Assessing the suitable habitat for reintroduction of brown trout (Salmo trutta forma fario) in a lowland river: A modeling approach

Huge efforts have been made during the past decades to improve the water quality and to restore the physical habitat of rivers and streams in western Europe. This has led to an improvement in biological water quality and an increase in fish stocks in many countries. However, several rheophilic fish species such as brown trout are still categorized as vulnerable in lowland streams in Flanders (Belgium). In order to support cost‐efficient restoration programs, habitat suitability modeling can be used. In this study, we developed an ensemble of habitat suitability models using metaheuristic algorithms to explore the importance of a large number of environmental variables, including chemical, physical, and hydromorphological characteristics to determine the suitable habitat for reintroduction of brown trout in the Zwalm River basin (Flanders, Belgium), which is included in the Habitats Directive. Mean stream velocity, water temperature, hiding opportunities, and presence of pools or riffles were identified as the most important variables determining the habitat suitability. Brown trout mainly preferred streams with a relatively high mean reach stream velocity (0.2–1 m/s), a low water temperature (7–15°C), and the presence of pools. The ensemble of models indicated that most of the tributaries and headwaters were suitable for the species. Synthesis and applications. Our results indicate that this modeling approach can be used to support river management, not only for brown trout but also for other species in similar geographical regions. Specifically for the Zwalm River basin, future restoration of the physical habitat, removal of the remaining migration barriers and the development of suitable spawning grounds could promote the successful restoration of brown trout.     

Heritable morphological differentiation in salmonids from two distinct stream types

We tested for phenotype-to-habitat associations in brown trout Salmo trutta populations from two ecologically different habitat types; i.e., groundwater and surface-water-fed streams. Additionally, we raised captive offspring from two such populations under standardised conditions to test whether potential phenotypic differentiation would be passed on to offspring. We found analogous differentiation by habitat in multiple wild populations. Some of these morphological differences were at least partially inherited by offspring. We suggest that this could have implications for both scientists and fisheries authorities studying or managing trout populations.     

An integrated method to create habitat suitability models for fragmented landscapes

Given the pervasive influence of human induced habitat fragmentation in ecological processes, landscape models are a welcome advance. The development of GIS software has allowed a greater use of these models and of analyses of the relationship between species and habitat variables. Habitat suitability models are thus theoretical concepts that can be used for planning in fragmented landscapes and habitat conservation. The most commonly used models are based on single species and on the assignment of suitability values for some environmental variables. Generally the cartographic basis for modeling suitability are thematic maps produced by a Boolean logic. In this paper we propose a model based on a set of focal species and on maps produced by a fuzzy classification method. Focal species, selected by an expert-based approach, provide a practical way of extending the scope of habitat suitability models to the conservation of biodiversity at landscape scale. The utilisation of a classification method that applies a continuity criterion may allow more consideration of the connectivity of an area because it allows a better detection of ecological gradients within a landscape. We applied this methodology to the Tuscany region focusing on terrestrial mammals. Performing a fuzzy classification we produced five land cover maps and through image processing operations we obtained a suitability model which applies a continuity criterion. The resulting suitability fuzzy model seems better for the study of connectivity and fragmentation, especially in areas with high spatial complexity.     

Evaporative water loss simulation improves models’ prediction of habitat suitability for a high-elevation forest skink

Accurate evaluation of habitat availability for wildlife is relevant for ecological applications. Researchers have frequently used models to simulate habitats thermally suitable for reptiles, but these results have limited application for species highly selective for habitat humidity. Here, we use the biophysical Niche Mapper™ model to investigate impacts of vegetation cover on the habitat quality of a high-elevation forest skink, Sphenomorphus taiwanensis, and to predict changes in habitat suitability in a future warmer climate (3 °C increase in air temperature). We assess habitat suitability with different densities of canopy cover in our study areas using two ecologically relevant estimates for lizards: maximum activity time and evaporative water loss (EWL) during the activity season. We measured preferred body temperature and EWL of this species for model parameterization, and behavioral response to EWL to supplement habitat quality assessment. The results indicated that this species is sensitive to EWL and reduces its activity when dehydrated. The model predicted that denser canopy levels increase microclimate cooling and humidity, and that most canopy levels are thermally suitable for this species, as the lizard can thermoregulate to manage adverse temperatures. Nevertheless, increasing canopy density could significantly decrease EWL during activity. In the warmer climate scenario, simulated maximum activity time and EWL changed little because of thermoregulation behavior. Our results suggest that habitat preference of this species is a consequence of water and energy requirements, and we note that combining EWL and maximum activity time data can enhance model accuracy of lizards’ habitat quality in a warmer climate.     

Static habitat partitioning and dynamic selection by sympatric young Atlantic salmon and brown trout in south-west England streams

Direct underwater observation of micro‐habitat use by 1838 young Atlantic salmon Salmo salar [mean L_T 7·9 ± 3.1(s.d.) cm, range 3·19] and 1227 brown trout Salmo trutta (L_T 10·9 ± 5·0 cm, range 3·56) showed both species were selective in habitat use, with differences between species and fish size. Atlantic salmon and brown trout selected relatively narrow ranges for the two micro‐habitat variables snout water velocity and height above bottom, but with differences between size‐classes. The smaller fishes <7 cm held positions in slower water closer to the bottom. On a larger scale, the Atlantic salmon more often used shallower stream areas, compared with brown trout. The larger parr preferred the deeper stream areas. Atlantic salmon used higher and slightly more variable mean water velocities than brown trout. Substrata used by the two species were similar. Finer substrata, although variable, were selected at the snout position, and differences were pronounced between size‐classes. On a meso‐habitat scale, brown trout were more frequently observed in slow pool‐glide habitats, while young Atlantic salmon favoured the faster high‐gradient meso‐habitats. Small juveniles <7 cm of both species were observed most frequently in riffle‐chute habitats. Atlantic salmon and brown trout segregated with respect to use of habitat, but considerable niche overlap between species indicated competitive interactions. In particular, for small fishes <7 cm of the two species, there was almost complete niche overlap for use of water depth, while they segregated with respect to water velocity. Habitat suitability indices developed for both species for mean water velocity and water depth, tended to have their optimum at lower values compared with previous studies in larger streams, with Atlantic salmon parr in the small streams occupying the same habitat as favoured by brown trout in larger streams. The data indicate both species may be flexible in their habitat selection depending on habitat availability. Species‐specific habitat overlap between streams may be complete. However, between‐species habitat partitioning remains similar.     

Data prevalence matters when assessing species' responses using data-driven species distribution models

The study of species' response is a key to understand the ecology of a species (e.g. critical habitat requirement and biological invasion processes) and design better conservation and management plans (e.g. problem identification, priority assessment and risk analysis). Predictive machine learning methods can be used as a tool for modeling species distributions as well as for describing important variables and specific habitat conditions required for a target species. This study aims (1) to demonstrate how habitat information such as species response curves can be retrieved from a species distribution model (SDM), (2) to assess the effects of data prevalence on model accuracy and habitat information retrieved from SDMs, and (3) to illustrate the differences between three data-driven methods, namely a fuzzy habitat suitability model (FHSM), random forests (RF) and support vector machines (SVMs). Nineteen sets of virtual species data with different data prevalences were generated using field-observed habitat conditions and hypothetical habitat suitability curves under four interaction scenarios governing the species–environment relationship for a virtual species. The effects of data prevalence on species distribution modeling were evaluated based on model accuracy and habitat information such as species response curves. Data prevalence affected both model accuracy and the assessment of species' response, with a stronger influence on the latter. The effects of data prevalence on model accuracy were less pronounced in the case of RF and SVMs which showed a higher performance. While the response curves were similar among the three models, data prevalence markedly affected the shapes of the response curves. Specifically, response curves obtained from a data set with higher prevalence showed higher tolerance to unsuitable habitat conditions, emphasizing the importance of accounting for data prevalence in the assessment of species–environment relationships. In a practical implementation of an SDM, data prevalence should be taken into account when interpreting the model results.     

Revisiting probabilistic neural networks: a comparative study with support vector machines and the microhabitat suitability for the Eastern Iberian chub (Squalius valentinus)

Probabilistic Neural Networks (PNNs) and Support Vector Machines (SVMs) are flexible classification techniques suited to render trustworthy species distribution and habitat suitability models. Although several alternatives to improve PNNs' reliability and performance and/or to reduce computational costs exist, PNNs are currently not well recognised as SVMs because the SVMs were compared with standard PNNs. To rule out this idea, the microhabitat suitability for the Eastern Iberian chub (Squalius valentinus Doadrio & Carmona, 2006) was modelled with SVMs and four types of PNNs (homoscedastic, heteroscedastic, cluster and enhanced PNNs); all of them optimised with Differential Evolution. The fitness function and several performance criteria (correctly classified instances, true skill statistic, specificity and sensitivity) and partial dependence plots were used to assess respectively the performance and reliability of each habitat suitability model. Heteroscedastic and enhanced PNNs achieved the highest performance in every index but specificity. However, these two PNNs rendered ecologically unreliable partial dependence plots. Conversely, homoscedastic and cluster PNNs rendered ecologically reliable partial dependence plots. Thus, Eastern Iberian chub proved to be a eurytopic species, presenting the highest suitability in microhabitats with cover present, low flow velocity (approx. 0.3 m/s), intermediate depth (approx. 0.6 m) and fine gravel (64–256 mm). PNNs outperformed SVMs; thus, based on the results of the cluster PNN, which also showed high values of the performance criteria, we would advocate a combination of approaches (e.g., cluster & heteroscedastic or cluster & enhanced PNNs) to balance the trade-off between accuracy and reliability of habitat suitability models.     

Predicting future invasion of an invasive alien tree in a Japanese oceanic island by process-based statistical models using recent distribution maps

Modelling and predicting the potential habitat and future range expansion of invasive species can help managers to mitigate the impact of such species. Because habitat suitability and the colonization process are key determinants of range expansion, inferences drawn from invasion patterns should be based on both attributes. To predict the potential habitat and expansion rate of the invasive tree Bischofia javanica on Hahajima Island, we used simultaneous models of habitat and dispersal to estimate the effect of environment and dispersal from the source population on the current distribution. We compared the fit and the estimated magnitudes of the environment and dispersal effects in the simultaneous models with those in habitat suitability and colonization kernel models. The values of Akaike’s information criterion for the simultaneous models were better than those of the habitat suitability and colonization kernel models, indicating that the current distribution of Bischofia was determined by both environment and dispersal. The simultaneous models predicted that the potential habitat of Bischofia would be larger than that predicted by the habitat suitability model. The potential habitat distribution and future invasion predicted by the simultaneous models will contribute to the development of specific landscape-scale management plans to control this invasive species.     

Probabilistic accounting of uncertainty in forecasts of species distributions under climate change

Forecasts of species distributions under future climates are inherently uncertain, but there have been few attempts to describe this uncertainty comprehensively in a probabilistic manner. We developed a Monte Carlo approach that accounts for uncertainty within generalized linear regression models (parameter uncertainty and residual error), uncertainty among competing models (model uncertainty), and uncertainty in future climate conditions (climate uncertainty) to produce site‐specific frequency distributions of occurrence probabilities across a species' range. We illustrated the method by forecasting suitable habitat for bull trout (Salvelinus confluentus) in the Interior Columbia River Basin, USA, under recent and projected 2040s and 2080s climate conditions. The 95% interval of total suitable habitat under recent conditions was estimated at 30.1–42.5 thousand km; this was predicted to decline to 0.5–7.9 thousand km by the 2080s. Projections for the 2080s showed that the great majority of stream segments would be unsuitable with high certainty, regardless of the climate data set or bull trout model employed. The largest contributor to uncertainty in total suitable habitat was climate uncertainty, followed by parameter uncertainty and model uncertainty. Our approach makes it possible to calculate a full distribution of possible outcomes for a species, and permits ready graphical display of uncertainty for individual locations and of total habitat.     

Comparing correlative and bioenergetics‐based habitat suitability models for drift‐feeding fishes

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Simple predictions of instream habitat model outputs for target fish populations

1. Bottom-up approaches based on individual behaviour can help to identify key variables influencing populations at larger scales. Instream habitat models have been developed to predict the consequences, for populations in stream reaches, of fish preferences for particular hydraulic conditions observed at the scale of individuals. Conventional instream habitat models (e.g. PHABSIM) predict habitat values for species or life stages in reaches, and their changes with discharge. Despite their worldwide use, they have been subject to continuing criticism and have been mainly limited to site-specific case studies.
2. We ran conventional instream habitat models in 58 French stream reaches dominated by brown trout. Using non-linear mixed effect models, we demonstrated that the outputs of instream habitat models (habitat values for three trout life stages and five other species) are predictable from average characteristics of reaches (discharge, depth, width and bed particle size).
3. Our models closely reflect variations in habitat values within-reaches (with discharge) and between-reaches. Within-reach changes are linked to the Reynolds number of reaches, while between-reach changes depend mainly on the Froude number at median daily discharge. These two dimensionless variables combine discharge, mean depth and mean width of reaches. Independent model validations showed robust model predictions that are consistent with studies of habitat values for brown trout made in larger streams from western North America.
4. Our results contribute to identifying the main hydraulic variables governing estimates of fish habitat values. They should facilitate habitat studies in multiple streams, at the basin or larger scales, while reducing their cost. They should enhance the biological validation of habitat model predictions, which remains critical.     

Evaluation of Habitat Suitability Models for Forest Passerines Using Demographic Data

ABSTRACT Habitat suitability is often used as a surrogate for demographic responses (i.e., abundance, survival, fecundity, or population viability) in the application of habitat suitability index (HSI) models. Whether habitat suitability actually relates to demographics, however, has rarely been evaluated. We validated HSI models of breeding habitat suitability for wood thrush (Hylocichla mustelina) and yellow-breasted chat (Icteria virens) in Missouri, USA. First, we evaluated HSI models as a predictor of 3 demographic responses: within-site territory density, site-level territory density, and nest success. We demonstrated a link between HSI values and all 3 types of demographic responses for the yellow-breasted chat and site-level territory density for the wood thrush. Second, we evaluated support for models containing HSI values, models containing measured habitat features (e.g., tree age, tree species, ecological land type), and models containing management treatments (e.g., even-aged and uneven-aged forest regeneration treatments) for each demographic response using model selection. Models containing HSI values received more support, in general, than models containing only habitat features or management treatments for all 3 types of wildlife response. The assumption that changes in habitat suitability represent wildlife demographic response to vegetation change is supported by our models. However, differences in species ecology may contribute to the degree to which HSI values are related to specific demographic responses. We recommend validation of HSI models with the particular demographic data of interest (i.e., density, productivity) to increase confidence in the model used for conservation planning.     

Genetic diversity is related to climatic variation and vulnerability in threatened bull trout

Understanding how climatic variation influences ecological and evolutionary processes is crucial for informed conservation decision‐making. Nevertheless, few studies have measured how climatic variation influences genetic diversity within populations or how genetic diversity is distributed across space relative to future climatic stress. Here, we tested whether patterns of genetic diversity (allelic richness) were related to climatic variation and habitat features in 130 bull trout (Salvelinus confluentus) populations from 24 watersheds (i.e., ~4–7th order river subbasins) across the Columbia River Basin, USA. We then determined whether bull trout genetic diversity was related to climate vulnerability at the watershed scale, which we quantified on the basis of exposure to future climatic conditions (projected scenarios for the 2040s) and existing habitat complexity. We found a strong gradient in genetic diversity in bull trout populations across the Columbia River Basin, where populations located in the most upstream headwater areas had the greatest genetic diversity. After accounting for spatial patterns with linear mixed models, allelic richness in bull trout populations was positively related to habitat patch size and complexity, and negatively related to maximum summer temperature and the frequency of winter flooding. These relationships strongly suggest that climatic variation influences evolutionary processes in this threatened species and that genetic diversity will likely decrease due to future climate change. Vulnerability at a watershed scale was negatively correlated with average genetic diversity (r = ?0.77; P < 0.001); watersheds containing populations with lower average genetic diversity generally had the lowest habitat complexity, warmest stream temperatures, and greatest frequency of winter flooding. Together, these findings have important conservation implications for bull trout and other imperiled species. Genetic diversity is already depressed where climatic vulnerability is highest; it will likely erode further in the very places where diversity may be most needed for future persistence.     

Effects of species invasion on population dynamics,vital rates and life histories of the native species

Invasions occurring in natural environments provide the opportunity to study how vital rates change and life histories evolve in the presence of a competing species. In this work, we estimate differences in reproductive traits, individual growth trajectories, survival, life histories and population dynamics between a native species living in allopatry and in sympatry with an invasive species of the same taxonomic Family. We used as a model system marble trout Salmo marmoratus (native species) and rainbow trout Oncorhynchus mykiss (non-native) living in the Idrijca River (Slovenia). An impassable waterfall separates the stream into two sectors only a few 100 meters apart: a downstream sector in which marble trout live in sympatry with rainbow trout and an upstream sector in which marble trout live in allopatry. We used an overarching modelling approach that uses tag-recapture and genetic data (>2,500 unique marble and rainbow trout were sampled and genotyped) to reconstruct pedigrees, test for synchrony of population dynamics and model survival and growth, while accounting for individual heterogeneity. The population dynamics of the two marble trout populations and of rainbow trout were synchronous. We found higher prevalence of younger parents, higher mortality and lower population density in marble trout living in sympatry with rainbow trout than in marble trout living in allopatry. There were no differences in the average individual growth trajectories between the two marble trout populations. Faster life histories of marble trout living in sympatry with rainbow trout are consistent with predictions of life history theory.     

Modelling habitat preference,abundance and species richness of alien macrocrustaceans in surface waters in Flanders (Belgium) using decision trees

The introduction and the spread of alien invasive species are a worldwide phenomenon causing global ecological and economic damages. Among the invaders, alien macrocrustaceans are known to be very successful invertebrates that colonise new habitats rapidly. Data from different fresh and brackish waters gathered by the Flemish Environment Agency (VMM) were used to build data-driven models predicting habitat preference, abundance and species richness of alien macro-Crustacea present in surface waters in Flanders. Different techniques such as regression and classification trees in combination with several optimisation methods (e.g. pruning) were used to construct the models. The performance of the models was moderate, because a balance between performance, ecological relevance and complexity was strived for. When using a three-fold cross validation it was found that the variation between the folds was limited, which is an indication of the robustness and the good reliability of the constructed models. Based on a sensitivity analysis the importance of conductivity, Kjeldahl nitrogen and shipping were stressed as well as graphically illustrated. Alien macrocrustaceans were predicted as present under brackish water conditions as well as in fresh waters with intensive ship traffic and low levels of organic pollution. The alien species richness was higher in rivers with intensive ship traffic and increased with increasing conductivity. Especially in brackish waters, alien macrocrustaceans reached high abundances. In fresh water, the abundance of alien species was generally lower. An integrated model that combined our habitat suitability model with a water quality model was used to predict the future distribution of alien macrocrustaceans. The predictions indicated that the prevalence and the species richness of alien macrocrustaceans are likely to increase with improving chemical water quality, whereas their abundance will probably decrease slightly. From our analysis, it is clear that models are a useful tool and that decision makers should focus on vulnerable areas such as brackish water areas and areas with intensive ship traffic in order to prevent the further introduction and spread of alien species.     

Population status and ecology of the Salmo trutta complex in an Italian river basin under multiple anthropogenic pressures

Salmonids inhabiting Mediterranean rivers are of particular concern for biodiversity conservation, as they are threatened by various stressors, including habitat alterations, overfishing, climate change, and introgressive hybridization with alien species. In the Tiber River basin (Central Italy), genetic introgression phenomena of the native Salmo cettii with the non‐native Salmo trutta hinder the separate analysis of the two species, which are both included in the S. trutta complex. Little is known about the factors currently limiting the trout populations in this area, particularly with respect to climate change. With the intention of filling this gap, the aims of the current study were to (a) quantify changes in the climate and (b) analyze the distribution, status, and ecology of trout populations, in the context of changing abiotic conditions over the last decades. Fish stock assessments were carried out by electrofishing during three census periods (1998–2004, 2005–2011, and 2012–2018) at 129 sites. The trend over time of meteorological parameters provided evidence for increased air temperature and decreased rainfall. Multivariate analysis of trout densities and environmental data highlighted the close direct correlation of trout abundance with water quality, altitude, and current speed. Climate‐induced effects observed over time in the sites where trout were sampled have not yet led to local extinctions or distribution shifts, indicating a marked resilience of trout, probably due to the buffering effect of intrinsic population dynamics. Decreasing body conditions over time and unbalanced age structures support the hypothesis that variations in hydraulic regime and water temperature could overcome these compensatory effects, which may lead to a severe decline in trout populations in the near future. In a climate change context, habitat availability plays a key role in the distribution of cold‐water species, which often do not have the possibility to move upstream to reach their thermal optimum because of water scarcity in the upper river stretches.     

Pumpkin seed cake as a fishmeal substitute in fish nutrition: effects on growth performance,morphological traits and fillet colour of two freshwater salmonids and two catfish species

The objectives of this study were to investigate the digestibility of pumpkin seed cake (PSC) for the rainbow trout, Oncorhynchus mykiss (Walbaum, 1792), and effects on performance and product quality traits of four different fish species when PSC partially replaced fishmeal in extruded diets. A digestibility trial was carried out to determine apparent digestibility coefficients (ADC) for crude protein (CP), ether extract (EE) and gross energy (GE) of PSC fed to rainbow trout. In subsequent growth trials, effects on performance and morphological traits and fillet colour values of four different fish species [rainbow trout; brook trout, Salvelinus fontinalis (Mitchill, 1814); African sharptooth catfish, Clarias gariepinus (Burchell, 1822); and wels catfish, Silurus glanis (Linnaeus, 1758)] were evaluated when 60% of fishmeal protein of a reference diet was replaced by PSC protein (based on digestible CP). Nutrient ADC of PSC were high (CP: 89%, EE: 88% and GE: 84%). No significant effects on growth and only minor effects on fillet colour were detected in the trials. However, replacing fishmeal with PSC at the chosen level affected morphological traits and feed conversion in all four species to different extents. Replacement effects of PSC should be tested at lower levels of inclusion before conclusions are drawn on its suitability in fish diets.     

Monitoring ecological status of wetlands using linked fuzzy inference system- remote sensing analysis

The present study develops an applicable model to simulate the ecological status of saltwater lakes in which depth and total dissolved solids are selected as the effective factors on aquatic habitats. First, spectral images of the operational land imager of Landsat 8 were used to simulate distribution of depth and total dissolved solids by applying two feed forward neural networks. Next, a Mamdani fuzzy inference system was used to develop habitat suitability rules of Artemia and Flamingo as the selected target species in which expert opinions were considered. Finally, habitat suitability maps of target species were generated by linking distribution maps of selected effective parameters and fuzzy inference system. Based on the results in the Urmia lake as a case study, the Nash–Sutcliffe efficiency coefficients of depth and total dissolved solids are 0.88 and 0.5 which indicates the proposed method for simulating distribution of these parameters is reliable. Average depth in the simulated date is 227 cm, while average simulated total dissolved solids is 264 g per litre. Simulation of habitat suitability maps demonstrated that average habitat suitability of Artemia is less than 30% in the most areas of the lake. Moreover, average habitat suitability of the Flamingo is less than 10% which implies the ecological status of the lake is critical and ecological restoration is necessary. The main advantage of the proposed method is to develop a framework for combining the expert opinions with remote sensing data processing to generate habitat suitability maps in lakes.     

Cost of predation avoidance in young-of-year lake trout (Salvelinus namaycush): growth differential in sub-optimal habitats

Selection of habitat to avoid predation may affect the diet of young-of-year (YOY) lake trout (Salvelinus namaycush). YOY lake trout may use inshore habitat to avoid predation; this habitat may be sub-optimal for growth. To test this, YOY lake trout were penned in nearshore and offshore pelagic areas of two arctic lakes. Toolik Lake had a lake trout population, the other lake, S6, did not. YOY lake trout in Toolik Lake lost weight, but those offshore lost less weight. The YOY lake trout in Lake S6 gained weight and those offshore gained more weight. The primary diet item of the YOY lake trout in both lakes during this experiment was the zooplankter Diaptomis probilofensis; it was also one of the most abundant species. However, its density inshore in Lake S6 was similar to inshore and offshore densities in Toolik Lake. The increased availability of alternative zooplankton prey in Lake S6 may account for the growth differential of YOY lake trout in Lake S6 relative to Toolik Lake. Bioenergetic modeling of YOY lake trout suggests that growth similar to that in the offshore of Lake S6 would be necessary for successful recruitment. If the reduced zooplankton availability in Toolik Lake leads to the reduced growth of YOY in the inshore and offshore pelagic areas, then these fish will be more susceptable to winter predation/starvation. For YOY lake trout to survive in Toolik Lake they most likely shift to feeding on benthic prey before the end of their first summer. Dept. of Chemical Engineering     

Modeling bird species distribution change in fire prone Mediterranean landscapes: incorporating species dispersal and landscape dynamics

Species distribution models (SDMs) have traditionally been founded on the assumption that species distributions are in equilibrium with environmental conditions and that these species–environment relationships can be used to estimate species responses to environmental changes. Insight into the validity of this assumption can be obtained from comparing the performance of correlative species distribution models with more complex hybrid approaches, i.e. correlative and process‐based models that explicitly include ecological processes, thereby accounting for mismatches between habitat suitability and species occupancy patterns. Here we compared the ability of correlative SDMs and hybrid models, which can accommodate non‐equilibrium situations arising from dispersal constraints, to reproduce the distribution dynamics of the ortolan bunting Emberiza hortulana in highly dynamic, early successional, fire driven Mediterranean landscapes. Whereas, habitat availability was derived from a correlative statistical SDM, occupancy was modeled using a hybrid approach combining a grid‐based, spatially‐explicit population model that explicitly included bird dispersal with the correlative model. We compared species occupancy patterns under the equilibrium assumption and different scenarios of species dispersal capabilities. To evaluate the predictive capability of the different models, we used independent species data collected in areas affected to different degree by fires. In accordance with the view that disturbance leads to a disparity between the suitable habitat and the occupancy patterns of the ortolan bunting, our results indicated that hybrid modeling approaches were superior to correlative models in predicting species spatial dynamics. Furthermore, hybrid models that incorporated short dispersal distances were more likely to reproduce the observed changes in ortolan bunting distribution patterns, suggesting that dispersal plays a key role in limiting the colonization of recently burnt areas. We conclude that SDMs used in a dynamic context can be significantly improved by using combined hybrid modeling approaches that explicitly account for interactions between key ecological constraints such as dispersal and habitat suitability that drive species response to environmental changes.