Lumbriculus variegatus (Müller, 1774) (Oligochaeta, Lumbriculidae) in Campos do Jordão State Park, São Paulo, Brazil

The aim of this paper was recording the occurrence of the species Lumbriculus variegatus (Müller, 1774) (Oligochaeta, Lumbriculidae) in lotic systems of the State of São Paulo. Specimens were collected in Sapucaí River, located in Campos do Jordão State Park. The mapping of geographical distribution of this species is of interest to public health since L. variegatus may be an intermediate host of Dioctophyme renale (Goeze, 1782) (Nematoda, Dioctophymatidae), a parasite of recognized zoonotic potential. Distribution data serves as a basis for environmental monitoring and evaluation, being essential to map possible cases of the disease (Dioctophimosis) and provide information to health professionals.

Study on the Potential Distribution of Leptinotarsa decemlineata and Its Natural Enemy Picromerus bidens Under Climate Change

The Colorado potato beetle (CPB), scientifically known as Leptinotarsa decemlineata, is a destructive quarantine pest that has invaded more than 40 countries and regions worldwide. It causes a 20–100% reduction in plant production, leading to severe economic losses. Picromerus bidens L. is a predatory insect that preys on CPB. This study used the MaxEnt model to predict the current and future potential distribution areas of CPB and P. bidens under different climatic scenarios to determine the possibility of using P. bidens as a natural enemy to control CPB. The possible introduction routes of CPB and P. bidens were subsequently predicted by combining their potential distribution with the current distribution of airports and ports. Notably, the potential distribution area of P. bidens was similar to that of CPB, suggesting that P. bidens could be used as a natural enemy to control CPB. Future changes in the suitable growth areas of CPB under different climate scenarios increased and decreased but were insignificant, while those of P. bidens decreased. Consequently, a reduction of the suitable habitats of P. bidens may cause a decrease in its population density, leading to a lack of adequate and timely prevention and control of invasive pests. Active measures should thus be enacted to minimize global warming and protect biodiversity. This study provides a theoretical basis and data support for early warning, monitoring, and control of the CPB spread.

Assessing the Impact of Climate Change on Potential Distribution of Meconopsis punicea and Its Influence on Ecosystem Services Supply in the Southeastern Margin of Qinghai-Tibet Plateau

Meconopsis punicea is an iconic ornamental and medicinal plant whose natural habitat has degraded under global climate change, posing a serious threat to the future survival of the species. Therefore, it is critical to analyze the influence of climate change on possible distribution of M. punicea for conservation and sustainable utilization of this species. In this study, we used MaxEnt ecological niche modeling to predict the potential distribution of M. punicea under current and future climate scenarios in the southeastern margin region of Qinghai-Tibet Plateau. Model projections under current climate show that 16.8% of the study area is suitable habitat for Meconopsis. However, future projections indicate a sharp decline in potential habitat for 2050 and 2070 climate change scenarios. Soil type was the most important environmental variable in determining the habitat suitability of M. punicea, with 27.75% contribution to model output. Temperature seasonality (16.41%), precipitation of warmest quarter (14.01%), and precipitation of wettest month (13.02%), precipitation seasonality (9.41%) and annual temperature range (9.24%) also made significant contributions to model output. The mean elevation of suitable habitat for distribution of M. punicea is also likely to shift upward in most future climate change scenarios. This study provides vital information for the protection and sustainable use of medicinal species like M. punicea in the context of global environmental change. Our findings can aid in developing rational, broad-scale adaptation strategies for conservation and management for ecosystem services, in light of future climate changes.

Forest tree species distribution for Europe 2000-2020: mapping potential and realized distributions using spatiotemporal Machine Learning

Paper describes a data-driven framework based on spatio-temporal ensemble machine learning to produce distribution maps for 16 forest tree species (Abies alba Mill., Castanea sativa Mill. , Corylus avellana L., Fagus sylvatica L., Olea europaea L., Picea abies L. H. Karst., Pinus halepensis Mill., Pinus nigra J. F. Arnold, Pinus pinea L., Pinus sylvestris L., Prunus avium L., Quercus cerris L., Quercus ilex L., Quercus robur L., Quercus suber L. and Salix caprea L.) at high spatial resolution (30 m). Tree occurrence data for a total of 3 million of points was used to train different Machine Learning (ML) algorithms: random forest, gradient-boosted trees, generalized linear models, k-nearest neighbors, CART and an artificial neural network. A stack of 585 coarse and high resolution covariates representing spectral reflectance (Landsat bands, spectral indices; time-series of seasonal composites), different biophysical conditions (i.e. temperature, precipitation, elevation, lithology) and biotic competition (other species distribution maps) was used as predictors for realized distributions, while potential distribution was modelled with environmental predictors only. Logloss and computing time were used to select the three best algorithms to train an ensemble model based on stacking with a logistic regressor as a meta-learner for each species. High resolution (30 m) probability and model uncertainty maps of realized distribution were produced for each species using a time window of 4 years for a total of 6 distribution maps per species for the studied period, while for potential distributions only one map per species was produced. Results of spatial cross validation show that Olea europaea and Quercus suber achieved the best performances in both potential and realized distribution, while Pinus sylvestris and Salix caprea achieved the worst. Further analysis shows that fine-resolution models consistently outperformed coarse resolution models (250 m) for realized distribution (average decrease in logloss: +53%). Realized distribution models achieved higher predictive performances than potential distribution ones. Importance of predictor variables differed across species and models, with the green band for summer and the NDWI and NDVI for fall for realized distribution and the diffuse irradiation and precipitation of the driest quarter being the most important and frequent for potential distribution. The ensemble model outperformed or performed as good as the best individual model in all potential species distributions, while for ten species it performed worse than the best individual model in modeling realized distributions. The framework shows how combining continuous and consistent EO time series data with state of the art ML can be used to derive dynamic distribution maps. The produced time-series occurrence predictions can be used to quantify temporal trends and detect potential forest degradation.

Predicting Current Potential Distribution and the Range Dynamics of Pomacea canaliculata in China under Global Climate Change

Pomacea canaliculata is one of the 100 worst invasive alien species in the world, which has significant effects and harm to native species, ecological environment, human health, and social economy. Climate change is one of the major causes of species range shifts. With recent climate change, the distribution of P. canaliculata has shifted northward. Understanding the potential distribution under current and future climate conditions will aid in the management of the risk of its invasion and spread. Here, we used species distribution modeling (SDM) methods to predict the potential distribution of P. canaliculata in China, and the jackknife test was used to assess the importance of environmental variables for modeling. Our study found that precipitation of the warmest quarter and maximum temperature in the coldest months played important roles in the distribution of P. canaliculata. With global warming, there will be a trend of expansion and northward movement in the future. This study could provide recommendations for the management and prevention of snail invasion and expansion.

Presence and potential distribution of malaria-infected New World primates of Costa Rica

Background In South and Central America, Plasmodium malariae/Plasmodium brasilianum, Plasmodium vivax, Plasmodium simium, and Plasmodium falciparum has been reported in New World primates (NWP). Specifically in Costa Rica, the presence of monkeys positive to P. malariae/P brasilianum has been identified in both captivity and in the wild. The aim of the present study was to determine the presence of P. brasilianum, P. falciparum, and P. vivax, and the potential distribution of these parasites-infecting NWP from Costa Rica. Methods The locations with PCR (Polymerase Chain Reaction) positive results and bioclimatic predictors were used to construct ecological niche models based on a modelling environment that uses the Maxent algorithm, named kuenm, capable to manage diverse settings to better estimate the potential distributions and uncertainty indices of the potential distribution. Results PCR analysis for the Plasmodium presence was conducted in 384 samples of four primates (Howler monkey [n = 130], White-face monkey [n = 132], Squirrel monkey [n = 50], and red spider monkey [n = 72]), from across Costa Rica. Three Plasmodium species were detected in all primate species (P. falciparum, P. malariae/P. brasilianum, and P. vivax). Overall, the infection prevalence was 8.9%, but each Plasmodium species ranged 2.1–3.4%. The niche model approach showed that the Pacific and the Atlantic coastal regions of Costa Rica presented suitable climatic conditions for parasite infections. However, the central pacific coast has a more trustable prediction for malaria in primates. Conclusions The results indicate that the regions with higher suitability for Plasmodium transmission in NWP coincide with regions where most human cases have been reported. These regions were also previously identified as areas with high suitability for vector species, suggesting that enzootic and epizootic cycles occur.

Climate Change Impacts on the Potential Distribution of Apocheima cinerarius (Erschoff) (Lepidoptera: Geometridae)

Among the impacts of ongoing and projected climate change are shifts in the distribution and severity of insect pests. Projecting those impacts is necessary to ensure effective pest management in the future. Apocheima cinerarius (Erschoff) (Lepidoptera: Geometridae) is an important polyphagous forest pest in China where causes huge economic and ecological losses in 20 provinces. Under historical climatic conditions, the suitable areas for A. cinerarius in China are mainly in the northern temperate zone (30–50° N) and the southern temperate zone (20–60° S). Using the CLIMEX model, the potential distribution of the pest in China and globally, both historically and under climate change, were estimated. Suitable habitats for A. cinerarius occur in parts of all continents. With climate change, its potential distribution extends northward in China and generally elsewhere in the northern hemisphere, although effects vary depending on latitude. In other areas of the world, some habitats become less suitable for the species. Based on the simulated growth index in CLIMEX, the onset of A. cinerarius would be earlier under climate change in some of its potential range, including Spain and Korea. Measures should anticipate the need for prevention and control of A. cinerarius in its potential extended range in China and globally.

Method to Predict the Non-Uniform Potential Distribution in Random Electrical Machine Windings under Pulse Voltage Stress

This article describes a practical method for predicting the distribution of electric potential inside an electrical machine’s winding based on design data. It broadens the understanding of winding impedance in terms of inter-winding behavior and allows to properly design an electrical machine’s insulation system during the development phase. The predictions are made based on an frequency-dependent equivalent circuit of the electrical machine which is validated by measurements in the time domain and the frequency domain. Element parameters for the equivalent circuit are derived from two-dimensional field simulations. The results demonstrate a non-uniform potential distribution and demonstrate that the potential difference between individual turns and between turns and the stator core exceeds the expected values. The findings also show a link between winding impedance and potential oscillations inside the winding. Additionally, the article provides an overview of the chronological progression of turn-based models and shows how asynchronous multiprocessing is used to accelerate the solution process of the equivalent circuit.

Predicting potential distribution and evaluating biotic interactions of threatened species: a case study of Discocactus ferricola (Cactaceae)

Information on distribution, number of populations, and biotic interactions are essential for assessing the threat status of species and to establish more effective conservation initiatives. Ecological niche modeling have been successfully applied to identify the potential distribution, even for rare species that have few recorded occurrence points. In this study, we evaluated the potential distribution and additionally generated the first data on the reproductive biology of Discocactus ferricola, due to its degree of threat and the absence of ecological data for that species. The potential distribution map highlighted areas with higher probability of occurrence of D. ferricola on the Residual Plateau of Maciço do Urucum located in Mato Grosso do Sul, Brazil. The occurrence of D. ferricola populations was limited to outcrops of flat ironstone (cangas) distributed in patches across the landscape, increasing the chances of serious threats, such as habitat loss due to mining and species extraction. We also found that D. ferricola is xenogamous. Therefore, in situ conservation actions must prioritize the maintenance of interactions with pollinators by preserving the flora and fauna of rocky outcrops and adjacent forests in areas of greater environmental suitability for D. ferricola. Our study highlights the use of ecological niche modeling and data on biotic interactions to evaluate species potential distribution, to guide new sampling efforts, and to assist conservation and management initiatives.