Patrick A. Zollner

Towards a behavioral ecology of ecological landscapes

Recent developments in landscape-level ecological modeling rest upon poorly understood behavioral phenomena. Surprisingly, these phenomena include animal movement and habitat selection, two areas with a long history of study in behavioral ecology. A major problem in applying traditional behavioral ecology to landscape-level ecological problems is that ecologists and behaviorists work at very different spatial scales. Thus a behavioral ecology of ecological landscapes would strive to overcome this inopportune differential in spatial scales. Such a landscape-conscious behavioral undertaking would not only establish more firmly the link between behavior and ecological systems, but also catalyze the study of basic biological phenomena of Interest to behaviorists and ecologists alike.

Improving the forecast for biodiversity under climate change

BACKGROUND As global climate change accelerates, one of the most urgent tasks for the coming decades is to develop accurate predictions about biological responses to guide the effective protection of biodiversity. Predictive models in biology provide a means for scientists to project changes to species and ecosystems in response to disturbances such as climate change. Most current predictive models, however, exclude important biological mechanisms such as demography, dispersal, evolution, and species interactions. These biological mechanisms have been shown to be important in mediating past and present responses to climate change. Thus, current modeling efforts do not provide sufficiently accurate predictions. Despite the many complexities involved, biologists are rapidly developing tools that include the key biological processes needed to improve predictive accuracy. The biggest obstacle to applying these more realistic models is that the data needed to inform them are almost always missing. We suggest ways to fill this growing gap between model sophistication and information to predict and prevent the most damaging aspects of climate change for life on Earth. ADVANCES On the basis of empirical and theoretical evidence, we identify six biological mechanisms that commonly shape responses to climate change yet are too often missing from current predictive models: physiology; demography, life history, and phenology; species interactions; evolutionary potential and population differentiation; dispersal, colonization, and range dynamics; and responses to environmental variation. We prioritize the types of information needed to inform each of these mechanisms and suggest proxies for data that are missing or difficult to collect. We show that even for well-studied species, we often lack critical information that would be necessary to apply more realistic, mechanistic models. Consequently, data limitations likely override the potential gains in accuracy of more realistic models. Given the enormous challenge of collecting this detailed information on millions of species around the world, we highlight practical methods that promote the greatest gains in predictive accuracy. Trait-based approaches leverage sparse data to make more general inferences about unstudied species. Targeting species with high climate sensitivity and disproportionate ecological impact can yield important insights about future ecosystem change. Adaptive modeling schemes provide a means to target the most important data while simultaneously improving predictive accuracy. OUTLOOK Strategic collections of essential biological information will allow us to build generalizable insights that inform our broader ability to anticipate species’ responses to climate change and other human-caused disturbances. By increasing accuracy and making uncertainties explicit, scientists can deliver improved projections for biodiversity under climate change together with characterizations of uncertainty to support more informed decisions by policymakers and land managers. Toward this end, a globally coordinated effort to fill data gaps in advance of the growing climate-fueled biodiversity crisis offers substantial advantages in efficiency, coverage, and accuracy. Biologists can take advantage of the lessons learned from the Intergovernmental Panel on Climate Change’s development, coordination, and integration of climate change projections. Climate and weather projections were greatly improved by incorporating important mechanisms and testing predictions against global weather station data. Biology can do the same. We need to adopt this meteorological approach to predicting biological responses to climate change to enhance our ability to mitigate future changes to global biodiversity and the services it provides to humans. Emerging models are beginning to incorporate six key biological mechanisms that can improve predictions of biological responses to climate change. Models that include biological mechanisms have been used to project (clockwise from top) the evolution of disease-harboring mosquitoes, future environments and land use, physiological responses of invasive species such as cane toads, demographic responses of penguins to future climates, climate-dependent dispersal behavior in butterflies, and mismatched interactions between butterflies and their host plants. Despite these modeling advances, we seldom have the detailed data needed to build these models, necessitating new efforts to collect the relevant data to parameterize more biologically realistic predictive models. New biological models are incorporating the realistic processes underlying biological responses to climate change and other human-caused disturbances. However, these more realistic models require detailed information, which is lacking for most species on Earth. Current monitoring efforts mainly document changes in biodiversity, rather than collecting the mechanistic data needed to predict future changes. We describe and prioritize the biological information needed to inform more realistic projections of species’ responses to climate change. We also highlight how trait-based approaches and adaptive modeling can leverage sparse data to make broader predictions. We outline a global effort to collect the data necessary to better understand, anticipate, and reduce the damaging effects of climate change on biodiversity.

Landscape-Level Perceptual Abilities in White-Footed Mice: Perceptual Range and the Detection of Forested Habitat

We define perceptual range as the distance from which an animal can perceive key landscape elements, such as distant patches of forested habitat. We argue that perceptual range should be a determinant of not only dispersal success in unfamiliar or hostile landscapes, but also of several landscape-level ecological processes influencing population dynamics. To redress the absence of empirical information on perceptual ranges, we simulated the dispersal of forest-dwelling white-footed mice (Peromyscus leucopus) across an agricultural landscape by releasing mice into unfamiliar, hostile agricultural habitat at various distances from fragments of forested habitat. We found that these forest mice have a remarkably low perceptual range with regard to detecting their forested (core) habitat. Mice released into bare fields failed to even orient towards forested habitat as little as 30 m distant, while mice in crop fields appeared unable to locate forest habitat as little as 10 m distant. These mice seemed to locate forested habitat by vision, despite the availability of non-visual cues. Future work will undoubtedly demonstrate vast differences in landscape-level perceptual abilities among animals, and show clearly that the ecological effects of a given landscape configuration will be influenced by the behavioral attributes of the species in question.

Predation, scramble competition, and the vigilance group size effect in dark-eyed juncos (Junco hyemalis)

Abstract In socially feeding birds and mammals, as group size increases, individuals devote less time to scanning their environment and more time to feeding. This vigilance “group size effect” has long been attributed to the anti-predatory benefits of group living, but many investigators have suggested that this effect may be driven by scramble competition for limited food. We addressed this issue of causation by focusing on the way in which the scan durations of free-living dark-eyed juncos (Junco hyemalis) decrease with group size. We were particularly interested in vigilance scanning concomitant with the handling of food items, since a decrease in food handling times (i.e. scan durations) with increasing group size could theoretically be driven by scramble competition for limited food resources. However, we showed that food-handling scan durations decrease with group size in an environment with an effectively unlimited food supply. Furthermore, this food-handling effect was qualitatively similar to that observed in the duration of standard vigilance scans (scanning exclusive of food ingestion), and both responded to changes in the risk of predation (proximity of a refuge) as one might expect based upon anti-predator considerations. The group size effects in both food-handling and standard scan durations may reflect a lesser need for personal information about risk as group size increases. Scramble competition may influence vigilance in some circumstances, but demonstrating an effect of competition beyond that of predation may prove challenging.

Anti-predatory vigilance and the limits to collective detection: visual and spatial separation between foragers

Abstract Collective detection concerns the idea that all members of a socially feeding group are alerted to an attack as long as at least one group member detects it. We found that collective detection in mixed flocks of emberizid sparrows is limited markedly by relatively small degrees of visual and spatial separation between foragers. These limits on collective detection appear to influence the degree to which flock members lower their vigilance with increasing group size (the group size effect). Specifically, the decrease in collective detection with increasing visual and spatial isolation between foragers is accompanied by a concomitant decrease in the strength of the vigilance group size effect. Explanations for the vigilance-related effects of such separation based upon a bird’s ability to monitor the vigilance behavior of flockmates can be ruled out for our experimental system. Our results also shed light on the issue of whether the vigilance group size effect is influenced more by collective detection or the simple dilution of risk with increasing group size. We argue that collective detection is not only an important determinant of the group size effect, but also that the phenomena of collective detection and risk dilution are interdependent.

Influence of forest management alternatives and land type on susceptibility to fire in northern Wisconsin, USA

We used the LANDIS disturbance and succession model to study the effects of six alternative vegetation management scenarios on forest succession and the subsequent risk of canopy fire on a 2791 km2 landscape in northern Wisconsin, USA. The study area is a mix of fire-prone and fire-resistant land types. The alternatives vary the spatial distribution of vegetation management activities to meet objectives primarily related to forest composition and recreation. The model simulates the spatial dynamics of differential reproduction, dispersal, and succession patterns using the vital attributes of species as they are influenced by the abiotic environment and disturbance. We simulated 50 replicates of each management alternative and recorded the presence of species age cohorts capable of sustaining canopy fire and the occurrence of fire over 250 years. We combined these maps of fuel and fire to map the probability of canopy fires across replicates for each alternative. Canopy fire probability varied considerably by land type. There was also a subtle, but significant effect of management alternative, and there was a significant interaction between land type and management alternative. The species associated with high-risk fuels (conifers) tend to be favored by management alternatives with more disturbances, whereas low disturbance levels favor low-risk northern hardwood systems dominated by sugar maple. The effect of management alternative on fire risk to individual human communities was not consistent across the landscape. Our results highlight the value of the LANDIS model for identifying specific locations where interacting factors of land type and management strategy increase fire risk.

Influence of Canopy Closure and Shrub Coverage on Travel along Coarse Woody Debris by Eastern Chipmunks (Tamias striatus)

Abstract We investigated relationships between canopy closure, shrub cover and the use of coarse woody debris as a travel path by eastern chipmunks (Tamias striatus) in the north central United States. Fine scale movements of chipmunks were followed with tracking spools and the percentage of each movement path directly along coarse woody debris was recorded. Availability of coarse woody debris was estimated using line intercepts. We predicted that, if chipmunks used coarse woody debris to reduce their risk of predation, movement along coarse woody debris would be greater for animals tracked at sites with open canopies and thick shrub cover. Travel along coarse woody debris was negatively associated with canopy closure and positively associated with the percent of coarse woody debris available at a site and the percentage of shrub cover at a site. Sex and age of eastern chipmunks did not appear to influence the amount of use of coarse woody debris. Our results suggest that coarse woody debris is more important to chipmunks in areas with open canopies and thick shrubs and are consistent with the hypothesis that coarse woody debris provides chipmunks with some protection from predators.

Human influence on the abundance and connectivity of high-risk fuels in mixed forests of northern Wisconsin, USA

Though fire is considered a “natural” disturbance, humans heavily influence modern wildfire regimes. Humans influence fires both directly, by igniting and suppressing fires, and indirectly, by either altering vegetation, climate, or both. We used the LANDIS disturbance and succession model to compare the relative importance of a direct human influence (suppression of low intensity surface fires) with an indirect human influence (timber harvest) on the long-term abundance and connectivity of high-risk fuel in a 2791 km2 landscape characterized by a mixture of northern hardwood and boreal tree species in northern Wisconsin. High risk fuels were defined as a combination of sites recently disturbed by wind and sites containing conifer species/cohorts that might serve as “ladder fuel” to carry a surface fire into the canopy. Two levels of surface fire suppression (high/current and low) and three harvest alternatives (no harvest, hardwood emphasis, and pine emphasis) were compared in a 2×3 factorial design using 5 replicated simulations per treatment combination over a 250-year period. Multivariate analysis of variance indicated that the landscape pattern of high-risk fuel (proportion of landscape, mean patch size, nearest neighbor distance, and juxtaposition with non fuel sites) was significantly influenced by both surface fire suppression and by forest harvest (p > 0.0001). However, the two human influences also interacted with each other (p < 0.001), because fire suppression was less likely to influence fuel connectivity when harvest disturbance was simultaneously applied. Temporal patterns observed for each of seven conifer species indicated that disturbances by either fire or harvest encouraged the establishment of moderately shade-tolerant conifer species by disturbing the dominant shade tolerant competitor, sugar maple. Our results conflict with commonly reported relationships between fire suppression and fire risk observed within the interior west of the United States, and illustrate the importance of understanding key interactions between natural disturbance, human disturbance, and successional responses to these disturbance types that will eventually dictate future fire risk.

Survival of Adult Martens in Northern Wisconsin

Abstract Low adult marten (Martes americana) survival may be one factor limiting their population growth >30 yr after their reintroduction in Wisconsin, USA. We estimated annual adult marten survival at 0.81 in northern Wisconsin, with lower survival during winter (0.87) than summer–fall (1.00). Fisher (Martes pennanti) and raptor kills were infrequent, and each reduced marten adult annual survival <10%. Annual adult survival was similar to or higher than survival in other areas, suggesting that it was not unusually low and therefore did not limit recovery of marten populations in northern Wisconsin. We captured few juvenile martens, suggesting low reproduction or reduced juvenile survival.

A Survival Estimate of Midwestern Adult Eastern Box Turtles Using Radiotelemetry

Abstract Eastern box turtles (Terrapene carolina carolina) are widespread in U.S. eastern deciduous forests, yet many populations are experiencing dramatic declines. Herein, we present an assessment of annual survival for adult eastern box turtles that were radio-tracked over a period of 2 y. Using a known fates Kaplan-Meier estimator, the baseline annual survival estimate for adult eastern box turtles in Indianas south-central region is 96.2%. Annual survival rates varied slightly between the hibernal period (95.6%) and the active period (96.7%). These initial data provide wildlife managers with a baseline from which a recovery period can be calculated. In areas where road mortality and human interface are high, this estimate should be adjusted to ensure the time for recovery is adequate. Further research is recommended over generations and age-classes to better inform management of this protected species.