Host-parasite biogeographic interactions: Modelling the distribution of Phyllotis xanthopygus rodents complex and their flea assemblage using the favourability function.

We modelled the distributions of two toads (Bufo bufo and Epidalea calamita) in the Iberian Peninsula using the favourability function, which makes predictions directly comparable for different species and allows fuzzy logic operations to relate different models. The fuzzy intersection between individual models, representing favourability for the presence of both species simultaneously, was compared with another favourability model built on the presences shared by both species. The fuzzy union between individual models, representing favourability for the presence of any of the two species, was compared with another favourability model based on the presences of either or both of them. The fuzzy intersections between favourability for each species and the complementary of favourability for the other (corresponding to the logical operation “A and not B”) were compared with models of exclusive presence of one species versus the exclusive presence of the other. The results of modelling combined species data were highly similar to those of fuzzy logic operations between individual models, proving fuzzy logic and the favourability function valuable for comparative distribution modelling. We highlight several advantages of fuzzy logic over other forms of combining distribution models, including the possibility to combine multiple species models for management and conservation planning.

BackgroundOver the last decade, reports about dengue cases have increase worldwide, which is particularly worrisome in South America due to the historic record of dengue outbreaks from the seventeenth century until the first half of the twentieth century. Dengue is a viral disease that involves insect vectors, namely Aedes aegypti and Ae. albopictus, which implies that, to prevent and combat outbreaks, it is necessary to understand the set of ecological and biogeographical factors affecting both the vector species and the virus.MethodsWe contribute with a methodology based on fuzzy logic that is helpful to disentangle the main factors that determine favorable environmental conditions for vectors and diseases. Using favorability functions as fuzzy logic modelling technique and the fuzzy intersection, union and inclusion as fuzzy operators, we were able to specify the territories at biogeographical risk of dengue outbreaks in South America.ResultsOur results indicate that the distribution of Ae. aegypti mostly encompasses the biogeographical framework of dengue in South America, which suggests that this species is the principal vector responsible for the geographical extent of dengue cases in the continent. Nevertheless, the intersection between the favorability for dengue cases and the union of the favorability for any of the vector species provided a comprehensive map of the biogeographical risk for dengue.ConclusionsFuzzy logic is an appropriate conceptual and operational tool to tackle the nuances of the vector-illness biogeographical interaction. The application of fuzzy logic may be useful in decision-making by the public health authorities to prevent, control and mitigate vector-borne diseases.

Understanding the invasion of the macroalga Rugulopteryx okamurae (Ochrophyta) in the northern Alboran Sea through the use of biogeographic models

ABSTRACTAimBeta diversity is essential for understanding how biological communities change along environmental gradients. Here we examined the taxonomic, phylogenetic and functional beta diversity patterns of sigmodontine rodents. We tested the influence of geographic distance and three environmental hypotheses: (1) water availability and productivity, (2) energy availability and (3) climatic stability, interpreting them through the lens of beta diversity and its components.LocationNorthwestern Argentina (NWA).TaxonSigmodontinae (Rodentia, Cricetidae).MethodsWe compiled a comprehensive museum‐based specimen database complemented with bibliographic records and field‐based surveys, resulting in 44 species of sigmodontines from 330 localities in NWA. For each pair of sites, we calculated beta diversity and partitioned it into turnover (substitution of species) and nestedness (difference in species richness). Then, we used multiple regression on distance matrices to test the influence of geographical and environmental variables on total beta diversity and its components on the taxonomic, phylogenetic and functional dimensions.ResultsWe found that turnover contributed more to total beta diversity than nestedness for all dimensions but to a larger degree for taxonomic than phylogenetic and functional dimensions. Elevation was the predictor with the highest explanatory value for total taxonomic beta diversity with an inverse relationship. Solar radiation and the minimum temperature of the coldest month emerged as the main predictors for total phylogenetic and functional beta diversity, respectively, also with an inverse relationship. Among the environmental hypotheses, energy availability had the highest explanatory power. When mapping the variation of beta diversity for the three measured dimensions, we found an abrupt shift between the eastern lowlands and the western highlands, coincident with the South American Transition Zone, where the Andean and Neotropical biogeographic regions meet.Main ConclusionsThese findings highlight the importance of thermal and solar radiation gradients as key drivers of beta diversity in sigmodontine rodents. Our study provides novel insights into the environmental drivers shaping rodent beta diversity on three different dimensions (taxonomic, phylogenetic and functional) in complex landscapes, emphasising the importance of examining multiple dimensions in biodiversity studies.

Climate change influences the distribution of mangroves towards tropical or temperate regions of the world. We hypothesized that Rhizophora species organized along complex spatial and temporal temperature and precipitation gradient. To determine the affinity of different mangroves with climatic parameters, the response of eight Rhizophora species to seven climatic parameters (i.e., annual mean temperature, annual precipitation, maximum temperature of warmest month, minimum temperature of coldest month, temperature annual range and temperature of driest month and precipitation of warmest month) was analyzed with Arc GIS and Maxent software. For temperature and precipitation there was significant difference (p<0.001) among species location. Only R. selala (p<0.001) differed most from the rest taxa in temperature. The jackknife test in Maxent revealed that minimum temperature of coldest month (regularized training gain ~0.71), temperature annual range, (regularized training gain ~0.66) and annual mean temperature (regularized training gain ~0.36) were the most important environmental parameters that determine the occurrence of R. mangle, being the most dominant species. This outcome was further validated by an accuracy of 91%. This implies thattemperature was a better predictive parameter than precipitation in the distribution of R. mangle.

Since the introduction of the first digital-based fuzzy logic controller chip, efficient hardware design of fuzzy logic control systems (FLCS) has drawn substantial attention. The interest in fuzzy logic hardware systems is motivated by the desperate need to provide fast fuzzy logic-based systems capable of operating in real time process control conditions. Fuzzy logic hardware implementation problems can be classified into two basic categories: the digital approach and the analog approach. The digital approach was originated by Togai and Watanabe who developed the first digital fuzzy logic-based inference engine chip. However, the digital approach to the fuzzy logic hardware implementation seems to be less efficient in contrast to analog, especially when the complexity and speed of a control problem are crucial. The transformation of a real-world fuzzy data into a binary format requires tremendous processing power that must be provided in the real time. Therefore, the analog solution offers a sufficient strategy to solve fuzzy logic control problems in dedicated hardware. Recently, successful implementation of current mode fuzzy logic controller developed in CMOS technology was reported. This approach starts with the theoretic framework for fuzzy set operations that leads to the coherent representation of the fuzzy inference operations, including fuzzification and defuzzification. The proposed approach, utilizing the control strategy proposed by Mamdani, concentrates on the algebraic correctness and elegance. It is algebraically effective but it lacks the current mode circuit implementation insight. This drawback motivated the presented research. This paper presents a graph-oriented approach to the synthesis of fuzzy logic building blocks. The framework for synthesis of current-mode fuzzy logic circuits is derived and the graph representations of basic building blocks are developed. These blocks comprise the bounded difference circuit, the absolute difference circuit, the minimum circuit, the maximum circuit, and the membership function circuit. Thereafter, the circuit implementations are analyzed and the circuit implementation issues related to the accuracy of the fuzzy operations are discussed. >

Decision-making systems are an integral part of any autonomous device. With the recent developments in bio-nanorobots, smart drugs, and engineered viruses, there is an immediate need of decision-making systems which are bio-compatible in nature. DNA is considered a perfect candidate for designing the computing systems in such decision-making systems because of their bio-compatibility and programmability. Complex biological systems can be easily modeled/controlled using fuzzy logic operations with the help of linguistic rules. In this paper, we propose an enzyme-free DNA strand displacement-based architecture of fuzzy inference engine using the fuzzy operators, such as fuzzy intersection and union. The basic building blocks of this architecture are minimum, maximum, and fan-out gates. All these gates are analog in nature, which means that the input/output values of the gates are represented by the concentration of the input/output DNA strands. To demonstrate the performance of the proposed architecture, a detailed design, analysis, and kinetic simulation of each gate were carried out. Finally, the minimum and maximum gates are cascaded according to the pre-defined rules to design the fuzzy inference engine. All these DNA circuits are implemented and simulated in Visual DSD software.

Phytolacca americana, introduced to China in the 20th century for its medicinal properties, has posed a significant ecological and agricultural challenge. Its prolific fruit production, high reproductive coefficient, adaptability, and toxic roots and fruits have led to the formation of monoculture communities, reducing native species diversity and posing threats to agriculture, human and animal health, and local ecosystems. Understanding its potential distribution patterns at a regional scale and its response to climate change is essential for effective monitoring, management, and control. In this study, we utilized the Maxent model to simulate potential habitat areas of P. americana across three timeframes (current, 2050s, and 2070s) under three climate change scenarios (SSP126, SSP245, and SSP585). Leveraging data from 556 P. americana sites across China, we employed ROC curves to assess the prediction accuracy. Our findings highlight key environmental factors influencing P. americana's geographical distribution, including the driest month's precipitation, the coldest month's minimum temperature, the wettest month's precipitation, isothermality, and temperature annual range. Under current climate conditions, P. americana potentially inhabits 280.26 × 104 km2 in China, with a concentration in 27 provinces and cities within the Yangtze River basin and its southern regions. While future climate change scenarios do not drastically alter the total suitable area, the proportions of high and low-suitability areas decrease over time, shifting towards moderate suitability. Specifically, in the SSP126 scenario, the centroid of the predicted suitable area shifts northeastward and then southwestward. In contrast, in the SSP245 and SSP585 scenarios, the centroid shifts northward.

Este estudo teve como objetivos avaliar a similaridade florística do componente arbóreo de 39 remanescentes de florestas superomontanas no domínio atlântico, Brasil, e analisar a influência de variáveis geográficas e climáticas sobre os padrões observados. Foi utilizada uma matriz binária de presença e ausência das espécies arbóreas compiladas dos 39 levantamentos florísticos e fitossociológicos. Para conhecer a relação da composição florística das áreas com variáveis ambientais e espaciais, foram extraídas as coordenadas geográficas e os dados climáticos de cada área. Com o objetivo de avaliar a similaridade florística dos remanescentes, foi utilizado um dendrograma e, para determinar a influência de variáveis ambientais e espaciais sobre os padrões florísticos, foi utilizada a análise multivariada NMDS. O dendrograma e a NMDS demonstraram a formação de agrupamentos, predominantemente entre remanescentes localizados em uma mesma unidade fitogeográfica. Observou-se a existência de um gradiente ambiental ligado às condições climáticas. Em áreas com maiores valores de sazonalidade térmica, amplitude térmica anual, precipitação, latitude e longitude, ocorreram florestas superomontanas com matriz ombrófila e, em áreas com maiores valores de temperatura média, amplitude térmica diária, isotermalidade, sazonalidade da precipitação e temperatura mínima no mês mais frio, ocorreram predominantemente florestas com matriz estacional.

Introduction Forsythia suspensa (Thunb.) Vahl,a pharmacopoeial medicinal plant,is valued for its therapeutic efficacy in clearing heat and detoxifying, dispelling wind-heat, and promoting blood circulation to resolve stasis. Phenolic acids, ubiquitous secondary metabolites in F. suspensa , are critically linked to pharmacological activities and exhibit diverse biological functions.It is therefore of significant interest to investigate whether environmental changes also alter the content distribution of phenolic acids in F. suspensa . Methods To elucidate the chemical diversity and ecological drivers of its bioactive compounds, we conducted phenolic acids metabolomic profiling across 10 wild populations F. suspensa using UPLC-MS/MS. Results Results showedsignificant inter-population variation in all thirty phenolic acids analyzed. Specifically, Verbascoside was significantly enriched in the AZ population, showing a positive correlation with Mean Monthly Temperature Range, Temperature Seasonality, and Temperature Annual Range, but a negative correlation with Annual Precipitation, Precipitation of Driest Quarter, Precipitation of Coldest Quarter and Min Temperature of Coldest Month. 4-Coumaroylshikimate, accumulated in WML and PS, was positively correlated with Precipitation of Wettest Month, Precipitation of Wettest Quarter, and Precipitation of Warmest Quarter, while negatively correlated with Min Temperature of Coldest Month. Gallotannin, enriched in LT, was negatively correlated with Mean Monthly Temperature Range, Temperature Seasonality, Temperature Annual Range, and Precipitation Seasonality, but positively correlated with Annual Precipitation. Isosalicin, accumulated in HX, showed a positive correlation with Max Temperature of Warmest Month and negative correlation with Annual Precipitation and Elevation. Discussion These findings demonstrated that phenolic acids accumulation in F. suspensa was primarilydriven by temperature heterogeneity, with precipitation as a secondary factor, whereas adaptation to elevation plays a minimal role. This study systematically investigated the divergence and environmental drivers of phenolic acids in F. suspensa populations, clarifying the molecular ecological mechanisms behind its adaptation toenvironmental heterogeneity and thereby offering important insights into how ecological factors shape the medicinal potential of F. suspensa , ultimately informing targeted breeding and optimized field management.

This paper presents the way of implementation of fuzzy set operators at the transistor level. We propose a novel realization of basic fuzzy logic (FL) functions, such as bounded sum, bounded difference, bounded product, bounded complement, fuzzy logic union (MAX) and fuzzy logic intersection (MIN). The proposed structures of the operators may be easily connected in chains, creating larger FL systems.

The paper presents a novel, transistor level, implementation of selected fuzzy set operators suitable for fuzzy control systems realized in low-power hardware. We propose a fully digital, asynchronous realization of basic fuzzy logic (FL) functions, such as the bounded sum, bounded difference, bounded product, bounded complement, fuzzy logic union (MAX) and fuzzy logic intersection (MIN). All of the proposed operators has been implemented in the CMOS TSMC 180nm Technology and verified by means of transistor level simulations in Hspice environment. The proposed structures of the FL functions can easily be scaled to any signal resolutions.

To investigate the factors affecting the distribution of Pomacea and project the trends in the spread of suitable distribution areas of Pomacea in 2050 and 2070 in Dali Bai Autonomous Prefecture, so as to provide insights into Pomacea control in the prefecture. The longitudes and latitudes of Pomacea sampling sites were captured based on Pomacea field survey data in 12 cities (counties) of Dali Bai Autonomous Prefecture from 2023 to 2024. A total of 19 climatic factors (annual mean temperature, mean diurnal range, isothermality, temperature seasonality, maximum temperature of the warmest month, minimum temperature of the coldest month, temperature annual range, mean temperature of the wettest quarter, mean temperature of the driest quarter, mean temperature of the warmest month, mean temperature of the coldest month, annual precipitation, precipitation of the wettest month, precipitation of the driest month, precipitation seasonality, precipitation of the wettest quarter, precipitation of the driest quarter, mean temperature of the warmest quarter, and mean temperature of the coldest quarter) and representative concentration pathways (RCPs) were retrieved from the world climate database (www.worldclim.org). All climatic variables were employed to create a maximum entropy (MaxEnt) model. The predictive accuracy of the model was assessed with the area under the receiver operating characteristic (ROC) curve (AUC), and the contributions of these 19 climatic factors to the distribution of Pomacea were analyzed in Dali Bai Autonomous Prefecture using Jackknife test. In addition, the suitable distribution areas of Pomacea were predicted with the MaxEnt model in Dali Bai Autonomous Prefecture in 2024 and in 2050 and 2070 under RCP4.5. Data pertaining to 91 Pomacea sampling sites were captured. ROC analysis revealed the MaxEnt model had an AUC value of 0.885 ± 0.088 for predicting the suitable distribution areas of Pomacea in Dali Bai Autonomous Prefecture. Of the 19 climatic factors, the maximum temperature of the warmest month had the highest contribution to the distribution of Pomacea in Dali Bai Autonomous Prefecture, followed by mean temperature of the driest quarter, mean temperature of the wettest quarter and minimum temperature of the coldest month. The suitable distribution area of Pomacea was predicted to be 14 555.69 km2 in Dali Bai Autonomous Prefecture in 2024, and would expand gradually to the southeastern part of the prefecture in the future due to climatic factors. The suitable distribution areas of Pomacea were projected to expand to 21 475.61 km2 in 2050 and 25 782.52 km2 in 2070 in Dali Bai Autonomous Prefecture, respectively. Temperature is an important contributor to the distribution of Pomacea in Dali Bai Autonomous Prefecture, and the suitable distribution area of Pomacea will gradually expand to the southeastern part of the prefecture in 2050 and 2070.

Bactrocera frauenfeldi (Schiner), the ‘mango fruit fly’, is a horticultural pest originating from the Papua New Guinea region. It was first detected in Australia on Cape York Peninsula in north Queensland in 1974 and had spread to Cairns by 1994 and Townsville by 1997. Bactrocera frauenfeldi has not been recorded further south since then despite its invasive potential, an absence of any controls and an abundance of hosts in southern areas. Analysis of cue-lure trapping data from 1997 to 2012 in relation to environmental variables shows that the distribution of B. frauenfeldi in Queensland correlates to locations with a minimum temperature for the coldest month >13.2°C, annual temperature range <19.3°C, mean temperature of the driest quarter >20.2°C, precipitation of the wettest month >268 mm, precipitation of the wettest quarter >697 mm, temperature seasonality <30.9°C (i.e. lower temperature variability) and areas with higher human population per square kilometre. Annual temperature range was the most important variable in predicting this species' distribution. Predictive distribution maps based on an uncorrelated subset of these variables reasonably reflected the current distribution of this species in northern Australia and predicted other areas in the world potentially at risk from invasion by this species. This analysis shows that the distribution of B. frauenfeldi in Australia is correlated to certain environmental variables that have most likely limited this species' spread southward in Queensland. This is of importance to Australian horticulture in demonstrating that B. frauenfeldi is unlikely to establish in horticultural production areas further south than Townsville.

ABSTRACTIn this article, we approached the study of spatiotemporal variation in trends for the monthly mean values of maximum and minimum temperatures on the Spanish mainland between 1951 and 2010, in order to find out how length and selected periods affected trends. The trend and significance signals were calculated every month and for each cell individually, in a high spatial resolution grid (Mann–Kendall test) by using decreasing and increasing temporal windows (from 20 to 60 years and vice versa). Finally, the results are presented as a sequence of temporal window trend maps to show the spatiotemporal variability of trends at high resolution over the years. The results of increasing temporal window trends show that temperatures have increased overall on the Spanish mainland, but the impact is different for cold and warm months, maximum and minimum temperatures, and the area affected by significant trends varies depending on the month. The positive and significant trend affecting &gt;20% of the total area extends in a west–east gradient during the cold months, while the reverse is true for the warmest ones. The analyses from decreasing the length of moving windows also vary greatly among months. The areas affected by significant trends are highly variable month‐on‐month, differ for maximum and minimum temperatures, and evolve in different ways over time. Few months show a significant trend during the last 30 years, and spatial distribution differences among trends for the maximum and minimum temperatures are detected. Spatially, a more complex gradient can be observed, but the global east–west and west–east gradient can also be generally seen in the warmest or coldest months. These findings show that a selected period determines the final trend. Furthermore, the results suggest that recent warming processes on the Spanish mainland have high spatial variability that differs among months and maximum and minimum temperatures, and has not been constant.