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• We explore spatially varying limiting factors in species-environment relationships using high resolution telemetry data from 14 individual wildcat hybrids distributed across geographical and environmental gradients in Scotland. • We proposed five hypotheses for how nonstationary limiting factors related to the strength of predictor variable effect size. • Our results show that assumptions of global, stationary habitat associations are likely not met in many habitat models. • We found that there were strong relationships between nonstationarity and spatially varying limiting factors. • Future habitat modeling research should explicitly consider scale and context dependence in a nonstationary modeling paradigm. Species distribution modeling is widely used to quantify and predict species-environment relationships. Most past applications and methods in species distribution modeling assume context independent and stationary relationships between patterns of species occurrence and environmental variables. There has been relatively little research investigating context dependence and nonstationarity in species distribution modeling. In this paper we explore spatially varying limiting factors in species-environment relationships using high resolution telemetry data from 14 individual wildcat hybrids distributed across geographical and environmental gradients in Scotland. (1) We proposed that nonstationary limiting factors would be indicated by significant association between statistical measures of variability of predictors and the predictive importance of those variables. (2) We further proposed that most of the limiting factor relationships observed would be related to spatial variation and a lesser amount to mean value of environmental variables within individual study sites. (3) Additionally, we anticipated that when there was a relationship between variation of an environmental factor and its importance as a predictor this relationship would be positive, such that higher variation would be associated with higher importance of the variable as a predictor (following the theory of limiting factors). (4) Conversely, we proposed that when there was a relationship between the mean value of an environmental variable and its importance as a predictor this relationship would be roughly evenly split between positive and negative relationships, given that environmental variables could become limiting either when they are highly abundant or high value, or when they are rare or low value in a particular landscape, depending on the nature of the species-environment relationship for that ecological variable. (5) Finally, we hypothesized that the frequency of supported limiting factor relationships would differ among variable groups, with variables that were directly related to key environmental resources more likely to be limiting than those that would have more indirect impacts on wildcat hybrid habitat selection or foraging. Our results show that assumptions of global, stationary habitat associations are likely not met in many habitat models, requiring explicit consideration of scale and context dependence in a nonstationary modeling paradigm. We found that both the mean value and the standard deviation are strong predictors of whether that variable will be limiting and differentially important as a predictor of occurrence. We confirmed that limiting factors become more limiting when it has higher variability across the sampled data, or when it is rare or not abundant. The frequency of supported limiting factor relationships differed among variable groups, with variables that were directly related to environmental resources likely to be essential for wildcat hybrid ecology more likely to be limiting than those that would have more indirect impacts on wildcat hybrid habitat selection or foraging. [ABSTRACT FROM AUTHOR]

The ecological environment of the rivers is affected tremendously by artificial constructions such as hydropower stations and dams. Closure alters hydrological conditions of the downstream area. Accordingly, the habitat conditions of the aquatic animals change negatively. The traditional habitat site models are mostly based on the statistical data that are drawn from the historical observation records. Interactions between aquatic animals’ behaviors and environmental issues are often ignored. The Eulerian-Eulerian-Habitat-Selection method (EEHS) in this paper is based on the Boltzmann equation, from the perspective of continuous and momentum theories, with the influences of other environmental factors such as water depth, temperature, substrate and sediment concentration. The movement procedure and distribution of the objects can be obtained by solving the deformed Boltzmann equation. Meanwhile, the model can be applied to other aquatic animals since the two parameters C ps and ω are considered with physical significance that are related with specie, in which C ps represents its sensitivity to the flow velocity and ω its body size. The model can also be applied to a large scale of the study area by taking advantage of the Eulerian framework used in the model. Chinese sturgeon’ distribution was simulated in this paper, with its preference of flow velocity, water depth, substrate and sediment concentration assessed. Compared with the Habitat Suitability Index (HSI) model, the EEHS model produced more accurate results of the distribution of Chinese sturgeon with a correlation coefficient of 0.95, much higher than 0.32 of the HIS model. The simulation results indicate that the habitat condition of Chinese sturgeon downstream of the Gezhou Dam fluctuate when the upstream discharge varies from 4000 to 30,000 m 3 /s. [ABSTRACT FROM AUTHOR]

Estimating absence locations of a species is important in conservation biology and conservation planning. For instance, using reliable absence as much as presence information, species distribution models can enhance their performance and produce more accurate predictions of the distribution of a species. Unfortunately, estimating reliable absence locations is difficult and often requires a deep knowledge of the species’ distribution and of its abiotic and biotic environmental preferences and tolerance. In this paper, we propose a methodology to reconstruct reliable absence information from presence-only information, and the conditions that those presence-only data have to meet to make this possible. Large species occurrence data collections (otherwise called occurrence datasets) contain high quality and expert-reviewed species observation records from scientific surveys. These surveys can be used to retrieve species presence locations, but they also record places where the species in their target list were not observed. Although these absences could be simply due to sampling variation, it is possible to intersect many of these reports to estimate true absence locations, i.e. those due to habitat unsuitability or geographical hindrances. In this paper, we present a method to generate reliable absence locations of this type for marine species, using scientific surveys reports contained in the Ocean Biogeographic Information System (OBIS), an authoritative species occurrence dataset. Our method spatially aggregates information from surveys focussing on the same target species. It detects absence locations for a given species as those locations in which repeated surveys (that included the species of interest in their target list) reported information only on other species. We qualitatively demonstrate the reliability of our method using distribution records of the Atlantic cod as a case study. Additionally, we quantitatively estimate its performance using another authoritative large species occurrence dataset, the Global Biodiversity Information Facility (GBIF). We also demonstrate that our approach has higher accuracy and presents complementary behaviour with respect to another method using environmental envelopes. Our process can support species distribution models (as well as other types of models, e.g. climate change models) by providing reliable data to presence/absence approaches. It can manage regional as well as global scale scenarios and runs within a collaborative e-Infrastructure (D4Science) that publishes it as-a-Service, allowing biologists to reproduce, repeat and share experimental results. [ABSTRACT FROM AUTHOR]

The construction of ecological network or other continuous habitat is essential for urban eco-system; however, to quantify the heterogeneous functional connectivity for eco-network is academically attractive and challenging. The dynamic lines of space syntax, tenable to simulate perception and navigation flows in network-configured human settlements, is introduced to inspire idea and approach to modeling connectivity in eco-network, while the classical graphic notions and variables are assumed functional to new relationship between other species and eco-network. After mapping continuous functional components among land layout into free space and then into dynamic lines that influence bio-flows, the paper conducts an exploration on functional connectivity of Singapore's green network. Conclusions involves the distribution heterogeneity of basic variables, Connectivity , Control , Mean Depth and Integration , demonstrating each meaning for functional connectivity in the network, with a step-wise Integration further comparing the connectivity patterns under different behavioral ranges. Moreover, a scale robustness determined via linear regression between Integration and Connectivity reveals network functionality as behavioral scale varying. The analogical modeling of space syntax raised in this paper is adaptive and instructive, particularly if original essential traits remain valid between the substituted species and space, because several principles and characteristics of conventional connectivity models can be logically inherited, while the graphic notions of dynamic line shares unique advantages. [ABSTRACT FROM AUTHOR]

Natural and designed ecological corridors are key elements for the survival of a species, as they allow the species to avoid local extinction by migrating to more suitable habitat patches. This paper studies various reliability metrics for the process of migration in a metapopulation landscape network from a critical habitat patch to destination habitat patches via perfect stepping stones and imperfect (deletable) corridors. The work presented herein generalizes earlier work on the application of reliability theory in ecology by allowing corridors to be heterogeneous (of non-identical unreliabilities). The paper is a tutorial exposition of modern reliability techniques, which formulate a problem in the Boolean domain, manipulate formulas to achieve disjointness of logically added subexpressions and retain statistical independence of logically multiplied ones, and finally reach a probability-ready expression that is directly transformed back to the probability domain. Several metrics are covered including system unreliability, life expectancy (MTTF), and component importance measures. An interesting finding is that the life expectancy of a classical landscape network is more than double that of a single corridor. Extensions to quantification of uncertainty in the above metrics and to evaluation of more sophisticated metrics of landscape connectivity are also pointed out. [ABSTRACT FROM AUTHOR]

• The habitat suitability model is coupled with the two-dimensional high-precision hydrodynamic model. • Finite volume method (FVM) with Godunov type is adopted to solve the two-dimensional hydrodynamic process. • Habitat suitability model is constructed by habitat suitability index based on IFIM theory. • The introduction of GPU acceleration technology greatly improves the simulation efficiency. The habitat suitability model is coupled with the two-dimensional high-precision hydrodynamic model in this paper. In the model, finite volume method (FVM) with Godunov type is adopted to solve the two-dimensional hydrodynamic process, which has good robustness and second-order temporal and spatial accuracy; Habitat suitability model is constructed by habitat suitability index based on IFIM theory. Meanwhile, the introduction of GPU acceleration technology greatly improves the simulation efficiency. Combined with the results of River2D, the results of this model have good accuracy. The model was applied to simulate the spawning habitat of Gymnocypris eckloni in the lower reaches of a hydropower station in the Upper Yellow River, and the reasonable discharged flow of hydropower station required for a good spawning habitat was 74 m3/s. It increased by 53.377% compared with the average annual discharge in May of the natural river. The evaluation of the spawning habitat of Gymnocypris eckloni provides a scientific basis for protecting the integrity of river ecosystem in this paper. [Display omitted] [ABSTRACT FROM AUTHOR]

Abstract: This paper describes an individual-based model, MORPH, that has been designed to predict the effect of environmental change on foraging animal populations. The key assumptions of MORPH are that individuals within populations behave in order to maximise their perceived fitness, but that perceived fitness may not always be positively related to the actual chances of survival and reproduction. MORPH has been parameterised for coastal birds on several European sites and predicted the effect of environmental change, caused by factors such as habitat loss, disturbance from humans and sea-level rise, on the survival and body condition of these species. However, MORPH contains a basic framework to describe animal physiology and foraging behaviour, and the distribution and abundance of the resources required by these animals. Therefore, MORPH is not restricted to coastal birds, and is potentially applicable to a wider range of systems. To be applied to a forager system, MORPH requires parameters describing (i) the distribution of the food supply and how food quality and abundance changes through time; (ii) the rate at which foragers consume food given the abundance of food and competitors; (iii) the amount of food the forager must consume each day to survive; (iv) the distribution and seasonal changes in other factors which influence the foraging behaviour and survival of foragers. The purpose of this paper is to (i) describe MORPH, (ii) give examples of its application, (iii) describe the types of systems to which MORPH can be applied, and (iv) publish its source code and a user guide. [Copyright &y& Elsevier]

Abstract: This paper is devoted to an explanation of the mathematical model of a population distribution in a habitat. The spatial distribution is considered as a function of factors affecting a population. The model includes both linear and non-linear modeling mechanisms, which allow description of a variety of environmental situations observed in nature. All components of the model are conceptually connected with one another and based on one methodological basis. This allows development of the integrative picture of mathematical modeling of spatial population dynamics. The theoretical portion of the paper presents logical structures and mathematical equations for numeric modeling of a population distribution in a habitat. The practical portion describes the application of the integrative model to the study of the spatial distribution of fry of Brown trout (Salmon trutta L.) in the experimental conditions. The integrative model represents a standardized and reliable method for studying spatial population dynamics applicable to a variety of populations of different species. This method offers a comprehensive algorithm of steps which one should take in order to predict spatial distribution of organisms. It also outlines the information necessary for mathematical modeling of spatial population dynamics. Through systematization of the modeling process, the integrative model aims to enhance the understanding and use of mathematical modeling in environmental sciences and ecology in general. [Copyright &y& Elsevier]

Abstract: Crustacean dormancy, like diapause in insects and seeds, is a remarkable and not always clear life-history event. Many problems, ranging from the question of frequency of diapause in the distinct taxonomic groups, to the possibility of the identification of features that define dormancy, have been posed and need investigation. This paper is concerned with one of the main questions in the field, namely the problem of studying the relationships between environment unpredictability and dormancy. This result explores, in particular, both rigorously and empirically, the well known prediction that says that a decline of the hatching rate should correspond to an increase of unpredictability of the habitat. This theoretical result was formulated by Cohen in 1966, and its validity in the original form is, also presently, a matter of discussion. Despite the growth of the literature on the subject, in fact, almost no advances have been made in relating environmental findings to the theory and this has resulted, mainly, from the difficulty of defining a good measure of habitat unpredictability. In this paper we propose an interpretation of this quantity in terms of fundamentals of Shannon information statistics, and by using this idea, we verify the validity of Cohen''s original statement on experimental data of three different populations of Chirocephalus diaphanus Prévost, 1803 (Crustacea, Anostraca), inhabiting both semi-permanent and temporary pools in Italy. We find an encouraging fitting between experimental and theoretical predictions and this can be interpreted, almost for the case under study, as an indication that Cohen law should hold. [Copyright &y& Elsevier]

This paper describes a physically based three-dimensional bioenergetic model for prediction of physical habitat quality for drift-feeding juvenile salmonids in a river. A three-dimensional Computational Fluid Dynamics (3D-CFD) model is used to simulate hydraulic patterns in a 50 m reach of the Bere stream, Dorset, UK. This information is then combined with a bioenergetic model that uses behavioural and physiological relationships to quantify the spatial pattern of energy gain when drift feeding. The model was tested by comparing patterns of predicted energy intake with observed habitat use by juvenile salmonids at different times of day.Hydraulic measurements or predictions are required as input to bioenergetic models to calculate the foraging range of the fish. Horizontal and vertical velocity gradients can be high and variable in shallow streams with complex topography and roughness zones. In this paper, a three-dimensional hydraulic model enables more realistic calculation of the foraging area of the fish. This takes account of the complexity of horizontal and vertical velocity gradients. Numerical experiments are used to demonstrate the sensitivity of energetic gain to changes in the method of calculating foraging area. Results support the hypothesis that feeding fish preferentially select areas of high energy gain, but move to areas of lower velocity when resting. [Copyright &y& Elsevier]

• The ecohydraulic modeling framework is a valuable tool for assessing fish ecology in dammed rivers. • Cascade dam construction could fragment spawning site habitats and reduce fish population abundance in the tailwater zone of the main stream. • Spawning site habitats would improve, leading to an increase in fish population abundance in the backwater zone of tributaries. • The effects of cascade dam construction on endemic fish habitat and population status depend on spawning site location, fish species, and life stages. Cascade dam constructions will alter the habitat of spawning sites and affect fish population in the Lancang River basin. This paper examines the impacts of cascade dam construction on four spawning sites, focusing on two co-distributed and endemic fish species: Schizothorax prenanti and Schizothorax davidi. An ecohydraulic modeling framework that combined hydro-morphodynamic, habitat, and population models was used to investigate changes in habitat quality and fish population under two scenarios: no-dam and with-dam. Fish habitat quality was evaluated using the habitat suitability index, and population fluctuations were assessed by the abundance and density of fish populations at all life stages. The simulation results indicated that cascade dam construction would fragment the spawning site habitat in the tailwater zone of the main stream and result in a decrease in fish population abundance and density. Conversely, spawning site habitats in backwater zone of tributaries would improve, and fish population abundance and density would increase. Additionally, the simulation results showed that the magnitude of fish population variations varied by species and life stages. These results highlight the different responses of spawning site location, fish species, and life stages to dam construction, which can help identify areas of the habitat with higher potential for finer-scale endemic fish conservation and recovery efforts. This study provides a comprehensive framework tool for fish ecological evaluation in dammed rivers, which has the potential to assist decision-makers involved in river ecosystem ecological conservation. [Display omitted] [ABSTRACT FROM AUTHOR]

• The Chesapeake Bay is the largest, most productive, and most biologically diverse estuary in the continental United States. • Pressures from human population growth and agricultural intensification have led to excessive nutrient and sediment inputs. • The Chesapeake Bay program partnership has been developing and applying a complex modeling system as a planning tool to inform management decisions and Bay restoration efforts. • This paper provides a description of the modeling system along with specific recommendations that emerged from a 2018 workshop designed to inform future model development. The Chesapeake Bay is the largest, most productive, and most biologically diverse estuary in the continental United States providing crucial habitat and natural resources for culturally and economically important species. Pressures from human population growth and associated development and agricultural intensification have led to excessive nutrient and sediment inputs entering the Bay, negatively affecting the health of the Bay ecosystem and the economic services it provides. The Chesapeake Bay Program (CBP) is a unique program formally created in 1983 as a multi-stakeholder partnership to guide and foster restoration of the Chesapeake Bay and its watershed. Since its inception, the CBP Partnership has been developing, updating, and applying a complex linked modeling system of watershed, airshed, and estuary models as a planning tool to inform strategic management decisions and Bay restoration efforts. This paper provides a description of the 2017 CBP Modeling System and the higher trophic level models developed by the NOAA Chesapeake Bay Office, along with specific recommendations that emerged from a 2018 workshop designed to inform future model development. Recommendations highlight the need for simulation of watershed inputs, conditions, processes, and practices at higher resolution to provide improved information to guide local nutrient and sediment management plans. More explicit and extensive modeling of connectivity between watershed landforms and estuary sub-areas, estuarine hydrodynamics, watershed and estuarine water quality, the estuarine-watershed socioecological system, and living resources will be important to broaden and improve characterization of responses to targeted nutrient and sediment load reductions. Finally, the value and importance of maintaining effective collaborations among jurisdictional managers, scientists, modelers, support staff, and stakeholder communities is emphasized. An open collaborative and transparent process has been a key element of successes to date and is vitally important as the CBP Partnership moves forward with modeling system improvements that help stakeholders evolve new knowledge, improve management strategies, and better communicate outcomes. [ABSTRACT FROM AUTHOR]

Although tropical rainforests preserve high levels of biodiversity, they are among the most threatened ecosystems globally due to large-scale fragmentation as a result of anthropogenic activities. Overall, fast human-driven habitat destruction is suspected to be one of the major causes of species extinction. The mosaic of vegetation types, which contributes to the incredible diversity of the tropics is highly impacted by large-scale fragmentation. The main causes of such habitat fragmentation are selective logging for valuable timber and agricultural clearance. The knowledge of the short and long-term effects of removing selected species in the tropical rainforests are scarce and need to be further investigated. Some studies about the effects of tropical forest disturbance in the short term have been conducted, but in the long term, there is limited knowledge. In this paper, I consider a system of coupled ordinary differential equations (ODEs) that modelled the dynamics of tropical rainforest subject to selective logging to understand how and why weeds and vine displace and limit tree species. From the empirical data collected on canopy height and plant diversity and the model proposed, I have the evidence of a decreasing tree diversity in tropical forests subject to management in comparison with to the same but untouched forests. [ABSTRACT FROM AUTHOR]

Forest biomass is a renewable resource that is increasingly utilised for bioenergy purposes in Sweden, which along with the extraction of industrial wood may conflict with biodiversity conservation. The aim of this paper is to present a method for integrated sustainability assessment of forest biomass extraction, particularly from bioenergy and biodiversity perspectives. The landscape simulator LandSim was developed and linked with models for the assessment of biomass yields and habitat networks representing prioritised biodiversity components. It was applied in a case study in Kronoberg County in southern Sweden. Forest growth and management were simulated for the period 2010–2110, following two land zoning scenarios, one applying even-aged forest management on all forest land except for protected areas (EAF-tot), and one applying continuous cover forest management on parts of the forest land, combined with protected areas and an intensified even-aged management on the other parts (CCF-int). The EAF-tot scenario implied higher yields of biomass feedstock for bioenergy, the CCF-int scenario only giving 66% of that yield, while the CCF-int scenario performed substantially better when it came to the habitat network indicators, if habitat suitability was ensured. Conclusively, the case study confirmed that the modelling framework of the LEcA tool, linking the landscape simulator LandSim with the biomass yield assessment and the habitat network model can be used for integrating main policy concerns when assessing renewable energy options. [ABSTRACT FROM AUTHOR]

Coastal ecosystems put up a number of impacts from human activities in the sea; the most recent is fish farming, interacting synergistically with the other impacts and with the natural structure and dynamics of the coastal ecosystem. In the Mediterranean Sea, the number of fish farms has increased dramatically from early ‘80s in coastal waters, releasing a substantial amount of organic matter, modifying the habitat and communities beneath cages and changing the spatio-temporal distribution of species. Among all the effects derived from fish farming, escape events of cultured fish are a relevant issue for management given their potential impact over wild counterparts in terms of habitat and food competition, genetic flow, biodiversity, spread diseases or parasites, and interaction with local fisheries, decreasing the price of the catches. This paper shows the first approach to model the temporal trends of biomass and yields of escapes from aquaculture by means of an EwE model. Three levels of escapes (×1, ordinary level: 5000 ind year −1 fish farm −1 , corresponding to 1.31 t year −1 ; massive event: ordinary level × 91; total destruction of fish farm: ordinary level × 1800) and four levels of fishing effort (ordinary E, ×2, ×5, ×10) were modelled as mechanism to recapture escapees. Temporal variation of biomass and yield is used to define how long should be maintained the effort to catch escapees. The total destruction of a fish farm generates the higher increase of escapees' landings, dissapearing in less than 6 months if fishing effort reach 10-fold the ordinary fishing effort. Differences among revenues from recaptures and derived expenses were always negative but tending to be greater for low levels of fishing effort and/or levels of escapes which means no fishery can be expected to be maintained by escapes. In general, fleets benefit from escapees in terms of yield but gains will depend on how escapees affect either positively or negatively the value of the catch. Simulations using EwE models may result a useful tool to design suitable recapture plans of escapees. [ABSTRACT FROM AUTHOR]

Chronosequences of glacier retreat are useful for investigating primary successions over time periods that are longer than direct observation would permit. In this context, space-for-time substitution studies have been applied to assess the effects of climate change on invertebrate assemblages. However, population dynamics of insect species following retreating glaciers has been under-investigated until now due to difficulty in applying capture-recapture methods and correctly identifying species in the field. Removal sampling methods are commonly used, but imperfect detectability is rarely accounted for in the analytical framework. In this paper we study the effects of environmental drivers of spatial, and indirectly temporal, variation in population size and sex-ratio of cold-adapted insects through a hierarchical framework for abundance. We show the importance of a metapopulation design, where samples are replicated in space and time, to model data from small and scattered populations, typically present in habitats with climate-mediated selective pressure like those along glacier forelands. This scattered distribution can influence the observation or sampling process and thus species detectability. Our results show that glacier retreat differently affects species-specific changes of population size and sex ratio along the chronosequence, even if the species are taxonomically related. Small-sized populations occur on the glacier surface, near the glacier front, and in sites deglaciated for at least 100 yrs. On the contrary, larger populations occupy sites deglaciated for more than 20 yrs, but less than 100 yrs. This pattern is described by the concave relationship of abundance with both species richness of other arthropods (proxy of habitat complexity) and soil organic matter (proxy of soil maturity). Sex-ratio showed opposite patterns in relation to time since deglaciation. Hierarchical models that estimate abundance of spatially distinct subpopulations represent useful tools for accurately assessing changes in species abundance following climate change while accounting for possible bias associated with imperfect detectability, an issue which is often neglected in space-for-time substitution studies on invertebrates and, more generally, in studies involving pitfall trapping. [ABSTRACT FROM AUTHOR]

Predicting cumulative effects is an important challenge of theoretical and management ecology. If a population will be exposed to multiple stressors (e.g., toxins, introduced competitors, climate change), will their cumulative effects be independent and hence multiplicative (the population survival rates due to each stressor can be multiplied together to determine the total reduction in abundance), synergistic (cumulative effects are greater than multiplicative), or antagonistic (stressors offset each other so cumulative effects are less than multiplicative)? Further, the effects of each stressor can vary with such factors as habitat quality, population density, and weather. It is difficult to predict cumulative effects with traditional population-level models because such models must assume the type and strength of stressor interactions a priori , and measuring stressor effects and interactions empirically is rarely practical. Instead, we used an individual-based model in which cumulative effects emerge from how each stressor affects the growth and survival of individuals, and how individuals interact. Our model is in fact based on theoretical concepts explored in the landmark 1980 paper of DeAngelis et al. (Cannibalism and size dispersal in young-of-the-year largemouth bass: experiment and model, Ecol. Model. 8, 133–148): in a community of fish that eat each other, initial differences in size among individuals have strong effects on subsequent abundance and size distributions. We model survival and growth of juvenile Colorado pikeminnow ( Ptychocheilus lucius ) during their first year, and two stressors they are subject to. The first stressor is a daily cycle of flow fluctuations imposed by an upstream hydroelectric dam; these fluctuations affect habitat area, food supply, and temperature, which then affect juvenile fish growth. Second is an introduced fish species that competes with pikeminnow for food, while both species can prey on each other via the size-based mechanism described by DeAngelis et al. We simulated the effects of the 36 combinations of six levels of these two stressors in each of 28 sites and weather year to produce 840 scenarios, using 7 weather year datasets as replicates. Emergent cumulative effects were multiplicative in 69% of these scenarios, synergistic in 22%, and antagonistic in 9%. Therefore, any a priori assumption about stressor interactions would be wrong in many situations. Synergistic effects were most common in deeper and larger habitats favorable to the introduced species; antagonistic effects were most common in smaller habitats where the introduced species had low growth, because flow fluctuations further reduced the small food supply. [ABSTRACT FROM AUTHOR]

Pollination by bees is important for food production. Recent concerns about the declines of both domestic and wild bees, calls for measures to promote wild pollinator populations in farmland. However, to be able to efficiently promote and prioritize between measures that benefit pollinators, such as modified land use, agri-environment schemes, or specific conservation measures, it is important to have a tool that accurately predicts how bees use landscapes and respond to such measures. In this paper we compare an existing model for predicting pollination (the “Lonsdorf model”), with an extension of a general model for habitat use of central place foragers (the “CPF model”). The Lonsdorf model has been shown to perform relatively well in simple landscapes, but not in complex landscapes. We hypothesized that this was because it lacks a behavioral component, assuming instead that bees in essence diffuse out from the nest into the landscape. By adding a behavioral component, the CPF model in contrast assumes that bees only use those parts of the landscape that enhances their fitness, completely avoiding foraging in other parts of the landscape. Because foraging is directed toward the most rewarding foraging habitat patches as determined by quality and distance, foraging habitat will include a wide range of forage qualities close to the nest, but a much narrower range farther away. We generate predictions for both simple and complex hypothetical landscapes, to illustrate the effect of including the behavioral rule, and for real landscapes. In the real landscapes the models give similar predictions for visitation rates in simple landscapes, but more different predictions in heterogeneous landscapes. We also analyze the consequences of introducing hedgerows near a mass-flowering crop field under each model. The Lonsdorf model predicts that any habitat improvement will enhance pollination of the crop. In contrast, the CPF model predicts that the hedgerow must provide good nesting sites, and not just foraging opportunities, for it to benefit pollination of the crop, because good forage quality alone may drain bees away from the field. Our model can be used to optimize pollinator mitigation measures in real landscapes. [ABSTRACT FROM AUTHOR]

The giant squid ( Architeuthis ) has been reported since even before the 16th century, and has recently been observed live in its habitat for the first time. Among the species belonging to this genus, Architeuthis dux has received special attention from biologists. The distribution of this species is poorly understood, as most of our information stems from stranded animals or stomach remains. Predicting the habitat and distribution of this species, and more in general of difficult to observe species, is important from a biological conservation perspective. In this paper, we present an approach to estimate the potential distribution of A. dux at global scale, with relative high resolution (1-degree). Our approach relies on a complex preparation phase, which improves the reliability of presence, absence and environmental data correlated to the species habitat. We compare our distribution with those produced by state-of-the-art approaches (MaxEnt and AquaMaps), and use an expert-drawn map as reference. We demonstrate that our model projection is in agreement with the expert's map and is also compliant with several biological assessments of the species habitat and with recent observations. Furthermore, we show that our approach can be generalized as a paradigm that is applicable to other rare species. [ABSTRACT FROM AUTHOR]

Agricultural practice is one of the most important factors leading to biodiversity loss. EU policies addressing this problem involve the provision of incentives for agri-environmental measures (AEM) and setting of targets for AEM on the national scale (e.g. for the amount of organic farming according to the German sustainability strategy), as well as monitoring their success. For AEM to most efficiently target, implement and monitor, they require comparable evaluation of results, describing their quantitative effects on biodiversity and nature conservation. However, there is a dearth of regional data about species and habitats, parts of biodiversity that are relevant for nature conservation. Thus, quantitative analyses are not typically feasible. Furthermore, impacts of agricultural practices on biodiversity cannot be analysed and evaluated merely from individual cases. Comparisons with average or maximum achievements on different spatial scales (benchmarking) are needed. However, meaningful state and pressure indicators are lacking for modelling the nature conservation value of agricultural fields and the consequences of changing pressures from agricultural practice. In this paper we present a model for evaluating the nature conservation value of field habitats based on projected field flora species richness. We propose a combination of an existing evaluation scale for habitat types, as the basis of the model setup, with field flora species richness. These are combined to obtain differentiated conservation values of field habitats as a measure of agricultural effects. We defined the field flora species richness as the total number of species on a homogenously managed field minus the cultivated crop. Indicators of the model are farming practices and site conditions. Based on an extensive literature review, these indicators were analysed regarding their influence on the flora species richness. Influences of the farming practices were reflected by the crop type, which was used as key indicator. As an outcome, the influence of conventional farming, organic farming and nature conservation oriented management on flora species richness was quantified. Additionally, we integrated the diversity of crop types and (semi-) natural habitats of the surrounding landscape into the model, in order to consider potential effects of landscape heterogeneity on field flora species richness. The model was applied in a case study at the NUTS 3-regional level (Nomenclature of territorial units for statistics), using the example of the AEM organic farming. In a scenario, we evaluated the possible effects of a complete conversion to organic farming on the assumed flora species richness. The results reveal that the modelling approach can be used to test for the effects of (i) conversion between organic and conventional farming, (ii) changes in crop rotations, and (iii) targeted positioning of organic farming or botanical management agreements in comparison to the spatially untargeted offering of payments. [ABSTRACT FROM AUTHOR]

Abstract: Many organisms are threatened by global climate change, but as sessile organisms, plants are particularly vulnerable. Unable to individually move to areas with more suitable conditions as the climate changes, plants must instead rely on their seeds dispersing far and often in order to migrate fast enough to keep pace with the changing climate. The fragmentation of natural landscapes by clearing for agricultural or urban development, or a species’ requirement for particular soil types or topography, makes this migration even more problematic. The likelihood of a plant species persisting will thus depend on factors such as the rate of climate change, the degree of landscape fragmentation, and also the plant species’ lifecycle, seed production, dispersal, and establishment. This paper presents a dynamic model, called PPunCC (Plant Persistence under Climate Change), that represents the important factors and processes likely to affect a plant species’ capacity to migrate across a landscape fast enough to avoid extinction. We use the model to show that creating large-scale corridors that increase the connectivity of fragmented landscapes through targeted restoration could help species migrate naturally and find suitable environments in new climates. We also examine the effect of varying the key point of vulnerability within its lifecycle between juvenile establishment, adult mortality or seed production and conclude that this has a relatively minor effect on the prognosis for the plant and does not affect the predicted benefits of restoration. [Copyright &y& Elsevier]

This paper addresses the question of optimal phenotypic plasticity as a response to environmental fluctuations while optimising the cost/benefit ratio, where the cost is energetic expense of plasticity, and benefit is fitness. The dispersion matrix Σ of the genes’ response (H =ln|Σ|) is used: (i) in a numerical model as a metric of the phenotypic variance reduction in the course of fitness optimisation, then (ii) in an analytical model, in order to optimise parameters under the constraint of limited energy availability. Results lead to speculate that such optimised organisms should maximise their exergy and thus the direct/indirect work they exert on the habitat. It is shown that the optimal cost/benefit ratio belongs to an interval in which differences between individuals should not substantially modify their fitness. Consequently, even in the case of an ideal population, close to the optimal plasticity, a certain level of genetic diversity should be long conserved, and a part, still to be determined, of intra-populations genetic diversity probably stem from environment fluctuations. Species confronted to monotonous factors should be less plastic than vicariant species experiencing heterogeneous environments. Analogies with the MaxEnt algorithm of are discussed, leading to the conjecture that this method may be applied even in case of multivariate but non multinormal distributions of the responses. [Copyright &y& Elsevier]

In this paper we developed a general stage-structured, Leslie-type model, suitable to simulate dynamics of soil arthropods under typical Mediterranean conditions. In order to explore arthropods’ life-history strategies in relation to enhanced spatial heterogeneity of the Mediterranean ecosystems, metapopulation characteristics were considered and different habitat quality regimes, in terms of dominant microclimatic conditions, were taken into account. Environmental stochasticity in temperature and humidity was incorporated into the model, and an elasticity analysis was conducted to quantify contribution of different life-history traits to metapopulation growth rate. The application of the model revealed well-known life-cycle characteristics of Mediterranean arthropods, such as seasonally fluctuating population sizes and skewing phenologies, a fact that confirms models’ reliability. Furthermore, the model seems able to elucidate controversial points of the animals’ life-cycle development, such as the long-term maintenance of populations in the field and the underlying mechanisms related to the adjustment to the specific features of the Mediterranean ecosystem. Subpopulations inhabiting various microsites display different dynamics and the interaction between these subpopulations, via dispersion, seems to be able to ensure stochastic equilibrium for the system. Dispersal appears to play a decisive role, allowing arthropods to conform to spatial severities and habitats fragmentation, rescuing individuals and recolonizing previously extinct habitats. [Copyright &y& Elsevier]

Abstract: Almost all metapopulation modelling assumes that connectivity between patches is only a function of distance, and is therefore symmetric. However, connectivity will not depend only on the distance between the patches, as some paths are easy to traverse, while others are difficult. When colonising organisms interact with the heterogeneous landscape between patches, connectivity patterns will invariably be asymmetric. There have been few attempts to theoretically assess the effects of asymmetric connectivity patterns on the dynamics of metapopulations. In this paper, we use the framework of complex networks to investigate whether metapopulation dynamics can be determined by directly analysing the asymmetric connectivity patterns that link the patches. Our analyses focus on “patch occupancy” metapopulation models, which only consider whether a patch is occupied or not. We propose three easily calculated network metrics: the “asymmetry” and “average path strength” of the connectivity pattern, and the “centrality” of each patch. Together, these metrics can be used to predict the length of time a metapopulation is expected to persist, and the relative contribution of each patch to a metapopulation''s viability. Our results clearly demonstrate the negative effect that asymmetry has on metapopulation persistence. Complex network analyses represent a useful new tool for understanding the dynamics of species existing in fragmented landscapes, particularly those existing in large metapopulations. [Copyright &y& Elsevier]

Abstract: Compared to population growth regulated by local conditions, dispersal has been underappreciated as a central process shaping the spatial distribution of populations. This paper asks: (a) which conditions increase the importance of dispersers relative to local recruits in determining population sizes? and (b) how does dispersal influence the spatial distribution patterns of abundances among connected populations? We approached these questions with a simulation model of populations on a coupled lattice with cells of continuously varying habitat quality expressed as carrying capacities. Each cell contained a population with the basic dynamics of density-regulated growth, and was connected to other populations by immigration and emigration. The degree to which dispersal influenced the distribution of population sizes depended most strongly on the absolute amount of dispersal, and then on the potential population growth rate. Dispersal decaying in intensity with distance left close neighbours more alike in population size than distant populations, leading to an increase in spatial autocorrelation. The spatial distribution of species with low potential growth rates is more dependent on dispersal than that of species with high growth rates; therefore, distribution modelling for species with low growth rates requires particular attention to autocorrelation, and conservation management of these species requires attention to factors curtailing dispersal, such as fragmentation and dispersal barriers. [Copyright &y& Elsevier]

In this paper, I argue that many ecological ideas that are typically expressed in terms of ‘patches’ of habitat can be framed more generally in terms of spatial correlation of resource availability. This avoids practical difficulties in the definition of a ‘patch’ in a given study. The idea is illustrated by reference to some existing models of territoriality, and by revisiting a model for the resource dispersion hypothesis. As an example, I show how this perspective resolves one of the difficulties of interpretation in a study of spatial organization in urban foxes. [Copyright &y& Elsevier]

In European grasslands, livestock grazing is a key driver of habitat quality. However, the specific grazing regimes that favour habitat quality and ensure biodiversity conservation remain largely unknown. This paper develops a dynamic model to predict how livestock grazing may be used to sustain a bird community without penalizing cattle feeding. The model focuses on a grassland grazed by cattle which is also the breeding habitat of three wader species. It integrates the dynamics of a sward, controlled through grazing, and that of three bird populations. Viability theory and dynamic programming are used to reveal viable grazing strategies that ensure the creation of two levels of habitat quality (homogeneous and heterogeneous) whilst ensuring cattle feeding. Viable grazing strategies are ranked through an economic criterion and referred as ecologic or economic grazing. Then using viability population analysis, we assess the extinction risk of the wader community in both levels of habitat quality. Globally, grazing had a more positive effect on the wader community than did the no-grazing scenario. Both levels of habitat quality could be generated through both grazing strategies corresponding to contrasting temporal distributions of livestock densities. Grazing strategies resulted in differential community viability. Ecologic grazing always ensured wader community maintenance, whatever the level of habitat quality targeted. This was not the case for economic grazing which reduced the wader community to two species. Species response showed two contrasting patterns, with a more dramatic decline for lapwings than redshanks in both the no-grazing and heterogeneous habitat quality scenarios. This may lead to conservation problems because of the relationship between population size and probability of extinction observed for lapwings. [Copyright &y& Elsevier]

In a dynamic landscape the rate of change in landscape structure can be even more important than the degree of patch isolation in determining population survival and abundance. If the changes in landscape structure occur at an “extremely” high rate (as in some anthropogenic changes), dispersal may not be able to keep up with the high rates of local extinction. Understanding impacts of such changes is thus crucial for determination of the driving factors for species survival in agricultural landscapes and for elaboration of conservation plans. Here we studied the effects of landscape dynamics under local farming practices on movements and population dynamics of a diurnal butterfly Maniola jurtina L. (Satyridae), specifically the impacts of regular yearly mowing on butterfly movements, distribution and abundance over many years. We used an existing simulation model, extended it by the effect of the intensity of disturbance (amount of mown habitat) and timing of disturbance within the reproductive season on the butterfly population dynamics, and validated on our data from a field experiment using a mark-release method. Increase in the amount of disturbed habitats in the landscape led to an increasing isolation of the remnant habitat patches for butterflies. This resulted in decreasing movements between habitat patches and ultimately to population decline, especially in less accessible patches. In the past, influence of landscape dynamics on species survival was usually considered at the long-term scale. Our results demonstrate that the short time scale landscape dynamics induced by farming practices should not be neglected. The novelty of this paper stems in the combination of inclusion of landscape dynamics, of realistic dispersal strategies of individuals, and of considering real landscapes. The effect of man-induced landscape changes on population persistence of a real species in a real landscape has not been possible to be studied by any of the previously developed models. [Copyright &y& Elsevier]

The search for natural sweeteners has prompted intensive research on plants with sweetening properties. Dioscoreophyllum cumminsii (Stapf) Diels is a dioecious, semelparous annual liana found as a late successional, understorey species in West African semi-deciduous forests. The fruits and subterranean tubers are intensely sweet and are both edible. The sweetening substance in D. cumminsii is a protein (monellin), which is 3000 times as sweet as sugar. Unfortunately, it is one of the threatened plant species in the country because of massive habitat loss and fragmentation. Conservation is now needed as a salvage programme. Population size is a major determinant of extinction risk. This has prompted the application of growth and population dynamics models to viability analysis of wild species. The aim of population viability analysis (PVA) is to determine the minimum viable population size (MVP) or area (MVA) of a particular species. In this paper, MVP was estimated for D. cumminsii using genetic models. The models simulated minimum effective population size of 6040individualsha−1 in the ratio of 5032 males to 1008 females. This suggests that to retain evolutionary potential, D. cumminsii requires an effective population size of more than the 500–5000 range considered adequate for many other species. [Copyright &y& Elsevier]

Abstract: Wildlife populations typically are described by Markovian models, with population dynamics influenced at each point in time by current but not previous population levels. Considerable work has been done on identifying optimal management strategies under the Markovian assumption. In this paper we generalize this work to non-Markovian systems, for which population responses to management are influenced by lagged as well as current status and/or controls. We use the maximum principle of optimal control theory to derive conditions for the optimal management such a system, and illustrate the effects of lags on the structure of optimal habitat strategies for a predator–prey system. [Copyright &y& Elsevier]

Abstract: Models predicting species spatial distribution are increasingly applied to wildlife management issues, emphasising the need for reliable methods to evaluate the accuracy of their predictions. As many available datasets (e.g. museums, herbariums, atlas) do not provide reliable information about species absences, several presence-only based analyses have been developed. However, methods to evaluate the accuracy of their predictions are few and have never been validated. The aim of this paper is to compare existing and new presence-only evaluators to usual presence/absence measures. We use a reliable, diverse, presence/absence dataset of 114 plant species to test how common presence/absence indices (Kappa, MaxKappa, AUC, adjusted D 2) compare to presence-only measures (AVI, CVI, Boyce index) for evaluating generalised linear models (GLM). Moreover we propose a new, threshold-independent evaluator, which we call “continuous Boyce index”. All indices were implemented in the BIOMAPPER software. We show that the presence-only evaluators are fairly correlated (ρ >0.7) to the presence/absence ones. The Boyce indices are closer to AUC than to MaxKappa and are fairly insensitive to species prevalence. In addition, the Boyce indices provide predicted-to-expected ratio curves that offer further insights into the model quality: robustness, habitat suitability resolution and deviation from randomness. This information helps reclassifying predicted maps into meaningful habitat suitability classes. The continuous Boyce index is thus both a complement to usual evaluation of presence/absence models and a reliable measure of presence-only based predictions. [Copyright &y& Elsevier]

Abstract: Heterogeneity of agricultural landscapes is supposed to be of significant importance for species diversity in agroecosystems. However, land use pattern changes may lead to an increase in suitable habitat for some species, but to habitat deterioration for other species with opposing habitat requirements. To investigate the effects of land use changes on different species’ habitat suitabilities and to allow a trade off between management objectives, we applied a spatial optimization model. In this paper we present a new approach that integrates a neighbourhood dependent multi-species evaluation of land use patterns into an optimization framework for generating goal-driven scenarios. It is implemented using a genetic algorithm approach that aims at maximizing habitat suitability of three selected bird species (Middle-Spotted Woodpecker, Wood Lark, Red-Backed Shrike) by identifying optimum agricultural land use patterns. The evaluation of habitat suitability is based on landscape metrics calculated within the species’ home ranges to incorporate the effects of species responses to landscape pattern on a territorial scale. The main focus of this study is to explore the potential of this approach for conservation management on the basis of a case study. We investigate where habitat requirements oppose, where they coincide and how a landscape optimized simultaneously for all target species should be characterized. We found that all species would benefit from an increase of deciduous and coniferous forest, a decrease of cropland and grassland in the study area and more heterogeneous land use patterns (smaller patches, more diversity of land use types). Habitat requirements of Red-Backed Shrike contrast most to those of the other two species with respect to landscape composition and configuration. [Copyright &y& Elsevier]

Abstract: This paper further explores a previously developed spatially explicit model that incorporates the effects of habitat topology and abiotic (climate) suitability on tick population density. The primary focus was to provide a parameterization of host dispersal, which is involved in the calculation of two critical parameters of the model, namely patch Traversability and Recruitment. We used a dispersal kernel that can accommodate a variety of dispersal patterns, varying the proportion of dispersing hosts as a function of patch size (), and the dispersing range of hosts (r). Model values were compared with a set of tick densities from an actual landscape. Correlations were very poor for low and r, but greatly improved (R =0.8–0.96, p =0.0001) for high values of these parameters. This suggests the significance of long-range dispersers to keep this actual network of tick metapopulation patches. Further results of the dispersal kernel hint at the importance of short-range hosts in the maintenance of neighbouring, small, well-connected patches. This abundance model involving climate suitability, habitat topology and host dispersal contributions, was applied to the tick Ixodes ricinus in a large area of northern Spain. The Recruitment at the patch level was calculated and used to forecast abundance of ticks across the study area. Sensitivity of every patch was defined as the response-range of Recruitment to quantitative changes in climate and topological features of the patch. To show how changes in the patch characteristics can dramatically alter the landscape composition and thence tick abundance, simulations were conducted in which the real landscape was modified by removing patches based on selected habitat features. The ecosystem was affected to the greatest extent by removal of patches of high sensitivity, large size, and high Recruitment. The proposed framework has particular utility for epidemiological studies aimed at evaluating the impact of climate change or habitat management on the survival of tick populations, and the health risks posed by ticks. [Copyright &y& Elsevier]

Abstract: Niche construction refers to the capacity of organisms to construct, modify, and select important components of their local environments (such as nests, burrows, chemicals, and nutrients), consequently modifying the sources of natural selection in their environment. These modifications can have profound effects on the genetic dynamics and structure of population. In the paper, we construct a 2D individual-based lattice model of niche construction, with deterministic and probabilistic transition rules, and present the typical dynamics and spatial structure of polymorphism, environmental resource and genotype frequencies. The effect of local extinction on polymorphism maintenance is also discussed. In simulation, both the deterministic and the probabilistic models can generate regular stripe, lumpiness or uniform structure in space, which supports a stable polymorphism even without heterozygote superiority. With habitat deterioration, niche construction accelerates the formation of steady polymorphism and impedes the harmful influence of environment on the population, which might indirectly embody a life-history strategy of organism under the unfavorable environment. Results are very sensitive to the parameters that represent different evolutionary and ecological factors and interactions in the models. These results suggest that niche construction can lead to coexistence with alternative polymorphism through genotype–environment feedback. [Copyright &y& Elsevier]

Abstract: Concerns about declines in forest biodiversity underscore the need for accurate estimates of the distribution and abundance of organisms at large scales and at resolutions that are fine enough to be appropriate for management. This paper addresses three major objectives: (i) to determine whether the resolution of typical air photo-derived forest inventory is sufficient for the accurate prediction of site occupancy by forest birds. We compared prediction success of habitat models using air photo variables to models with variables derived from finer resolution, ground-sampled vegetation plots. (ii) To test whether incorporating spatial autocorrelation into habitat models via autologistic regression increases prediction success. (iii) To determine whether landscape structure is an important factor in predicting bird distribution in forest-dominated landscapes. Models were tested locally (Greater Fundy Ecosystem [GFE]) using cross-validation, and regionally using an independent data set from an area located ca. 250km to the northwest (Riley Brook [RB]). We found significant positive spatial autocorrelation in the residuals of at least one habitat model for 76% (16/21) of species examined. In these cases, the logistic regression assumption of spatially independent errors was violated. Logistic models that ignored spatial autocorrelation tended to overestimate habitat effects. Though overall prediction success was higher for autologistic models than logistic models in the GFE, the difference was only significantly improved for one species. Further, the inclusion of spatial covariates did little to improve model performance in the geographically discrete study area. For 62% (13/21) of species examined, landscape variables were significant predictors of forest bird occurrence even after statistically controlling for stand-level variability. However, broad spatial extents explained less variation than local factors. In the GFE, 76% (16/21) of air photo and 81% (17/21) of ground plot models were accurate enough to be of practical utility (AUC>0.7). When applied to RB, both model types performed effectively for 55% (11/20) of the species examined. We did not detect an overall difference in prediction success between air photo and ground plot models in either study area. We conclude that air photo data are as effective as fine resolution vegetation data for predicting site occupancy for the majority of species in this study. These models will be of use to forest managers who are interested in mapping species distributions under various timber harvest scenarios, and to protected areas planners attempting to optimize reserve function. [Copyright &y& Elsevier]

Abstract: This paper describes an approach for conducting spatial uncertainty analysis of spatial population models, and illustrates the ecological consequences of spatial uncertainty for landscapes with different properties. Spatial population models typically simulate birth, death, and migration on an input map that describes habitat. Typically, only a single “reference” map is available, but we can imagine that a collection of other, slightly different, maps could be drawn to represent a particular species’ habitat. As a first approximation, our approach assumes that spatial uncertainty (i.e., the variation among values assigned to a location by such a collection of maps) is constrained by characteristics of the reference map, regardless of how the map was produced. Our approach produces lower levels of uncertainty than alternative methods used in landscape ecology because we condition our alternative landscapes on local properties of the reference map. Simulated spatial uncertainty was higher near the borders of patches. Consequently, average uncertainty was highest for reference maps with equal proportions of suitable and unsuitable habitat, and no spatial autocorrelation. We used two population viability models to evaluate the ecological consequences of spatial uncertainty for landscapes with different properties. Spatial uncertainty produced larger variation among predictions of a spatially explicit model than those of a spatially implicit model. Spatially explicit model predictions of final female population size varied most among landscapes with enough clustered habitat to allow persistence. In contrast, predictions of population growth rate varied most among landscapes with only enough clustered habitat to support a small population, i.e., near a spatially mediated extinction threshold. We conclude that spatial uncertainty has the greatest effect on persistence when the amount and arrangement of suitable habitat are such that habitat capacity is near the minimum required for persistence. [Copyright &y& Elsevier]

Abstract: Habitat destruction has long been thought to lead the biased extinctions of some species. An interesting and important question is: who will be the first to become extinct in communities during habitat destruction, the inferior competitors or the superior competitors? Firstly, we demonstrate, by means of numerical simulation, an “odds–even” evolution rule: after extinction of a few dominant species following large habitat destruction, the rest of the community shows a spontaneous hierarchical self-organization, i.e., the species with either odd or even numbers become more abundant. Secondly, we show that for moderate or small habitat destruction, it is the poor competitor(s) that goes extinct first. Lastly, some ecological orders of persisting species of different metapopulation (community) during habitat destruction are ranged in the paper. These ecological orders of persisting species show that there exists a special ecological position in different metapopulation system (community) in which the species will evolve into the strongest (best) competitor during habitat destruction. [Copyright &y& Elsevier]

A nonlinear n-population metapopulation model, which can describe the nonlinear relationship between one species and other species or between one species and the habitat, is presented in this paper. By simulation and mathematics analysis, we discover that species possess an ability to control or avoid extinction during habitat destruction. Any species in n-population metapopulation can increase (decrease) the influence of habitat destruction if it agrees (disagrees) with the environment, and it also can increase (decrease) the proportion of sites occupied by all species by harmonizing (not harmonizing) with the other species. [Copyright &y& Elsevier]

In this paper, we address three aspects of the brown bear population in Slovenia: its size (and its evolution over time), its spatial expansion out of the core area, and its potential habitat based on natural habitat suitability. Data collected through measurement/observation of the bear population and from the literature are used. A model is developed for each aspect. The results are estimates of population size, a picture of the spatial expansion of the population and maps of its optimal and maximal potential habitat (based on natural suitability). Overall, the brown bear population has been increasing since the establishment of a core protective area and has been expanding outside this area. The habitat suitability maps show that there is room for further expansion. Based on habitat suitability and bear population density, as well as human activity and current damage reports, we recommend that the Alps should be temporarily kept free of the bears, until the necessary mitigation measures regarding human–bear conflicts are carried out. On the other hand it is of crucial importance to adapt human activities and improve bear management in the optimal habitat, with which the goals of successful conservation of the species might be achieved. [Copyright &y& Elsevier]

Expert knowledge regarding the distribution of sambar deer (Cervis unicolor) in Lake Eildon National Park (LENP), Victoria was used to build a wildlife habitat model to assist with park management. The paper presents two methods for eliciting expert knowledge. These were a quantitative geographical information system (GIS)-based approach using a customised graphical user interface, and a qualitative approach that uses semi-structured interviews. The GIS approach is valuable as it is objective, repeatable and provides a spatial context for knowledge elicitation. Experts were asked to provide estimates of sambar sightings and predicted densities with the assistance of contextual environmental data including terrain, roads, hydrology and rainfall surfaces. The quantitative knowledge elicitation process did not identify any sambar environmental niches in the Park, and the experts disagreed about the location of likely habitat. On the other hand, the qualitative assessment showed very strong expert agreement and a combination of this information and published literature was used to build a habitat map. The results of the analysis indicate that sambar deer occur throughout the entire Park. It is envisaged that the results can be used as baseline information for population modelling and natural resource management in the Park. Elicitation of knowledge is complicated by a number of factors including computer proficiency and study site familiarity. The relatively large cohort used in this study and the inherent inconsistencies that were encountered indicate that wildlife managers should interpret results carefully from habitat models that use only a relatively small cohort of experts. [Copyright &y& Elsevier]

Most habitat maps are presented as if they were a certain fact, with no indication of uncertainties. In many cases, researchers faced with the task of constructing such maps are aware of problems with the modelling data and of decisions that they make within the modelling process that are likely to affect the output, but they find it difficult to quantify this information. In some cases they attempt to evaluate the modelled predictions against independent data, but the summary statistics have no spatial component and do not address errors in the predictions. It is proposed that maps of uncertainty would help in the interpretation of these summaries, and to emphasize patterns in uncertainty such as spatial clustering or links with particular covariates. This paper reviews the aspects of uncertainty that are relevant to habitat maps developed with logistic regression, and suggests methods for investigating and communicating these uncertainties. It addresses the problems of subjective judgement, model uncertainty and vague concepts along with the more commonly considered uncertainties of random and systematic error. Methods for developing realistic confidence intervals are presented along with suggestions on how to visualize the information for use by decision-makers. [Copyright &y& Elsevier]

A spatial optimization model was formulated and used to maximize black-tailed prairie dog populations in the Badlands National Park and the Buffalo Gap National Grassland in South Dakota. The choice variables involved the strategic placement of limited additional protected habitat. Population dynamics were captured in formulations that reflected exponential population growth combined with the recalcitrant dispersal behavior of this social mammal that is important to many other species. The model results are compared to a previous paper which modeled the black-footed ferret, an aggressive disperser that is dependent upon prairie dogs for food and shelter. [ABSTRACT FROM AUTHOR]

• An ecohydraulic modeling framework is developed. • The framework composed of hydro-morphodynamic, habitat, and population models. • The framework could simultaneous simulated velocity, depth, substrates distribution, suitability index, habitat suitability index, weighted usable area, overall suitability index, fish number and fish density. • The framework provides decision-makers with valuable information to optimize the ecohydraulic management. The ecohydraulic modeling framework in ecological systems includes hydro-morphodynamic, habitat, and population models. In this paper, we proposed an ecohydraulic modeling framework that combines numerical methods and ecological theories to explore the dynamics and interplay between fluvial processes in rivers and the quality of physical habitat and density distribution for fish. The practicality of applying the developed system to ecohydraulics modeling was explored through three case studies and compared with as well as validated using observed data. On the basis of the calculated results, the model system was proven to be efficient in describing population dynamics of the European grayling (Thymallus thymallus. L.) in the Aare River in Switzerland. Satisfactory predictions of the long-term population evolution of the rainbow trout (Oncorhynchus mykiss), brown trout (Salmo trutta) and flannelmouth sucker (Catostomus latipinnis) in the Colorado River in the United States (US) were obtained. Furthermore, the effects of Da-Wei Power Plant construction on the Jiao-Mu River in China on the schizothorax (Schizothorax prenanti) and schizothorax (Racoma) fish species were investigated. The efficiency of fish stocking strategies was evaluated and optimal fish stocking numbers were proposed. The resulting ecohydraulic modeling framework provided very promising results, which highlighted the fundamental role of the temporal variability of hydro-morphological parameters in structuring populations of fish species. Using the ecohydraulic modeling framework to simulate population trends in anticipation of any changes in water management can provide decision-makers with valuable prediction results. [Display omitted] [ABSTRACT FROM AUTHOR]

The objective in this paper is to determine analytically the maximally sustainable pro-rata density-dependent harvest rate of a hypothetical biological species on the spatial boundary of its habitat, which is otherwise a protected zone (i.e. no harvesting of the species is allowed in the interior of its habitat). This is achieved by analysing an abstract mathematical model for the spatio-temporal evolution of the species density over its habitat if it is subjected to a continuum of potential pro-rata density-dependent harvest rates on the spatial boundary. The model takes the form of an initial-boundary value problem involving a reaction-diffusion equation in which the reaction term is a concave function of the population density and Robin boundary conditions are prescribed. A long-time asymptotic analysis of the population density is undertaken by invoking classical results from the theory of eigenproblems. In this way, necessary and sufficient conditions on the pro-rata density-dependent harvest rate are established for the existence of a strictly positive equilibrium attractor of model solutions. Moreover, important necessary properties of this equilibrium attractor are established to guarantee the existence of a density pro-rata harvest rate which maximises the total harvest per unit time at equilibrium. • A model for describing the spatio-temporal evolution of a biological is analysed. • The existence of a unique, positive equilibrium attractor is established. • Important characteristics of the unique equilibrium attractor are established. • Monotonic properties of the unique positive equilibrium solution are established. • A guarantee of the existence of an optimal pro-rata harvest rate is established. [ABSTRACT FROM AUTHOR]

Reconciliation between water uses and sustaining aquatic species populations requires an effort to identify and quantify essential habitat characteristics for ecosystem health and valuation methods to predict ecosystem response to restoration actions. This process is particularly challenging for anadromous fish species such as California's Sacramento River winter-run Chinook salmon, due to their limited geographic range and diverse life history habitat requirements. Tools, such as life-cycle models, are needed to manage population dynamics and quantify the composite effects of processes across space and time. Nevertheless, complex institutions can hinder result interpretation and communication, and limit model use in decision-making. This paper focuses on the federally endangered and endemic Sacramento River winter-run Chinook (Oncorhynchus tshawytscha) by developing a Winter-Run Habitat-based Population Model (WRHAP). WRHAP is a conceptual, freshwater rearing stage model that includes alternative rearing habitats reported in the literature (e.g., floodplains, off-channel and tributaries), defines rules of habitat use based on instream conditions, and incorporates a juvenile growth module that combines bioenergetics modeling with empirical growth rates. Model outputs reasonably follow observed out-migration patterns and provide a realistic smolt size distribution arriving at the San Francisco Bay. This effort demonstrates the importance of currently "non-critical" habitats (as defined by the Endangered Species Act) for juvenile development, with floodplain habitat contributing to a quarter of out-migrating biomass (despite < 18% availability and <10% of total rearing days), and off-channel growth being one of the most sensitive parameters (explaining ~13% of average juvenile weight variance). The model shows the utility of a simple population model to explore relationships between habitat quality/quantity and juvenile development, and to assist water/environmental management and decision-making processes focused on species recovery. [ABSTRACT FROM AUTHOR]

• New model of fecundity-tolerance trade-off for homogeneous habitat. • We show differences in the results coming from MFA and IBM. • Coexistence of species is possible in our model over wide range of parameter's values. Possibility of a coexistence of different species is one of the important issues in ecology. Various mechanism and methods have been proposed to describe biodiversity. In this paper we present and discuss a new model describing the tolerance-fecundity trade-off on a homogeneous habitat, as a mechanisms for sustaining biodiversity. The model is investigated using two techniques – difference equations operating on globally defined functions and computer simulations dealing with individual plants. We show that while the first approach excludes the possibility of a coexistence of species, the second method allows it. We argue that it is the individual treatment of each plant life history which allows for coexistence, while operating on a whole population denies such a possibility. [ABSTRACT FROM AUTHOR]

• Per-capita contribution metrics assess the importance of areas within networks. • The generalized metric is applicable to any spatially structured population. • Equilibrium or transient population dynamics can be investigated. • The usefulness of the metric is demonstrated with four case studies. • The metric can be calculated with provided R code. The ability to classify habitats and movement pathways as sources or sinks is an important part of the decision making process for the conservation of spatially structured populations. Diverse approaches have been used to quantify the importance of habitats and pathways in a spatial network; however, these approaches have been limited by a lack of general applicability across life histories and movement strategies. In this paper, we develop a generalized per-capita contribution metric, the C -metric, for quantifying habitat and pathway quality. This metric is novel in that it can be applied broadly to both metapopulations and migratory species. It allows for any number of age and sex classes, unlimited number of seasons or time intervals within the annual cycle, and for density-dependent parameters. We demonstrate the flexibility of the metric with four case studies: a hypothetical metapopulation, elk of the Greater Yellowstone Ecosystem, northern pintail ducks in North America, and the eastern population of the monarch butterfly. General computer code to calculate the per-capita contribution metric is provided. We demonstrate that the C -metric is useful for identifying source and sink habitats in a network and suggest that the C -metric could be supplemented by some measure of network structure for a more robust description of habitat or pathway importance. [ABSTRACT FROM AUTHOR]