How complex do models need to be to predict dispersal of threatened species through matrix habitats?

Movement and Demography of At-Risk Butterflies: Building Blocks for Conservation

The number of insect species at risk of population decline and extinction is increasing rapidly. Yet we know almost nothing about the ecology of these species, except for at-risk butterflies. A growing body of literature shows how butterfly vital rates, including demography and movement, are essential for guiding conservation and recovery. History has shown us that without these data, conservation decisions often weaken, rather than enhance, population viability. This is especially true in changing landscapes. We review knowledge of vital rates across all at-risk butterflies. We have information on movement for 17 of 283 butterfly species and information on demography for 19 species. We find that habitat-specific movement behavior is key to understanding how to connect populations, and habitat-specific demography is central to managing habitats. Methods and analyses worked out for butterflies can provide a scaffold around which to build studies for the conservation of other at-risk insects.

Individual variation changes dispersal distance and area requirements of a checkerspot butterfly

Individual variation in movement can have important consequences for spatial population dynamics. For instance, individual variation increases leptokurtosis in dispersal distance, such that more individuals move very short and very long distances relative to a homogeneous population. We quantified individual variation in movement of the Baltimore checkerspot butterfly (Euphydryas phaeton) to investigate its importance for two conservation-related metrics: the expected dispersal distance and the critical minimum patch size, or the smallest area within which a population can persist based on loss due to emigration. All movement parameters showed among-individual variation, with the greatest variation in move lengths and time spent resting. Correlations in among-individual movement parameters indicated that some butterflies were generally more mobile than others. We incorporated empirically estimated movement and demographic parameters into two individual-based models (IBMs), one with homogeneity in movement among individuals, and one with heterogeneity in movement. As expected, individual variation in movement increased the leptokurtosis of lifetime movement distance; the maximum difference in distance moved was substantial (-850 m vs. -5800 m) and is likely of significance for conservation. Individual variation also affected the critical minimum patch size, but the difference (-0.7 ha vs. -0.5 ha) is unlikely to be ecologically significant. Notably, populations with individual variation had higher growth rates in small patches and lower growth rates in large patches, a logical consequence of increased leptokurtosis. Individual variation in movement is fairly straightforward to quantify using mixed effects models and is important for spatial population dynamics, thus we encourage its inclusion in studies of other systems.

Habitat restoration affects immature stages of a wetland butterfly through indirect effects on predation

Habitat loss worldwide has led to the widespread use of restoration practices for the recovery of imperiled species. However, recovery success may be hampered by focusing on plant communities, rather than the complex suite of direct and indirect interactions among trophic levels that occur in natural systems. Through a factorial field experiment, we tested the effects of wetland restoration on egg and juvenile survival of a locally rare butterfly, Satyrodes appalachia, via tree removal and damming. Tree removal more than tripled S. appalachia host plant abundance, but neither restoration action directly affected S. appalachia egg and juvenile survival. Instead, we found strong indirect effects of habitat manipulation on S. appalachia egg and juvenile survival that were mediated through predation. The interaction of tree removal and damming significantly decreased predation of S. appalachia eggs relative to each treatment alone. Damming alone had a significant positive indirect effect on the survival of S. appalachia juveniles, likely because increases in standing water reduced predator access. Our results emphasize the need for experiments that evaluate the demographic responses of imperiled species to habitat restoration prior to management action and quantify potential indirect effects mediated through higher trophic levels.

Defining and evaluating the umbrella species concept for conserving and restoring landscape connectivity

Conserving or restoring landscape connectivity between patches of breeding habitat is a common strategy to protect threatened species from habitat fragmentation. By managing connectivity for some species, usually charismatic vertebrates, it is often assumed that these species will serve as conservation umbrellas for other species. We tested this assumption by developing a quantitative method to measure overlap in dispersal habitat of 3 threatened species-a bird (the umbrella), a butterfly, and a frog-inhabiting the same fragmented landscape. Dispersal habitat was determined with Circuitscape, which was parameterized with movement data collected for each species. Despite differences in natural history and breeding habitat, we found substantial overlap in the spatial distributions of areas important for dispersal of this suite of taxa. However, the intuitive umbrella species (the bird) did not have the highest overlap with other species in terms of the areas that supported connectivity. Nevertheless, we contend that when there are no irreconcilable differences between the dispersal habitats of species that cohabitate on the landscape, managing for umbrella species can help conserve or restore connectivity simultaneously for multiple threatened species with different habitat requirements.

The trajectory of dispersal research in conservation biology. Systematic review

Dispersal knowledge is essential for conservation management, and demand is growing. But are we accumulating dispersal knowledge at a pace that can meet the demand? To answer this question we tested for changes in dispersal data collection and use over time. Our systematic review of 655 conservation-related publications compared five topics: climate change, habitat restoration, population viability analysis, land planning (systematic conservation planning) and invasive species. We analysed temporal changes in the: (i) questions asked by dispersal-related research; (ii) methods used to study dispersal; (iii) the quality of dispersal data; (iv) extent that dispersal knowledge is lacking, and; (v) likely consequences of limited dispersal knowledge. Research questions have changed little over time; the same problems examined in the 1990s are still being addressed. The most common methods used to study dispersal were occupancy data, expert opinion and modelling, which often provided indirect, low quality information about dispersal. Although use of genetics for estimating dispersal has increased, new ecological and genetic methods for measuring dispersal are not yet widely adopted. Almost half of the papers identified knowledge gaps related to dispersal. Limited dispersal knowledge often made it impossible to discover ecological processes or compromised conservation outcomes. The quality of dispersal data used in climate change research has increased since the 1990s. In comparison, restoration ecology inadequately addresses large-scale process, whilst the gap between knowledge accumulation and growth in applications may be increasing in land planning. To overcome apparent stagnation in collection and use of dispersal knowledge, researchers need to: (i) improve the quality of available data using new approaches; (ii) understand the complementarities of different methods and; (iii) define the value of different kinds of dispersal information for supporting management decisions. Ambitious, multi-disciplinary research programs studying many species are critical for advancing dispersal research.

SEARCH: Spatially Explicit Animal Response to Composition of Habitat

Complex decisions dramatically affect animal dispersal and space use. Dispersing individuals respond to a combination of fine-scale environmental stimuli and internal attributes. Individual-based modeling offers a valuable approach for the investigation of such interactions because it combines the heterogeneity of animal behaviors with spatial detail. Most individual-based models (IBMs), however, vastly oversimplify animal behavior and such behavioral minimalism diminishes the value of these models. We present program SEARCH (Spatially Explicit Animal Response to Composition of Habitat), a spatially explicit, individual-based, population model of animal dispersal through realistic landscapes. SEARCH uses values in Geographic Information System (GIS) maps to apply rules that animals follow during dispersal, thus allowing virtual animals to respond to fine-scale features of the landscape and maintain a detailed memory of areas sensed during movement. SEARCH also incorporates temporally dynamic landscapes so that the environment to which virtual animals respond can change during the course of a simulation. Animals in SEARCH are behaviorally dynamic and able to respond to stimuli based upon their individual experiences. Therefore, SEARCH is able to model behavioral traits of dispersing animals at fine scales and with many dynamic aspects. Such added complexity allows investigation of unique ecological questions. To illustrate SEARCH's capabilities, we simulated case studies using three mammals. We examined the impact of seasonally variable food resources on the weight distribution of dispersing raccoons (Procyon lotor), the effect of temporally dynamic mortality pressure in combination with various levels of behavioral responsiveness in eastern chipmunks (Tamias striatus), and the impact of behavioral plasticity and home range selection on disperser mortality and weight change in virtual American martens (Martes americana). These simulations highlight the relevance of SEARCH for a variety of applications and illustrate benefits it can provide for conservation planning.