas. The identification of influential spatial drivers will assist in future modeling efforts, and the potential distribution map generated may aid public health officials in watching for potential hotspots, assessing vulnerability, and refining endemicity.

Spatial distribution ofVachellia karrooin Zimbabwean savannas (southern Africa) under a changing climate

AbstractClimate change projections in southern Africa show a drier and a warmer future climate. It is not yet clear how these changes are going to affect the suitable habitat of bush encroacher woody species in southern African savannas. Maximum Entropy niche modelling technique was used to test the extent to which climate change is likely to affect the suitable habitat ofVachellia karrooin Zimbabwe based on six Global Climate Models (GCMs) from Coupled Model Intercomparison Project Phase 5 (CMIP5) and two Representative Concentration Pathways (RCPs) for the 2070s. An overlay analysis was then performed in a Geographic Information System based on the current and future bioclimatically suitable areas for the respective GCMs and RCPs. This was done to determine the potential effect of climate change on the focal species. Results show that temperature related variables are more important in explaining the spatial distribution ofV. karroothan precipitation related variables. In addition, results indicate an overall increase in the modelled suitable habitat forV.karrooby the 2070s across the GCMs and RCPs considered in this study. Specifically, the suitable habitat ofV.Karroois projected to increase by a maximum of 57,594 km2signifying a 69% increase from the current suitable habitat (83,674 km2). The suitable areas are projected to increase in eastern, western and south eastern parts of Zimbabwe. These results imply that improved understanding of the response of woody species to a changing climate is important for managing bush encroachment in savanna ecosystems.

Environmental suitability for Lutzomyia (Nyssomyia) whitmani (Diptera: Psychodidae: Phlebotominae) and the occurrence of American cutaneous leishmaniasis in Brazil

BackgroundLeishmaniasis represents an important public health problem in Brazil. The continuous process of urbanization and expansion of human activities in forest areas impacts natural habitats, modifying the ecology of some species of Leishmania, as well as its vectors and reservoirs and, consequently, changes the epidemiological pattern that contributes to the expansion of American cutaneous leishmaniasis in Brazil. Here, we discuss Lutzomyia (Nyssomyia) whitmani, the main vector of ACL, transmitting two dermotropic Leishmania species including Leishmania (Viannia) braziliensis and Leishmania (V.) shawi.MethodsWe used the maximum entropy niche modelling approach (MaxEnt) to evaluate the environmental suitability of L. (N.) whitmani and the transmission of ACL in Brazil, in addition to designing models for a future scenario of climate change. MaxEnt was used under the “auto-features” mode and the default settings, with 100-fold repetition (bootstrap). The logistic output was used with higher values in the habitat suitability map, representing more favourable conditions for the occurrence of L. (N.) whitmani and human cases of ACL.ResultsTwo models were developed: the Lutzomyia (N.) whitmani model (LWM) and the American cutaneous leishmaniasis model (ACLM). LWM identified the species “preferential habitat” included regions with moderate annual precipitation (AP) between 1000–1600 mm, intermediate vegetation density (NDVI) values, mean temperature of the coldest quarter (MTCQ), between 15–21 °C, and annual mean temperature (AMT), between 19–24 °C. ACLM indicates that ACL is strongly associated with areas of intermediate density vegetation, areas with AP between 800–1200 mm, MTCQ above 16 °C and AMT below 23 °C.ConclusionsThe models generated for L. (N.) whitmani and ACL indicated a satisfactory predictive capacity. Future projections of LWM indicate an expansion of climatic suitability for L. (N.) whitmani for the northern and southern regions of Brazil. Future projections of ACL indicate the ongoing process of disease expansion in the face of the predicted climatic changes and reinforce the broad geographical expanse of this disease in Brazil. The models were able to identify that a continuous process of environmental degradation favours the establishment of L. (N.) whitmani and the occurrence of ACL by a strong association of the vector(s) and ACL to areas of intermediate vegetation cover density.

The Distribution and Management of Two Invasive Pests of Eucalyptus: The Red Gum Lerp Psyllid, Glycaspis brimblecombei (Hemiptera: Psylloidae), and the Blue Gum Chalcid Wasp, Leptocybe invasa (Hymenoptera: Eulophidae), in Zimbabwe

Eucalyptus species are indigenous to Australia but arenowgrown worldwide due to their fast growth rate and various uses as timber and fuel wood. Insect pests of Eucalyptus have since followed their host and, in most cases, leaving behind the natural enemies which usually regulate them below economic injury. This is the case with Glycaspis brimblecombei and Leptocybe invasa which are now resident in most parts of the world including Zimbabwe. Damage as a result of the two pests currently poses a threat to reforestation efforts to provide alternative sources of firewood for curing tobacco. The objective of this study was to determine the distribution of the two pests as well as assess the possibility of managing L. invasa through biological control by releasing and recovering successive generations of the natural enemy Selitrichodes neseri in selected L. invasa-infested areas. Surveys were therefore carried out in Zimbabwe and GPS coordinates for pest presence recorded and used to determine the current distribution and future projections of the two pests using Maximum Entropy (maxent) ecological niche modelling. In preliminary studies to manage L. invasa, the natural wasp enemy S. neseri was released in Eucalyptus plantations and recovery studies done to establish their perpetuation in the field. Based on temperature and precipitation averages for Zimbabwe, the model predicted widespread distribution of the two pests especially in Mashonaland West, Bulawayo, Harare, Midlands province and parts of Manicaland province. This predicted range was projected to shrink due to climate change by the year 2055. In terms of relative contribution in predicting the distribution of the occurrence data, the three most important variables were mean annual temperature (39 %), mean temperature coolest month (18.3%)and annual moisture index (18 %). The performance of the model was high, with an AUC value of 0.884. Selitrichodes neseri wasps were recovered in infested Eucalyptus samples 4–6 generations after the initial release, indicating a high possibility of the natural enemy being able to establish in the future. Our findings are therefore important in understanding the current and projected distribution of both L. invasa and G. brimblecombei in Zimbabwe and formulating management measures for the two pests.

On the absence of the Green-tailed Trainbearer Lesbia nuna (Trochilidae) from Venezuela: an analysis based on environmental niche modelling.

BackgroundLesbia nuna, a hummingbird distributed in the tropical Andes, has been included in Venezuela's bird list on the basis of a specimen collected in 1873 at Sierra Nevada, Mérida and deposited in the Natural History Museum, London, with no further records for this country since then. This record, largely considered as valid by most authors, has been questioned by others, although without formal analyses.New informationThe potential habitat range of the Green-Tailed Trainbearer, Lesbia nuna gouldii (Trochilidae), in the northern Andes from Ecuador to Venezuela was modelled, using maximum entropy niche modelling, environmental covariates and records from locations across the Colombian Andes. The predicted suitable habitat range corresponded well to the known range of the subspecies L. n. gouldii in Colombia and clearly excluded Sierra Nevada. Therefore, these analyses suggest that this species should be removed from the Venezuelan bird list.

Potential Distribution ofDrosophila suzukii(Diptera: Drosophilidae) in Relation to Alternate Hosts in Mexico

Abstract The spotted wing drosophila, Drosophila suzukii (Matsumura) (Diptera: Drosophilidae), is one of the most important pests of berry crop production in Mexico. The purpose of this research was to model the potential distribution of D. suzukii in the Mexico relative to 4 non-crop hosts using Maximum Entropy Ecological Niche Modeling. Spotted wing drosophila records were collected from a survey conducted in commercial blackberry plots and non-cultivated areas between 2013–2015. The data for the presence of non-crop hosts in the country and the bioclimatic variables used in the modeling were obtained from the Global Biodiversity Information Facility and WorldClim websites, respectively. For climatic variable selection, a principal component analysis on climatic variables was conducted prior to the MaxEnt modeling. The results demonstrate that the potential distribution of spotted wing drosophila was primarily in central Mexico. However, other suitable locations in the southeastern portion of the county...

Distribution of the isopod Excirolana braziliensis on sandy beaches of the Atlantic and Pacific Oceans

MEPS Marine Ecology Progress Series Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsTheme Sections MEPS 583:137-148 (2017) - DOI: https://doi.org/10.3354/meps12333 Distribution of the isopod Excirolana braziliensis on sandy beaches of the Atlantic and Pacific Oceans Gastón Martínez1,2,*, Matías Arim1,2, Omar Defeo1,2 1Centro Universitario de la Región Este (CURE), Universidad de la República, Ruta 9 y Ruta 15, PC 27000 Rocha, Uruguay 2Departamento de Ecología y Evolución, Facultad de Ciencias, Universidad de la República, PC 11400 Montevideo, Uruguay *Corresponding author: gmartinez@cure.edu.uy ABSTRACT: We assessed geographic patterns of abundance of the isopod Excirolana braziliensis across its whole distribution range in the context of the abundant centre hypothesis (ACH). We also evaluated auxiliary hypotheses to the ACH involving habitat availability and suitability. We compiled species abundance and occurrence information on 139 Pacific and Atlantic sandy beaches of the Americas. Abundance patterns were contrasted against 5 hypothetical distribution models. Habitat availability (sandy beach along the coast), and the role played by grain size on isopod abundance were analysed. Maximum entropy niche modelling based on primary production, salinity, water temperature and tidal range data was used to estimate trends in habitat suitability. E. braziliensis abundance peaked at the 2 edges of its range on the Atlantic coast and towards the centre of its range on the Pacific coast. Congruently, the niche model predicted very low habitat suitability at the centre of the species’ range on the Atlantic coast. Primary production was the main contribution to the model (74.8%). The highest abundances were found in fine sediments (0.20 mm). Support for the ACH for E. braziliensis was found only for the Pacific coast, whereas habitat suitability and availability together with local in-beach morphodynamics accounted for deviations from ACH predictions in the Atlantic. The highest abundances registered in upwelling areas and on beaches with fine sands highlight the primary role played by regional and local conditions over geographic location. KEY WORDS: Abundant-centre hypothesis · Habitat availability · Primary production · Salinity · Sandy beaches · Surface water temperature Full text in pdf format Supplementary materialSee Comment and Reply Comment on this article PreviousNextCite this article as: Martínez G, Arim M, Defeo O (2017) Distribution of the isopod Excirolana braziliensis on sandy beaches of the Atlantic and Pacific Oceans. Mar Ecol Prog Ser 583:137-148. https://doi.org/10.3354/meps12333 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in MEPS Vol. 583. Online publication date: November 16, 2017 Print ISSN: 0171-8630; Online ISSN: 1616-1599 Copyright © 2017 Inter-Research.

Predicting the current potential and future world wide distribution of the onion maggot, Delia antiqua using maximum entropy ecological niche modeling.

Climate change will markedly impact biology, population ecology, and spatial distribution patterns of insect pests because of the influence of future greenhouse effects on insect development and population dynamics. Onion maggot, Delia antiqua, larvae are subterranean pests with limited mobility, that directly feed on bulbs of Allium sp. and render them completely unmarketable. Modeling the spatial distribution of such a widespread and damaging pest is crucial not only to identify current potentially suitable climactic areas but also to predict where the pest is likely to spread in the future so that appropriate monitoring and management programs can be developed. In this study, Maximum Entropy Niche Modeling was used to estimate the current potential distribution of D. antiqua and to predict the future distribution of this species in 2030, 2050, 2070 and 2080 by using emission scenario (A2) with 7 climate variables. The results of this study show that currently highly suitable habitats for D.antiqua occur throughout most of East Asia, some regions of North America, Western Europe, and Western Asian countries near the Caspian sea and Black Sea. In the future, we predict an even broader distribution of this pest spread more extensively throughout Asia, North America and Europe, particularly in most of European countries, Central regions of United States and much of East Asia. Our present day and future predictions can enhance strategic planning of agricultural organizations by identifying regions that will need to develop Integrated Pest Management programs to manage the onion maggot. The distribution forecasts will also help governments to optimize economic investments in management programs for this pest by identifying regions that are or will become less suitable for current and future infestations.

Wind conditions facilitate the seasonal water‐crossing behaviour of Oriental Honey‐buzzards Pernis ptilorhynchus over the East China Sea

Migratory raptors rarely fly over stretches of water larger than 25 km, although different species undertake water crossings of varying lengths, depending mainly on their wing morphology. Oriental Honey‐buzzards fly c. 680 km over the East China Sea in autumn from breeding areas in Japan to wintering areas in Southeast Asia, but avoid this long water crossing in spring. We investigated the effects of weather on this exceptional migratory behaviour and its seasonality through a maximum entropy niche modelling approach. We used data collected through satellite tracking of 31 adult birds as presence points and a set of variables related to wind, precipitation and convective condition as environmental predictors. Results of modelling showed very different, almost non‐overlapping, areas suitable for migration over the East China Sea region in autumn and spring. Suitable migration routes in autumn mostly occurred over the sea, whereas suitable areas for spring migration mostly occurred over land, suggesting that circumnavigating the East China Sea is preferable in spring. At the regional scale, wind conditions facilitate water‐crossing behaviour of Oriental Honey‐buzzards in autumn, but not in spring. Specifically, suitable tailwinds over the sea enable water‐crossing in autumn, whereas in spring, wind support and convective conditions are best over land. Our modelling did not suggest any importance of convective conditions for autumn migration. However, we expect that at smaller temporal scales, convective conditions would be a considerable facilitator of the water‐crossing behaviour in this species.

Predicting the potential environmental suitability for Theileria orientalis transmission in New Zealand cattle using maximum entropy niche modelling

The tick-borne haemoparasite Theileria orientalis is the most important infectious cause of anaemia in New Zealand cattle. Since 2012 a previously unrecorded type, T. orientalis type 2 (Ikeda), has been associated with disease outbreaks of anaemia, lethargy, jaundice and deaths on over 1000 New Zealand cattle farms, with most of the affected farms found in the upper North Island. The aim of this study was to model the relative environmental suitability for T. orientalis transmission throughout New Zealand, to predict the proportion of cattle farms potentially suitable for active T. orientalis infection by region, island and the whole of New Zealand and to estimate the average relative environmental suitability per farm by region, island and the whole of New Zealand.The relative environmental suitability for T. orientalis transmission was estimated using the Maxent (maximum entropy) modelling program. The Maxent model predicted that 99% of North Island cattle farms (n=36,257), 64% South Island cattle farms (n=15,542) and 89% of New Zealand cattle farms overall (n=51,799) could potentially be suitable for T. orientalis transmission. The average relative environmental suitability of T. orientalis transmission at the farm level was 0.34 in the North Island, 0.02 in the South Island and 0.24 overall.The study showed that the potential spatial distribution of T. orientalis environmental suitability was much greater than presumed in the early part of the Theileria associated bovine anaemia (TABA) epidemic. Maximum entropy offers a computer efficient method of modelling the probability of habitat suitability for an arthropod vectored disease. This model could help estimate the boundaries of the endemically stable and endemically unstable areas for T. orientalis transmission within New Zealand and be of considerable value in informing practitioner and farmer biosecurity decisions in these respective areas.

The Use of Spatial and Spatiotemporal Modeling for Surveillance of H5N1 Highly Pathogenic Avian Influenza in Poultry in the Middle East.

Since 2005, H5N1 highly pathogenic avian influenza virus (HPAIV) has severely impacted the economy and public health in the Middle East (ME) with Egypt as the most affected country. Understanding the high-risk areas and spatiotemporal distribution of the H5N1 HPAIV in poultry is prerequisite for establishing risk-based surveillance activities at a regional level in the ME. Here, we aimed to predict the geographic range of H5N1 HPAIV outbreaks in poultry in the ME using a set of environmental variables and to investigate the spatiotemporal clustering of outbreaks in the region. Data from the ME for the period 2005-14 were analyzed using maximum entropy ecological niche modeling and the permutation model of the scan statistics. The predicted range of high-risk areas (P > 0.60) for H5N1 HPAIV in poultry included parts of the ME northeastern countries, whereas the Egyptian Nile delta and valley were estimated to be the most suitable locations for occurrence of H5N1 HPAIV outbreaks. The most important environmental predictor that contributed to risk for H5N1 HPAIV was the precipitation of the warmest quarter (47.2%), followed by the type of global livestock production system (18.1%). Most significant spatiotemporal clusters (P < 0.001) were detected in Egypt, Turkey, Kuwait, Saudi Arabia, and Sudan. Results suggest that more information related to poultry holding demographics is needed to further improve prediction of risk for H5N1 HPAIV in the ME, whereas the methodology presented here may be useful in guiding the design of surveillance programs and in identifying areas in which underreporting may have occurred.

Spatial and Temporal Epidemiology of Lumpy Skin Disease in the Middle East, 2012-2015.

Lumpy skin disease virus (LSDV) is an infectious disease of cattle that can have severe economic implications. New LSD outbreaks are currently circulating in the Middle East (ME). Since 2012, severe outbreaks were reported in cattle across the region. Characterizing the spatial and temporal dynamics of LSDV in cattle populations is prerequisite for guiding successful surveillance and control efforts at a regional level in the ME. Here, we aim to model the ecological niche of LSDV and identify epidemic progression patterns over the course of the epidemic. We analyzed publically available outbreak data from the ME for the period 2012–2015 using presence-only maximum entropy ecological niche modeling and the time-dependent method for the estimation of the effective reproductive number (R-TD). High-risk areas (probability >0.60) for LSDV identified by ecological niche modeling included parts of many northeastern ME countries, though Israel and Turkey were estimated to be the most suitable locations for occurrence of LSDV outbreaks. The most important environmental predictors that contributed to the ecological niche of LSDV included annual precipitation, land cover, mean diurnal range, type of livestock production system, and global livestock densities. Average monthly effective R-TD was equal to 2.2 (95% CI: 1.2, 3.5), whereas the largest R-TD was estimated in Israel (R-TD = 22.2, 95 CI: 15.2, 31.5) in September 2013, which indicated that the demographic and environmental conditions during this period were suitable to LSDV super-spreading events. The sharp drop of Isreal’s inferred R-TD in the following month reflected the success of their 2013 vaccination campaign in controlling the disease. Our results identified areas in which underreporting of LSDV outbreaks may have occurred. More epidemiological information related to cattle populations are needed to further improve the inferred spatial and temporal characteristics of currently circulating LSDV. However, the methodology presented here may be useful in guiding the design of risk-based surveillance and control programs in the region as well as aid in the formulation of epidemic preparedness plans in neighboring LSDV-free countries.

Using Ecological Niche Modeling for Biodiversity Conservation Guidance in the Western Podillya (Ukraine): Reptiles

Abstract Using Ecological Niche Modeling for Biodiversity Conservation Guidance in the Western Podillya (Ukraine): Reptiles. Tytar, V., Sobolenko, L., Nekrasova, O. Mezhzherin, S. - Maximum entropy niche modeling was employed as a tool to assess potential habitat suitability for 10 reptile species and to map their potential distribution in the Western Podillya (Ukraine). We used climate, topography and human impact (assessed by the Human Footprint) as predictor variables. “Isothermality”, “temperature seasonality” and the “mean temperature of coldest month” were three most important factors in predicting habitat suitability and distribution. A profound contribution to the modeling has been displayed by the Human Footprint, meaning that human infrastructure may benefit reptile species. Areas have been distinguished that in the first place should be of interest to biodiversity conservationists targeting reptiles and maps summarizing predicted habitat suitability and species richness were produced for guiding conservation efforts.