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Mechanistic effect models (MEM) have become increasingly popular in the field of environmental risk assessment (ERA) of plant protection products. However there remains numerous open questions to risk assessors, modelers, applicants and the public. This report provides a scientific evaluation of 11 MEM or MEM families. It also critically assesses their relevance for ERA (e.g. as a refinement tool), based on case studies. Finally, the report offers suggestions for future improvements in model development for implementation in ERA. Outcomes were discussed with experts from industries, consultancies, academia and agencies at a European symposium (19-20 Sept 2019, Berlin); the presentations and minutes are available in the annex.

Multiple packs of wolfs have settled recently in the Netherlands. Question is how large the potential distribution area can be in the near future and what the corresponding population number is. This report answers these questions based on a data driven model which assess habitat suitability., Met de vestiging van meerdere roedels wolven is de terugkeer van deze soort in Nederland een feit. Vraag is hoe het potentiële verspreidingsgebied van de wolf in Nederland er op termijn uit zou kunnen zien en hoe groot de wolvenpopulatie zou kunnen worden. Dit rapport beantwoordt deze vragen op basis van een datagedreven modelanalyse naar de habitatgeschiktheid van Nederland voor de wolf.

Wildlife in cities divides people, with some animals bringing positive benefits and others causing conflict, for example due to property damage.Urban wildlife professionals from municipal administration, nature conservation, and hunting associations have a crucial role in shaping human-wildlife relationships in cities and fostering conflict-free coexistence. While many studies on urban wildlife have focused on the views of citizens, few have investigated the perspectives of experts to date. To address this knowledge gap, we interviewed 36 urban wildlife professionals giving guidance in the context of urban wildlife management, either in one of the four largest German cities by population (Berlin, Hamburg, Munich and Cologne) or at the national level.Red foxes, wild boars, raccoons, stone martens and Eurasian beavers were the five mammal species most frequently highlighted in interviews to cause human-wildlife conflicts. The interviewees saw wild boars and raccoons as the most controversial urban wild mammals but emphasized the need to create refuges for beavers and better inform the public about foxes.Management in terms of public outreach, urban planning and population control, as well as establishing official contact points and stricter fines of activities violating regulations were highlighted as important elements of a toolkit to manage urban wildlife conflicts.

Context Preserving functional connectivity is a conservation priority to secure the long-term viability of geographically dispersed subpopulations, such as the jaguar (Panthera onca) populations in Central America. However, managing connectivity in this region is limited due to the scarcity of local assessments of the connectivity between existing populations, some of which exhibit low levels of gene flow and genetic admixture. Objectives We selected the jaguar as a model species to understand how gene flow of large carnivores is shaped in a heavily human-impacted landscape in the Neotropics. We assessed the impact of landscape features and spatial scale on jaguar gene flow across northern Central America, predicted synoptic, landscape-wide functional connectivity across the region; and compared connectivity predictions based on models of gene flow, habitat suitability, and expert knowledge. Methods We employed genetic data based on 335 faecal samples collected from 72 individual jaguars. We parameterized gene flow resistance surfaces using linear mixed effects models and the maximum likelihood population-effects method. We evaluated nine landscape variables at six spatial scales, selecting the optimal scale and transformation for each variable according to univariate models and AIC. To predict jaguar gene flow, we developed multivariate models and implemented resistant kernels to forecast functional connectivity between jaguar populations across the study region under three dispersal distance scenarios. Furthermore, we compared the connectivity estimates based on gene flow against those based on habitat suitability and the corridors delineated by expert knowledge in the region. Results Low resistance to jaguar gene flow was associated with greater tree cover and vegetation, lower areas of built-up, and intermediate distances from water bodies. Notably, tree cover affected jaguar gene flow on a smaller scale compared to the rest of variables. Highe

Rapid development of tracking technologies allow the collection of high-quality data on multiple simultaneously moving individuals. This, in turn, initiated the development of several methods to infer interactions among moving animals. However, the performance of these methods has not been studied systematically, especially with regard to the factors that are highly relevant for field ecologists, such as duration of the tracking period, its temporal resolution and the proportion of the tracked community.Here, we assessed the performance of three dynamic interaction indices (Coefficient of sociality, Correlation coefficient and Dynamic interaction) and two novel approaches based on step selection functions (SSF-occurrence-distribution and SSF-distance). We tested these methods on the data simulated with a predator–prey system, reflecting three common types of interactions while on the move: avoidance (prey individuals fleeing from the predator), attraction (predator following and chasing prey) and neutral movement (no interactions between predator and prey). We assessed the ability of each method to correctly detect the modelled interaction type by manipulating the perceptual range of the predator, the proportion of tracked prey individuals, the temporal resolution and the duration of the tracking period.We found that the ability to correctly infer interactions increased for all methods with an increase in the perceptual range of the predator and the proportion of tracked prey individuals. In contrast, the duration of the tracking period affected the methods' performance differently: some methods (Cs and SSF-distance) were insensitive to it, whereas the performance of other methods improved (DI and SSF-occurrence-distribution) and worsened (Cr) with the duration of the tracking period. The three dynamic interaction indices and SSF-distance were rather robust to changes in data resolution.Despite using the predator–prey system as our study case, our findings are appli

"There are no scientifically justified obstacles to protecting biodiversity in all its beauty and diversity. There are only six years left to achieve the biodiversity targets by 2030. We must work together now to get there in time."In the 10 Must Knows from Biodiversity Science 2024, 64 scientists have further developed their well-founded and diverse findings and recommendations from the 10MustKnows22. The content of the ten selected key areas of the Earth-human system is supplemented by relevant publications from 2022 and 2023 and linked to the 23 global goals of the Kunming-Montreal Global Biodiversity Framework (GBF) adopted in December 2022. The authors are aware that the next six years until 2030 are essential for achieving an ecologically sustainable and socially just life on our planet in the medium and long term. With the 10MustKnows24, they want to actively contribute to accelerating the socio-ecological transformation by providing scientifically sound recommendations for politics and society.These are the 10MustKnows24: 1: Achieving climate and biodiversity protection together 2: Enabling a healthy life on a healthy planet 3: Considering undiscovered biodiversity 4: Linking linguistic, cultural and biological diversity 5: Harmonising the diverse use of forest ecosystems and biodiversity conservation 6: Transforming agricultural and food systems 7: Protecting land and resources 8: Releasing transformative change through international collaboration and Education for Sustainable Development 9: Ensuring free access and open use of biodiversity-related data 10: Reducing biodiversity impacts from food consumption

"Es gibt wissenschaftlich keine begründeten Hindernisse, die Biodiversität in ihrer Schönheit und Vielfalt zu schützen. Es bleiben nur noch sechs Jahre, um die Biodiversitätsziele bis 2030 zu erreichen. Dafür müssen wir jetzt gemeinsam anpacken."In den 10 Must-Knows aus der Biodiversitätsforschung 2024 haben 64 Wissenschaftlerinnen und Wissenschaftler ihre fundierten und vielseitigen Erkenntnisse und Empfehlungen aus den 10MustKnows22 weiterentwickelt. Die zehn ausgewählten Schlüsselbereiche des Erde-Mensch-Systems werden inhaltlich durch relevante Publikationen von 2022 und 2023 ergänzt und mit den im Dezember 2022 verabschiedeten 23 globalen Zielen des Kunming-Montreal Global Biodiversity Framework (GBF) verknüpft. Den Autorinnen und Autoren ist bewusst, dass die kommenden sechs Jahre bis 2030 wesentlich sind, um mittel- und langfristig ein ökologisch nachhaltiges und sozial gerechtes Leben auf unserer Erde zu erreichen. Mit den 10MustKnows24 möchten sie durch wissenschaftlich gesicherte Empfehlungen für Politik und Gesellschaft ihren aktiven Beitrag leisten, um die sozial-ökologische Transformation zu beschleunigen.Das sind die 10MustKnows24: 1. Klima- und Biodiversitätsschutz gemeinsam verwirklichen 2. Ein gesundes Leben auf einem gesunden Planeten ermöglichen 3. Unentdeckte Biodiversität beachten 4. Sprachliche, kulturelle und biologische Vielfalt verknüpfen 5. Vielfältige Nutzung von Waldökosystemen und Biodiversitätsschutz in Einklang bringen 6. Agrar- und Ernährungssysteme transformieren 7. Land und Ressourcen schützen 8. Transformativen Wandel durch internationale Zusammenarbeit und Bildung für nachhaltige Entwicklung bewirken 9. Freien Zugang und offene Nutzung von biodiversitätsbezogenen Daten sicherstellen 10. Auswirkungen des Lebensmittelkonsums auf die Biodiversität verringern

In the 10 Must Knows from Biodiversity Science 45 scientists present facts about biodiversity in a well-founded and generally intelligible way. They analyse the complex systems of the earth by highlighting ten key areas, each of which, in turn, is inextricably linked to all the others. And they show ways to stop the continued loss of species diversity and ecosystems, and to promote biodiversity. The underlying aim is to provide policy-makers and society with scientifically validated assessments of the latest knowledge to facilitate improved policy decisions and action at local, regional, national and global levels, in order to conserve the diversity of life – biodiversity. These are the 10MustKnows 2022: 1. Achieving climate and biodiversity protection together 2. Strengthening planetary health 3. Considering hidden biodiversity 4. Promoting biocultural habitats 5. Using forests sustainably 6. Transforming agriculture 7. Protecting land and resources 8. Expanding transnational infrastructure and education for sustainability 9. Ensuring access and open use of research data 10. Setting biodiversity-friendly incentives

Understanding species-environment relationships at large spatial scales is required for the prioritization of conservation areas and the preservation of landscape connectivity for large carnivores. This endeavour is challenging for jaguars (Panthera onca), given their elusiveness, and the local nature of most jaguar studies, precluding extrapolation to larger areas. We developed an occupancy model using occurrence data of jaguars across five countries of Central America, collected from camera-trap studies of 2–12 months' duration, deployed over an area of 14 112 km2 from 2005 to 2018. Our occupancy model showed that habitat use of jaguars increased with primary net productivity and distance to human settlements, and decreased with distance to rivers. Detection of the species was related to survey effort and research team identity. Within the jaguar extent of occurrence, 73% was deemed suitable for the species, with 47% of it lying within Jaguar Conservation Units (JCU) and 59% of JCU land being legally protected. Suitable areas were divided into four distinct clusters of continuous habitat shared across country borders. However, large areas of predicted low habitat suitability may constrict connectivity in the region. The reliability of these spatial predictions is indicated by the model validation using an independent dataset (AUC = 0.82; sensitivity = 0.766, specificity = 0.761), and concordance of our results with other studies conducted in the region. Across Central America, we found that human influence has the strongest impact on jaguar habitat use and JCUs are the main reservoirs of habitat. Therefore, conservation actions must focus on preventing habitat loss and mitigating human pressure, particularly within the clusters of continuous areas of high suitability, and on restoring habitat to foster connectivity. The long-term persistence of jaguars in the region will depend on strong international cooperation that secures jaguar populations and their habitat a

In the 10 Must Knows from Biodiversity Science 45 scientists present facts about biodiversity in a well-founded and generally intelligible way. They analyse the complex systems of the earth by highlighting ten key areas, each of which, in turn, is inextricably linked to all the others. And they show ways to stop the continued loss of species diversity and ecosystems, and to promote biodiversity. The underlying aim is to provide policy-makers and society with scientifically validated assessments of the latest knowledge to facilitate improved policy decisions and action at local, regional, national and global levels, in order to conserve the diversity of life – biodiversity. These are the 10MustKnows 2022: 1. Achieving climate and biodiversity protection together 2. Strengthening planetary health 3. Considering hidden biodiversity 4. Promoting biocultural habitats 5. Using forests sustainably 6. Transforming agriculture 7. Protecting land and resources 8. Expanding transnational infrastructure and education for sustainability 9. Ensuring access and open use of research data 10. Setting biodiversity-friendly incentives

Organismal movement is ubiquitous and facilitates important ecological mechanisms that drive community and metacommunity composition and hence biodiversity. In most existing ecological theories and models in biodiversity research, movement is represented simplistically, ignoring the behavioural basis of movement and consequently the variation in behaviour at species and individual levels. However, as human endeavours modify climate and land use, the behavioural processes of organisms in response to these changes, including movement, become critical to understanding the resulting biodiversity loss. Here, we draw together research from different subdisciplines in ecology to understand the impact of individual‐level movement processes on community‐level patterns in species composition and coexistence. We join the movement ecology framework with the key concepts from metacommunity theory, community assembly and modern coexistence theory using the idea of micro–macro links, where various aspects of emergent movement behaviour scale up to local and regional patterns in species mobility and mobile‐link‐generated patterns in abiotic and biotic environmental conditions. These in turn influence both individual movement and, at ecological timescales, mechanisms such as dispersal limitation, environmental filtering, and niche partitioning. We conclude by highlighting challenges to and promising future avenues for data generation, data analysis and complementary modelling approaches and provide a brief outlook on how a new behaviour‐based view on movement becomes important in understanding the responses of communities under ongoing environmental change.

Understanding host–pathogen dynamics requires realistic consideration of transmission events that, in the case of directly transmitted pathogens, result from contacts between susceptible and infected individuals. The corresponding contact rates are usually heterogeneous due to variation in individual movement patterns and the underlying landscape structure. However, in epidemiological models, the roles that explicit host movements and landscape structure play in shaping contact rates are often overlooked. We adapted an established agent‐based model of classical swine fever (CSF) in wild boar Sus scrofa to investigate how explicit representation of landscape heterogeneity and host movement between social groups affects invasion and persistence probabilities. We simulated individual movement both phenomenologically as a correlated random walk (CRW) and mechanistically by representing interactions of the moving individuals with the landscape and host population structure. The effect of landscape structure on the probability of invasion success and disease persistence depended remarkably on the way host movement is simulated and the case fatality ratio associated with the pathogen strain. The persistence probabilities were generally low with CRW which ignores feedbacks to external factors. Although the basic reproduction number R0, a measure of the contagiousness of an infectious disease, was kept constant, these probabilities were up to eight times higher under mechanistic movement rules, especially in heterogeneous landscapes. The increased persistence emerged due to important feedbacks of the directed movement on the spatial variation of host density, contact rates, and transmission events to distant areas. Our findings underscore the importance of accounting for spatial context and group size structures in eco‐epidemiological models. Our study highlights that the simulation of explicit, mechanistic movement behaviour can reverse predictions of disease persistence in

Animals access resources such as food and shelter, and acquiring these resources has varying risks and benefits, depending on the suitability of the landscape. Some animals change their patterns of resource selection in space and time to optimize the trade-off between risks and benefits. We examine the circadian variation in resource selection of swamp wallabies (Wallabia bicolor) within a human-modified landscape, an environment of varying suitability. We used GPS data from 48 swamp wallabies to compare the use of landscape features such as woodland and scrub, housing estates, farmland, coastal areas, wetlands, waterbodies, and roads to their availability using generalized linear mixed models. We investigated which features were selected by wallabies and determined whether the distance to different landscape features changed, depending on the time of the day. During the day, wallabies were more likely to be found within or near natural landscape features such as woodlands and scrub, wetlands, and coastal vegetation, while avoiding landscape features that may be perceived as more risky (roads, housing, waterbodies, and farmland), but those features were selected more at night. Finally, we mapped our results to predict habitat suitability for swamp wallabies in human-modified landscapes. We showed that wallabies living in a human-modified landscape selected different landscape features during day or night. Changing circadian patterns of resource selection might enhance the persistence of species in landscapes where resources are fragmented and disturbed.

Ecosystems respond in various ways to disturbances. Quantifying ecological stability therefore requires inspecting multiple stability properties, such as resistance, recovery, persistence and invariability. Correlations among these properties can reduce the dimensionality of stability, simplifying the study of environmental effects on ecosystems. A key question is how the kind of disturbance affects these correlations. We here investigated the effect of three disturbance types (random, species‐specific, local) applied at four intensity levels, on the dimensionality of stability at the population and community level. We used previously parameterized models that represent five natural communities, varying in species richness and the number of trophic levels. We found that disturbance type but not intensity affected the dimensionality of stability and only at the population level. The dimensionality of stability also varied greatly among species and communities. Therefore, studying stability cannot be simplified to using a single metric and multi‐dimensional assessments are still to be recommended.

Understanding the drivers underlying disease dynamics is still a major challenge in disease ecology, especially in the case of long‐term disease persistence. Even though there is a strong consensus that density‐dependent factors play an important role for the spread of diseases, the main drivers are still discussed and, more importantly, might differ between invasion and persistence periods.Here, we analysed long‐term outbreak data of classical swine fever, an important disease in both wild boar and livestock, prevalent in the wild boar population from 1993 to 2000 in Mecklenburg‐Vorpommern, Germany. We report outbreak characteristics and results from generalized linear mixed models to reveal what factors affected infection risk on both the landscape and the individual level.Spatiotemporal outbreak dynamics showed an initial wave‐like spread with high incidence during the invasion period followed by a drop of incidence and an increase in seroprevalence during the persistence period. Velocity of spread increased with time during the first year of outbreak and decreased linearly afterwards, being on average 7.6 km per quarter. Landscape‐ and individual‐level analyses of infection risk indicate contrasting seasonal patterns. During the persistence period, infection risk on the landscape level was highest during autumn and winter seasons, probably related to spatial behaviour such as increased long‐distance movements and contacts induced by rutting and escaping movements. In contrast, individual‐level infection risk peaked in spring, probably related to the concurrent birth season leading to higher densities, and was significantly higher in piglets than in reproductive animals.Our findings highlight that it is important to investigate both individual‐ and landscape‐level patterns of infection risk to understand long‐term persistence of wildlife diseases and to guide respective management actions. Furthermore, we highlight that exploring different temporal aggre

Environmental factors shape the spatial distribution and dynamics of populations. Understanding how these factors interact with movement behavior is critical for efficient conservation, in particular for migratory species. Adult female green sea turtles, Chelonia mydas, migrate between foraging and nesting sites that are generally separated by thousands of kilometers. As an emblematic endangered species, green turtles have been intensively studied, with a focus on nesting, migration, and foraging. Nevertheless, few attempts integrated these behaviors and their trade‐offs by considering the spatial configurations of foraging and nesting grounds as well as environmental heterogeneity like oceanic currents and food distribution. We developed an individual‐based model to investigate the impact of local environmental conditions on emerging migratory corridors and reproductive output and to thereby identify conservation priority sites. The model integrates movement, nesting, and foraging behavior. Despite being largely conceptual, the model captured realistic movement patterns which confirm field studies. The spatial distribution of migratory corridors and foraging hot spots was mostly constrained by features of the regional landscape, such as nesting site locations, distribution of feeding patches, and oceanic currents. These constraints also explained the mixing patterns in regional forager communities. By implementing alternative decision strategies of the turtles, we found that foraging site fidelity and nesting investment, two characteristics of green turtles' biology, are favorable strategies under unpredictable environmental conditions affecting their habitats. Based on our results, we propose specific guidelines for the regional conservation of green turtles as well as future research suggestions advancing spatial ecology of sea turtles. Being implemented in an easy to learn open‐source software, our model can coevolve with the collection and analysis of

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AimClimate change alters the water cycle, potentially affecting the distribution of species. Using an ensemble of species distribution models (SDMs), we predicted changes in distribution of the Asian elephant in South Asia due to increasing climatic variability under warming climate and human pressures. LocationIndia and Nepal. MethodsWe compiled a comprehensive geodatabase of 115 predictor variables, which included climatic, topographic, human pressures and land use, at a resolution of 1 km2, and an extensive database on current distribution of elephants. For variable selection, we first developed 14 candidate models based on different hypotheses on elephant habitat selection. For each candidate model, a series of 240 individual models were evaluated using several metrics. Using three climatic and one land use change datasets for two greenhouse gas scenarios, ensemble SDMs were used to predict future projections. ResultsNine predictor variables were selected for ensemble SDMs. Elephant distribution is driven predominantly by changes in climatic water balance (>60%), followed by changes in temperature and human‐induced disturbance. The results suggest that around 41.8% of the 256,518 km2 of habitat available at present will be lost by the end of this century due to combined effects of climate change and human pressure. Projected habitat loss will be higher in human‐dominated sites at lower elevations due to intensifying droughts, leading elephants to seek refuge at higher elevations along valleys with greater water availability in the Himalayan Mountains. Main conclusionsChanges in climatic water balance could play a crucial role in driving species distributions in regions with monsoonal climates. In response, species would shift their range upwards along gradients of water availability and seasonal droughts. Conservation and management of elephant populations under global change should include design of movement corridors to enable dispersa

Non-consumptive effects of predators within ecosystems can alter the behavior of individual prey species, and have cascading effects on other trophic levels. In this context, an understanding of non-consumptive predator effects on the whole prey community is crucial for predicting community structure and composition, hence biodiversity patterns. We used an individual-based, spatially-explicit modelling approach to investigate the consequences of landscapes of fear on prey community metrics. The model spans multiple hierarchical levels from individual home range formation based on food availability and perceived predation risk to consequences on prey community structure and composition. This mechanistic approach allowed us to explore how important factors such as refuge availability and foraging strategy under fear affect prey community metrics. Fear of predators affected prey space use, such as home range formation. These adaptations had broader consequences for the community leading to changes in community structure and composition. The strength of community responses to perceived predation risk was driven by refuge availability in the landscape and the foraging strategy of prey animals. Low refuge availability in the landscape strongly decreased diversity and total biomass of prey communities. Additionally, body mass distributions in prey communities facing high predation risk were shifted towards small prey animals. With increasing refuge availability the consequences of non-consumptive predator effects were reduced, diversity and total biomass of the prey community increased. Prey foraging strategies affected community composition. Under medium refuge availability, risk-averse prey communities consisted of many small animals while risk-taking prey communities showed a more even body mass distribution. Our findings reveal that non-consumptive predator effects can have important implications for prey community diversity and should therefore be considered in the co

Epidemiological models of infectious diseases are essential tools in support of risk assessment, surveillance design, and contingency planning in public and animal health. Direct pathogen transmission from host to host is an essential process of each host–pathogen system and respective epidemiological modeling concepts. It is widely accepted that numerous diseases involve indirect transmission (IT) through pathogens shed by infectious hosts to their environment. However, epidemiological models largely do not represent pathogen persistence outside the host explicitly. We hypothesize that this simplification might bias management-related model predictions for disease agents that can persist outside their host for a certain time span. We adapted an individual-based, spatially explicit epidemiological model that can mimic both transmission processes. One version explicitly simulated indirect pathogen transmission through a contaminated environment. The second version simulated direct host-to-host transmission only. We aligned the model variants by the transmission potential per infectious host (i.e., basic reproductive number R0) and the spatial transmission kernel of the infection to allow unbiased comparison of predictions. The quantitative model results are provided for the example of surveillance plans for early detection of foot-and-mouth disease in wild boar, a social host. We applied systematic sampling strategies on the serological status of randomly selected host individuals in both models. We compared between the model variants the time to detection and the area affected prior to detection, measures that strongly influence mitigation costs. Moreover, the ideal sampling strategy to detect the infection in a given time frame was compared between both models. We found the simplified, direct transmission model to underestimate necessary sample size by up to one order of magnitude but to overestimate the area put under control measures. Thus, the model predictions

Denmark was considered not to have an established population of free-ranging wild boar. Today, sporadic observations of wild boar challenge that view. Due to its reservoir role for economic devastating swine diseases, wild boar represents a potential threat for Denmark’s position as a large pig- and pork-exporting country. This study assessed the prospects of wild boar invasion in Denmark.Multi-source citizen science data of wild boar observations were integrated into a multi-modelling approach linking habitat suitability models with agent-based, spatially-explicit simulations. We tested whether the currently observed presence of wild boar is due to natural immigration across the Danish–German border, or whether it is more likely that wild boar escaped fenced premises. Five observational data sources served as evaluation data: (1) questionnaires sent to all 1625 registered owners of Danish farm land, located in the 60 parishes closest to the border, (2) an online questionnaire, (3) a mobile web-based GPS application, (4) reports in the media or by governmental agencies, and (5) geo-referenced locations of fenced wild boar populations.Data covering 2008–2013 included 195 observations of wild boar, including 16 observations of breeding sows. The data from the Danish Nature Agency and the mailed questionnaires were consistent regarding the location of wild boar observations, while data from the Danish Veterinary and Food Administration, the media and the electronic questionnaires documented individual scattered observations in the rest of Jutland. Most observations were made in the region bordering Germany.It is uncertain whether the relatively few observations represent an established population. Model outcomes suggested that the origin of wild boar in about half of the area with sporadic observations of wild boar could be attributed to spatial expansions from a local Danish population near the border and consisting of wild boar originally of German origin. However, t

Knowing the distribution of species and the factors which determine it is a basic requirementfor conservation efforts and developing management plans. Species distribution modelling (SDM) is aspeedy and cost-effective tool for predicting species distributions, particularly for species in remote andinaccessible areas. This technique can be applied for example for poorly known small carnivore speciesin Southeast Asia, a biodiversity hot spot for mammals. SDM is used to gain ecological insights about theenvironmental factors that determine species distribution, and helps to identify the areas where a species can occur and where confl icts may arise. However, recent advances in statistical theory and computer processing have made SDM a somewhat complex, diverse, and confusing area of research. This review presents an overview over the different techniques of species distribution modelling, and databases needed to answer applied questions in carnivore conservation, particularly in the tropics. We guide the ecologist through different methods which have become established approaches in the scientifi c literature and through freely available resources on abiotic data (environmental layers) for conducting such studies. We summarise the steps involved in predictive species distribution modelling, where the (carnivore) occurrence data come from different resources (such as museum records, voluntary surveys, systematic surveys, etc.). Finally, we explore the applications of such predictions in carnivore conservation.

Classical swine fever (CSF) is a severe multi-systemic disease that can affect both domestic pigs and wild boar. Past outbreaks in European wild boar involved high-virulent CSF virus (CSFV) strains and were mostly self-limiting. In these cases, morbidity and mortality rates were high in the affected regions. In contrast, endemic infections have been observed in several European wild boar populations in recent decades. Morbidity and mortality rates were much lower despite the fact that outbreaks were still detected via diseased or fallen animals. The virus strains involved were mostly classified as genotype 2.3 strains of moderate virulence causing age-dependent disease outcomes. The mechanisms leading to the establishment and perpetuation of endemicity are still not fully understood, but the factor “moderate virulence” seems to be of considerable importance.In this study, we aim to clarify whether the perception of declined ‘CSF severity’ could hypothetically reflect the adaptation of an initially high-virulent virus or whether this might be better explained as a misinterpretation of observations. A mechanistic eco-epidemiological model was employed to follow up a highly virulent strain of CSFV introduced into large connected wild boar populations. In the model, the virulence of the CSF virus is represented by case mortality and life expectancy after lethal infection. Allowing for small stochastic variation, these two characteristics of the virus are passed on with every new simulated infection that occurs.Model analysis revealed a decrease from high to moderate case mortality within a few years of simulated perpetuation of the virus. The resulting mortality corresponded to the level where the population average of the infectious period and the basic reproduction number of the disease were maximal. This shift in virulence was sufficient to prolong virus circulation considerably beyond the epidemic phase of the simulated outbre

To counteract the threat of habitat loss and fragmentation for wildlife in Europe, planning processes need to incorporate basic requirements of wildlife populations. In several regions in Germany, the expansion of the wildcat (Felis silvestris, Schreber 1777) population is hindered by fragmented habitat and anthropogenic barriers. We developed a corridor plan for Lower Saxony, Germany, that can be used as a protocol for guiding species restoration to reconnect fragmented habitat patches based on a statistical habitat selection model. The model was transferred directly into a cost surface and we used least-cost path models to find the best potential corridors leading from source areas towards the north and connecting existing populations. We evaluated the habitat model and corridors with a dataset of more than 800 cases of wildcat sightings and road kills within the study area. 9500 km2 of the area of Lower Saxony were identified as suitable wildcat habitat, of which only one third is populated by wildcats at the moment. Wildcat sightings and casualties were significantly more often near potential corridors identified by the least-cost path model than elsewhere. With the wildcat corridor network proposed here, areas can be defined which should have a high priority to be kept in a natural state as an aim of land use plans, which should be improved where necessary and where mitigation measures should be concentrated. We give practical advice on how to optimise and implement corridors for the purpose of land use planning.

Classical Swine Fever (CSF) is considered an endemic disease in European wild boar populations. In view of the high economic impact of the introduction of the virus into domestic pig units, huge efforts are invested in the preventive control of CSF in wild boar populations. Recent European Community guidelines favour oral mass vaccination against CSF in wild boar populations. The guidelines are explicit on the temporal structure of the vaccination protocol, but little is known about the efficacy of different spatial application schemes, or how they relate to outbreak dynamics. We use a spatially explicit, individual-based wild boar model that represents the ecology of the hosts and the epidemiology of CSF, both on a regional scale and on the level of individual course of infection. We simulate adaptive spatial vaccination schemes accounting for the acute spread of an outbreak while using the temporal vaccination protocol proposed in the Community guidelines. Vaccination was found to be beneficial in a wide range of scenarios. We show that the short-term proactive component of a vaccination strategy is not only as decisive as short-term continuity, but also that it can outcompete alternative practices while being practically feasible. Furthermore, we show that under certain virus-host conditions vaccination might actually contribute to disease persistence in local populations.

Despite the documented negative effects of roads on wildlife, ecological research on road effects has had comparatively little influence on road planning decisions. We argue that road research would have a larger impact if researchers carefully considered the relevance of the research questions addressed and the inferential strength of the studies undertaken. At a workshop at the German castle of Rauischholzhausen we identified five particularly relevant questions, which we suggest provide the framework for a research agenda for road ecology: (1) Under what circumstances do roads affect population persistence? (2) What is the relative importance of road effects vs. other effects on population persistence? (3) Under what circumstances can road effects be mitigated? (4) What is the relative importance of the different mechanisms by which roads affect population persistence? (5) Under what circumstances do road networks affect population persistence at the landscape scale? We recommend experimental designs that maximize inferential strength, given existing constraints, and we provide hypothetical examples of such experiments for each of the five research questions. In general, manipulative experiments have higher inferential strength than do nonmanipulative experiments, and full before-after-control-impact designs are preferable to before-after or control-impact designs. Finally, we argue that both scientists and planners must be aware of the limits to inferential strength that exist for a given research question in a given situation. In particular, when the maximum inferential strength of any feasible design is low, decision makers must not demand stronger evidence before incorporating research results into the planning process, even though the level of uncertainty may be high. Copyright

Despite the documented negative effects of roads on wildlife, ecological research on road effects has had comparatively little influence on road planning decisions. We argue that road research would have a larger impact if researchers carefully considered the relevance of the research questions addressed and the inferential strength of the studies undertaken. At a workshop at the German castle of Rauischholzhausen we identified five particularly relevant questions, which we suggest provide the framework for a research agenda for road ecology: (1) Under what circumstances do roads affect population persistence? (2) What is the relative importance of road effects vs. other effects on population persistence? (3) Under what circumstances can road effects be mitigated? (4) What is the relative importance of the different mechanisms by which roads affect population persistence? (5) Under what circumstances do road networks affect population persistence at the landscape scale? We recommend experimental designs that maximize inferential strength, given existing constraints, and we provide hypothetical examples of such experiments for each of the five research questions. In general, manipulative experiments have higher inferential strength than do nonmanipulative experiments, and full before-after-control-impact designs are preferable to before-after or control-impact designs. Finally, we argue that both scientists and planners must be aware of the limits to inferential strength that exist for a given research question in a given situation. In particular, when the maximum inferential strength of any feasible design is low, decision makers must not demand stronger evidence before incorporating research results into the planning process, even though the level of uncertainty may be high