Simple individual-based models effectively represent Afrotropical forest bird movement in complex landscapes

Reliable estimates of dispersal rates between habitat patches (i.e. functional connectivity) are critical for predicting long-term effects of habitat fragmentation on population persistence. Connectivity measures are frequently derived from least cost path or graph-based approaches, despite the fact that these methods make biologically unrealistic assumptions. Individual-based models (IBMs) have been proposed as an alternative as they allow modelling movement behaviour in response to landscape resistance. However, IBMs typically require excessive data to be useful for management. Here, we test the extent to which an IBM requiring only an uncomplicated set of movement rules [the 'stochastic movement simulator' (SMS)] can predict animal movement behaviour in real-world landscapes. Movement behaviour of two forest birds, the Cabanis's greenbul Phyllastrephus cabanisi (a forest specialist) and the white-starred robin Pogonocichla stellata (a habitat generalist), across an Afrotropical matrix was simulated using SMS. Predictions from SMS were evaluated against a set of detailed movement paths collected by radiotracking homing individuals. SMS was capable of generating credible predictions of bird movement, although simulations were sensitive to the cost values and the movement rules specified. Model performance was generally highest when movement was simulated across low-contrasting cost surfaces and when virtual individuals were assigned low directional persistence and limited perceptual range. SMS better predicted movements of the habitat specialist than the habitat generalist, which highlights its potential to model functional connectivity when species movements are affected by the matrix. Synthesis and applications. Modelling the dispersal process with greater biological realism is likely to be critical for improving our predictive capability regarding functional connectivity and population persistence. For more realistic models to be widely applied, it is vital that their application is not overly complicated or data demanding. Here, we show that given relatively basic understanding of a species' dispersal ecology, the stochastic movement simulator represents a promising tool for estimating connectivity, which can help improve the design of functional ecological networks aimed at successful species conservation

Heritability and Artificial Selection on Ambulatory Dispersal Distance in Tetranychus urticae: Effects of Density and Maternal Effects

Dispersal distance is understudied although the evolution of dispersal distance affects the distribution of genetic diversity through space. Using the two-spotted spider mite, Tetranychus urticae, we tested the conditions under which dispersal distance could evolve. To this aim, we performed artificial selection based on dispersal distance by choosing 40 individuals (out of 150) that settled furthest from the home patch (high dispersal, HDIS) and 40 individuals that remained close to the home patch (low dispersal, LDIS) with three replicates per treatment. We did not observe a response to selection nor a difference between treatments in life-history traits (fecundity, survival, longevity, and sex-ratio) after ten generations of selection. However, we show that heritability for dispersal distance depends on density. Heritability for dispersal distance was low and non-significant when using the same density as the artificial selection experiments while heritability becomes significant at a lower density. Furthermore, we show that maternal effects may have influenced the dispersal behaviour of the mites. Our results suggest primarily that selection did not work because high density and maternal effects induced phenotypic plasticity for dispersal distance. Density and maternal effects may affect the evolution of dispersal distance and should be incorporated into future theoretical and empirical studies

Modelling establishment probabilities of an exotic plant, Rhododendron ponticum, invading a heterogeneous, woodland landscape using logistic regression with spatial autocorrelation

Rhododendron ponticum has become a well-established invasive species throughout the British Isles and is now considered a problematic invasive weed species. The habitat requirements for establishment, however, have only previously been described qualitatively. The aim of this study was to quantify the influence of topographical and environmental characteristics on the probability of establishment of this invasive shrub in a woodland environment. A binomial generalized linear model (GLM), incorporating spatial autocorrelation, was used to model the presence/absence of R. ponticum seedlings (<7-year-old plants)given substrate type and depth, canopy type and percent cover, altitude, slope, aspect and the distance to the nearest seed source as covariates. Depth and type of substrate along with distance from the closest seed source were found to be the most important predictors of seedling establishment. Specifically, fallen logs or tree stumps, newly colonised by moss, were identified as the most favourable habitat type for R. ponticum invasion. We show that the inclusion of spatial autocorrelation can affect model conclusions and, as a consequence, may influence management recommendations. Knowing how to reduce establishment can assist in managing invasive populations. Similarly, understanding how establishment probabilities vary according to habitat may aid the conservation of threatened populations

Improving prediction and management of range expansions by combining analytical and individual-based modelling approaches

Summary 1. Improving understanding and the prediction and management of range expansions is a key challenge for ecology. Over recent years there has been a rapid increase in modelling effort focussed on range expansions and a shift from predominantly theoretical developments towards application especially in the field of invasion biology, but also in relation to reintroductions and species’ responses to climate change. 2. While earlier models were exclusively analytical, individual-based models (IBMs) are now increasingly widely used. We argue that, instead of being viewed as competing methodologies, analytical and simulation methods can valuably be used in conjunction.3. In order to demonstrate the utility of employing both modelling approaches, we first use a mechanistic wind dispersal model to generate age-specific dispersal kernels for the invasive shrub, Rhododendron ponticum. This information along with demographic parameters is incorporated both within an IBM and an analytical, integrodifference model. 4. Estimates of equilibrium wavespeeds are similar for the two models, although slower rates of spread are consistently projected by the IBM. Comparing results provides an important cross-validation. Importantly our results demonstrate the equilibrium wavespeed to be sensitive to the characterisation of age structure in the model; when few age classes are used much higher rates of spread are projected. 5. The analytical model is extremely efficient at providing elasticity analysis of the equilibrium wavespeed and this information can help inform management. We gain qualitatively similar results using the IBM but obtaining the results is time consuming and, because the model is stochastic, they are noisy and harder to interpret. We argue that such elasticity analyses are needed for the many cases where success of control is measured on a relatively short time horizon. 6. We run the IBM on a real landscape (represented using GIS) comprising different habitat types, and compare two different control scenarios. This highlights the flexibility of the IBM approach and clearly demonstrates the utility of this approach for more tactical applications.7. We emphasise that analytical and individual-based approaches offer different, but complementary, advantages and suggest how their joint use can facilitate the improvement of biodiversity management at a range of spatial scales. <br/

Integrating demographic data and a mechanistic dispersal model to predict invasion spread of Rhododendron ponticum in different habitats

The factors underlying the invasiveness of non-native plants species and the invasibility of habitats in non-native ranges have been investigated in a number of studies. However, there are few examples where invasion potential across a range of key, vulnerable habitats within the non-native range has been compared for a single problematic species. Understanding the invasion potential of a species in different habitat types is crucial in prioritising management and control efforts, and in the protection of vulnerable habitats through monitoring. Here, using the invasive shrub Rhododendron ponticum as a case study, we integrate information on both the demographics and spatial dynamics within an individual-based, spatially-explicit model to investigate invasion potential in different habitats. Firstly, empirical demographic data were used to establish relationships between demographic traits, such as height and fecundity, and habitat variables. The outputs from models fitted using a Generalised Linear Model approach were then incorporated into an individual-based simulation model of plant spread to investigate the invasion potential in different habitats using a factorial design of treatments. Plant height, and thus seed release height, was found to be the main driver of invasion speed through an increase in dispersal potential, which resulted in the highest invasion speeds predicted for evergreen woodlands, and relatively low speeds for open habitats. Conversely, invasion density was driven by plant fecundity and seedling survival and not dispersal potential, which resulted in the highest invasion densities predicted for open habitats, and relatively low densities for evergreen habitats. Deciduous woodland had features that resulted in intermediate invasion potential, both in terms of speed and density and may, therefore be the habitat that is most vulnerable to rapid and dense invasion

Capacity for recovery in Bornean orangutan populations when limiting offtake and retaining forest

Aim: We assess the potential long-term viability of orangutan populations across Borneo, considering the effects of habitat loss, and various forms of population reduction, including hunting, retaliatory killings, and capture and translocation. Location: The study focused on the island of Borneo, a region that has experienced substantial deforestation over the past four decades, resulting in the degradation and fragmentation of its lowland forests, thereby threatening the island's unique biodiversity, including orangutan populations. Methods: To evaluate the long-term viability of orangutan populations, we employed a spatially-explicit individual-based model. This model allowed us to simulate various scenarios, including the impact of removing habitat fragments or individuals from the population. Results: Our findings revealed that small forest fragments facilitate orangutan movement, thereby increasing the number of individuals settling in non-natal patches. Crucially, orangutan populations proved highly vulnerable to even small levels of offtake. Annual removal rates exceeding 2% diminished the positive role of small forest patches in sustaining population connectivity, the long-term viability of populations and prospects for recovery. Main Conclusions: Our results suggest that orangutan populations in Borneo could potentially recover from recent declines if removal of orangutans by hunting, retaliatory killings, capture and translocation is reduced, and habitat connectivity is maintained within human-modified landscapes. These findings emphasize the urgent need for conservation strategies that mitigate negative human-wildlife interactions, and/or help preserve habitat and fragments as stepping stones. Measures could include promoting coexistence with local communities and translocating orangutans only in rare cases where no suitable alternative exists, to ensure the long-term survival of orangutan populations in Borneo