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How the complexity of food webs depends on environmental variables is a long‐standing ecological question. It is unclear though how food‐chain length should vary with adaptive evolution of the constitutive species. Here we model the evolution of species colonisation rates and its consequences on occupancies and food‐chain length in metacommunities. When colonisation rates can evolve, longer food‐chains can persist. Extinction, perturbation and habitat loss all affect evolutionarily stable colonisation rates, but the strength of the competition‐colonisation trade‐off has a major role: weaker trade‐offs yield longer chains. Although such eco‐evo dynamics partly alleviates the spatial constraint on food‐chain length, it is no magic bullet: the highest, most vulnerable, trophic levels are also those that least benefit from evolution. We provide qualitative predictions regarding how trait evolution affects the response of communities to disturbance and habitat loss. This highlights the importance of eco‐evolutionary dynamics at metacommunity level in determining food‐chain length. [ABSTRACT FROM AUTHOR]

Mountain headwater streams have emerged as important climate refuges for native cold‐water species due to their slow climate velocities and extreme physical conditions that inhibit non‐native invasions. Species persisting in refuges often do so as fragmented, relict populations from broader historical distributions that are subject to ongoing habitat reductions and increasing isolation as climate change progresses. Key for conservation planning is determining where remaining populations will persist and how habitat restoration strategies can improve biological resilience to enhance the long‐term prospects for species of concern. Studying bull trout, a headwater species in the northwestern USA, we developed habitat occupancy models using a data set of population occurrence in 991 natal habitat patches with a suite of novel geospatial covariates derived from high‐resolution hydroclimatic scenarios and other sources representing watershed and instream habitat conditions, patch geometry, disturbance, and biological interactions. The best model correctly predicted bull trout occupancy status in 82.6% of the patches and included effects for: patch size estimated as habitat volume, extent of within‐patch reaches <9°C mean August temperature, distance to nearest occupied patch, road density, invasive brook trout prevalence, patch slope, and frequency of high winter flows. The model was used to assess 16 scenarios of bull trout occurrence within the study streams that represented a range of restoration strategies under three climatic conditions (baseline, moderate change, and extreme change). Results suggested that regional improvements in bull trout status were difficult to achieve in realistic restoration strategies due to the pervasive nature of climate change and the limited extent of restoration actions given their high costs. However, occurrence probabilities in a subset of patches were highly responsive to restoration actions, suggesting that targeted investments to improve the resilience of some populations may be contextually beneficial. A possible strategy, therefore, is focusing effort on responsive populations near more robust population strongholds, thereby contributing to local enclaves where dispersal among populations further enhances resilience. Equally important, strongholds constituted a small numerical percentage of patches (5%–21%), yet encompassed the large majority of occupied habitat by volume (72%–89%) and their protection could have significant conservation benefits for bull trout. [ABSTRACT FROM AUTHOR]

Aim: The population processes that drive tree species distribution are still widely debated. We test the hypotheses that metapopulation processes of colonization and extinction are linked to predictions of species distribution models. Location: Europe: Spain, France, Germany, Finland and Sweden. Taxon: Angiosperms and Gymnosperms. Methods: For 17 tree species analysed, we fitted species distribution models (SDM) relating environmental variables to presence–absence data across Europe. Then, using independent data from national forest inventories across Europe, we tested whether colonization and extinction probabilities are related to SDM occurrence probabilities. Finally, we assessed the probability of presence at metapopulation equilibrium depending on colonization and extinction probabilities. Results: We found that for most species at least one process (colonization/extinction) is related to SDM occurrence probability, but rarely both (only two species). Depending on the species, the link was either for colonization or for extinction, but relationships were generally weak. In addition, the metapopulation models tended to overestimate the occurrence probability at equilibrium. Main conclusions: Our study shows that metapopulation processes are only weakly related to SDM occurrence probability and call for caution in extrapolating SDM models to metapopulation dynamics. [ABSTRACT FROM AUTHOR]

Intra-specific variability often produces an overlap between species distributions of individual performances which can influence competition relations and community dynamics. We analysed a two-species competition-colonisation model of vegetation with intra-specific variability in juvenile growth. On each patch colonised by both species, the winner was the juvenile with higher individual growth. Intra-specific variability disproportionately favoured the more fecund species because the tail of its distribution represented more individuals. In some cases, this process could even lead to a reversal of competition hierarchy and exclusion of the species with higher mean juvenile performance. In the space of species 2 mean growth and fecundity traits, the combinations of traits allowing coexistence with species 1 appeared close to an ideal trade-off curve. Along this curve, species 2 and species 1 coexisted at similar abundance. The balance of relative abundances diminished with the distance of species 2 from this curve. For a given level of relative species performances, coexistence stability increased continuously as species differentiation increased. In contrast to classical models that exhibit abrupt changes of equilibrium community properties when species traits vary, our model displayed continuous changes of these properties in relation to the balance of life traits within and among species. Intra-specific variability allows flexible patterns of community dynamics and could explain discrepancies between observations and classical theories. [ABSTRACT FROM AUTHOR]

If the deterministic threats of fragmentation can be stopped or reversed, species may find opportunities to disperse between patches and reduce the risk of extinction. In order to realise these opportunities and apply them to conservation programmes, it is necessary to understand the dynamics involved and to estimate which capacity is high enough to sustain a population at the landscape level. In a regional population consisting of several subpopulations, the incidence function model (IFM) is a stochastic, spatially-realistic patch occupancy model which can be applied using few parameters. With this model one can simulate and manipulate a patch network for a species. In IFM, the extinction probability is assumed to be proportional to local population size which in turn is assumed to be proportional to the local patch area. Although, the basic area of patches is of importance, influence from the geometric shape of patches may be equally or more important to determine potential incidence of a species in a particular patch. Basic area measurements might overestimate the probability of occupancy and/or capacity of a certain patch network to sustain a metapopulation. One applicable method to use in dealing with regional dynamics in fragmented landscapes is metapopulation capacity; derived from metapopulation theory, this method can be used to rank different patch networks. In our study, we examine if there is any difference in occupancy level and capacity between four different area scenarios. This allows us to determine if the basic area measurement of patches can result in a biased estimation of population viability in a specific landscape. It is concluded that perimeter-area related measures of patch size combined with capacity could be a more important measure for estimation of population dynamics and impact of landscape changes compared to basic area measurement and occupancy levels. [ABSTRACT FROM AUTHOR]

1. A recent and controversial topic in landscape ecology is whether populations of species respond to habitat fragmentation in a general fashion. Empirical research has provided mixed support, resulting in controversy about the use of general rules in landscape management. Rather than simply assessing post hoc whether individual species follow such rules, a priori testing could shed light on their accuracy and utility for predicting species response to landscape change. 2. We aim to create an a priori model that predicts the presence or absence of multiple species in habitat patches. Our goal is to balance general theory with relevant species life-history traits to obtain high prediction accuracy. To increase the utility of this work, we aim to use accessible methods that can be applied using readily available inexpensive resources. 3. The classification tree patch-occupancy model we create for birds is based on habitat suitability, minimum area requirements, dispersal potential of each species and overall landscape connectivity. 4. To test our model we apply it to the South East Queensland region, Australia, for 17 bird species with varying dispersal potential and habitat specialization. We test the accuracy of our predictions using presence–absence information for 55 vegetation patches. 5. Overall we achieve Cohen’s kappa of 0·33, or ‘fair’ agreement between the model predictions and test data sets, and generally a very high level of absence prediction accuracy. Habitat specialization appeared to influence the accuracy of the model for different species. 6. We also compare the a priori model to the statistically derived model for each species. Although this ‘optimal model’ generally differed from our original predictive model, the process revealed ways in which it could be improved for future attempts. 7. Synthesis and applications. Our study demonstrates that ecological generalizations alongside basic resources (a vegetation map and some species-specific information) can provide conservative accuracy for predicting species occupancy in remnant vegetation patches. We show that the process of testing and developing models based on general rules could provide basic tools for conservation managers to understand the impact of current or planned landscape change on wildlife populations. [ABSTRACT FROM AUTHOR]

In this paper, we investigate a spatially explicit metapopulation model with Allee effects. We refer to the patch occupancy model introduced by Levins (Bull Entomol Soc Am 15:237–240, ) as a spatially implicit metapopulation model, i.e., each local patch is either occupied or vacant and a vacant patch can be recolonized by a randomly chosen occupied patch from anywhere in the metapopulation. When we transform the model into a spatially explicit one by using a lattice model, the obtained model becomes theoretically equivalent to a “lattice logistic model” or a “basic contact process”. One of the most popular or standard metapopulation models with Allee effects, developed by Amarasekare (Am Nat 152:298–302, ), supposes that those effects are introduced formally by means of a logistic equation. However, it is easier to understand the ecological meaning of associating Allee effects with this model if we suppose that only the logistic colonization term directly suffers from Allee effects. The resulting model is also well defined, and therefore we can naturally examine it by Monte Carlo simulation and by doublet and triplet decoupling approximation. We then obtain the following specific features of one-dimensional lattice space: (1) the metapopulation as a whole does not have an Allee threshold for initial population size even when each local population follows the Allee effects; and (2) a metapopulation goes extinct when the extinction rate of a local population is lower than that in the spatially implicit model. The real ecological metapopulation lies between two extremes: completely mixing interactions between patches on the one hand and, on the other, nearest neighboring interactions with only two nearest neighbors. Thus, it is important to identify the metapopulation structure when we consider the problems of invasion species such as establishment or the speed of expansion. [ABSTRACT FROM AUTHOR]

An herbivorous cichlid fish Cichlasoma ( Theraps) nicaraguense has been reported to perform brood care for the fry of a piscivorous cichlid Cichlasoma ( Nandopsis) dovii in a Nicaraguan lake. It was suggested that interspecific brood care (IBC) evolved to propagate C. dovii as a predator of another herbivorous fish Neetroplus nematopus, which is superior to C. nicaraguense in competition for breeding territory. However, it is still unclear how IBC is maintained in the face of cheaters that do not provide IBC. In this study, to elucidate the conditions for maintenance of IBC, we developed a spatially structured model, assuming a trade-off between reproduction and IBC (i.e., intra- and interspecific competition) and behavioral plasticity in IBC. The model predicted the following maintenance conditions: the probability of expressing (or suppressing) IBC in response to competitor invasion (or exclusion) is low, or, if the probability is high, then IBC is less effective for exclusion of competitors. Furthermore, we also predicted that IBC can be maintained without spatial structure if it is plastic behavior. Our model contributes to understanding of maintenance of IBC by providing empirically testable predictions. We discuss how this model is applicable to more general relationships, such as those in competitive or mutualistic systems. [ABSTRACT FROM AUTHOR]

Estimates of abundance of threatened and endangered species are crucial for monitoring population status and recovery progress. For most wildlife species, multiple abundance estimation methods are available and the choice of method should depend on cost and efficacy. We field-tested the cost and efficacy of line transect, total count, sample count, and double observer methods for estimating abundance of gopher tortoise (Gopherus polyphemus) burrows in two habitats that differed in vegetation density (sparse and dense) at the Ordway-Swisher Biological Station in north-central Florida. In the dense vegetation stratum, density of burrows estimated using the line transect method (8.58 ± 0.94 burrows ha-1) was lower than that obtained from the total count method (11.33 burrows ha-1). In the sparse vegetation stratum, estimated burrow density using the line transect method (11.32 ± 1.19 burrows ha-1) was closer to the burrow density obtained from the total count method (13.00 burrows ha-1). Density of burrows estimated using the double observer method was identical to that obtained from the total count method in dense vegetation stratum, but slightly greater than that obtained from the total count method in sparse vegetation stratum. Density of burrows estimated using the sample count method varied widely depending on the proportion of plots sampled. The cost of sampling as well as estimates of burrow density varied with habitat type. The line transect method was the least costly of the methods, and we were able to sample a larger effective area with the same effort. Using burrow cameras and patch occupancy modeling approach, we also estimated the probability of burrow occupancy by gopher tortoises (active: 0.50 ± 0.09; inactive: 0.04 ± 0.04), and used these values to estimate abundance of gopher tortoises. Using estimates of burrow abundance based on the line transect method, density of gopher tortoises was 2.75 ± 0.74 ha-1 in the sparse vegetation stratum. We recommend that gopher tortoise monitoring programs use rigorous methods for estimating burrow abundance (e.g., line transect methods) and the probability of burrow occupancy by gopher tortoises (e.g., patch occupancy modeling approach). [ABSTRACT FROM AUTHOR]

Patch occupancy models provide a simple phenomenological approach to evaluating ecological questions on a metapopulation scale. In this study, I use and modify a patch occupancy model to evaluate the effects of synchronous extinctions correlated with flooding and patch-size-dependent migration on the regional dynamics of a neotropical beetle, Cephaloleia fenestrata. Various methods have been used to evaluate patch occupancy models. Previous authors most commonly have evaluated patch occupancy models by logistic regression of incidence functions. Likelihoods produced from regression methods, however, neglect autocorrelation in spatial occupancy patterns even though spatial auto-correlation is common in ecological data. In this study, I used a Monte Carlo method of model evaluation, which accounts for spatial autocorrelation. Results suggest that patches undergo synchronous extinctions correlated with flooding and this affects regional dynamics of C. fenestrata. Immigration probability positively correlated with patch size, and emigration probability negatively correlated with patch size, also affecting C. fenestrata regional dynamics. The patch occupancy pattern was positively spatially autocorrelated at only two of the sites, but was nearly significant at another. The logistic regression method was a reasonable alternative to the Monte Carlo method for model evaluation. Other model evaluation methods (fits to model development data, proportion of occupied patches, and turnover rates) were inconsistent (at best) quantitative measures of a model's fit to independent data. When used to select among competing models, however, the fits to model development data were reasonably good indicators of fits to independent data. Given the increased complexity involved in using the Monte Carlo method, the simpler logistic regression method may be a preferable alternative, especially when spatial autocorrelation is minimal. [ABSTRACT FROM AUTHOR]

Presence–absence data are used widely in analysis of wildlife–habitat relationships. Failure to detect a species’ presence in an occupied habitat patch is a common sampling problem when the population size is small, individuals are difficult to sample, or sampling effort is limited. In this paper, the influence of non-detection of occurrence on parameter estimates of logistic regression models of wildlife–habitat relationships was assessed using analytical analysis and simulations. Two patterns of non-detection were investigated: (1) a random distribution of non-detection among occupied patches; and (2) a non-random distribution of non-detection in which the probability of detecting a species in an occupied patch covaried with measurable habitat variables. Our results showed that logistic regression models of wildlife–habitat relationships were sensitive to even low levels of non-detection in occupancy data. Both analytic and simulation studies show that non-detection yields bias in parameter estimation of logistic regression models. More importantly, the direction of bias was affected by the underlying pattern of non-detection and whether the habitat variable was positively or negatively related to occupancy. For a positive habitat coefficient, a random distribution of non-detection yielded negative bias in estimation, whereas linkage of the probability of non-detection to habitat covariates produced positive bias. For a negative habitat coefficient, the pattern was reversed, with a random distribution of non-detection leading to positive bias in estimation. A release–recapture livetrapping study of small mammals in central Indiana, USA, was used to illustrate the magnitude of non-detection in a typical field sampling protocol with varying levels of sampling intensity. Estimates of non-detection error ranged from 0 to 23% for seven species after 5 days of sampling. We suggest that for many sampling situations, relationships between probability of detection and habitat covariates need to be established to correctly interpret results of wildlife–habitat models. [Copyright &y& Elsevier]