A Comparison of Corridors and Intrinsic Connectivity to Promote Dispersal in Transient Successional Landscapes

Low-vagility organisms that specialize on transitory successional habitats may be especially dependent upon habitat connectivity to maintain population viability. We analyzed the theoretical intrinsic connectivity of successional landscapes (i.e., the natural juxtaposition of similar habitats that allows dispersal) as a function of patch geometry coupled with the disperser's habitat specificity. Habitat specialists living in poorly connected landscapes (approximating hexagonal patches) have only a 26.5% chance of colonizing a new site when their resident patch becomes unsuitable. In contrast, generalists living in well connected landscapes can virtually always colonize a new site when needed. We infer from our simulation that for some habitat specialists, such as the rare, endemic Florida scrub lizard (Sceloporus woodi), anthropogenic control of successional dynamics for commercial logging may significantly reduce intrinsic connectivity. Lizard population viability may now depend upon the extrinsic connectivity provided by artificial corridors. However, the use of corridors will not serve as a general solution to the problem of anthropogenically reduced intrinsic connectivity until key logistical design problems have been resolved. Moreover, efforts to enhance intrinsic connectivity by modifying patch geometry may produce undesirable edge effects and conflict with old-growth preservation. Future research should focus on developing spatially explicit corridor models, documenting natural levels of intrinsic connectivity, quantifying anthropogenic disruption of natural connectivity, and describing species-specific mechanisms of inter-patch dispersal.     

Spatial uncertainty analysis of population models

This paper describes an approach for conducting spatial uncertainty analysis of spatial population models, and illustrates the ecological consequences of spatial uncertainty for landscapes with different properties. Spatial population models typically simulate birth, death, and migration on an input map that describes habitat. Typically, only a single “reference” map is available, but we can imagine that a collection of other, slightly different, maps could be drawn to represent a particular species’ habitat. As a first approximation, our approach assumes that spatial uncertainty (i.e., the variation among values assigned to a location by such a collection of maps) is constrained by characteristics of the reference map, regardless of how the map was produced. Our approach produces lower levels of uncertainty than alternative methods used in landscape ecology because we condition our alternative landscapes on local properties of the reference map. Simulated spatial uncertainty was higher near the borders of patches. Consequently, average uncertainty was highest for reference maps with equal proportions of suitable and unsuitable habitat, and no spatial autocorrelation. We used two population viability models to evaluate the ecological consequences of spatial uncertainty for landscapes with different properties. Spatial uncertainty produced larger variation among predictions of a spatially explicit model than those of a spatially implicit model. Spatially explicit model predictions of final female population size varied most among landscapes with enough clustered habitat to allow persistence. In contrast, predictions of population growth rate varied most among landscapes with only enough clustered habitat to support a small population, i.e., near a spatially mediated extinction threshold. We conclude that spatial uncertainty has the greatest effect on persistence when the amount and arrangement of suitable habitat are such that habitat capacity is near the minimum required for persistence.     

Dynamics of Hybridization and Introgression in Red Wolves and Coyotes

Abstract:  Hybridization and introgression are significant causes of endangerment in many taxa and are considered the greatest biological threats to the reintroduced population of red wolves ( Canis rufus ) in North Carolina (U.S.A.). Little is known, however, about these processes in red wolves and coyotes ( C. latrans ). We used individual-based simulations to examine the process of hybridization and introgression between these species. Under the range of circumstances we considered, red wolves in colonizing and established populations were quickly extirpated, persisted near the carrying capacity, or had intermediate outcomes. Sensitivity analyses suggested that the probabilities of quasi extinction and persistence of red wolves near the carrying capacity were most affected by the strength of two reproductive barriers: red wolf challenges and assortative mating between red wolves and coyotes. Because model parameters for these barriers may be difficult to estimate, we also sought to identify other predictors of red wolf population fate. The proportion of pure red wolves in the population was a strong predictor of the future probabilities of red wolf quasi extinction and persistence. Finally, we examined whether sterilization can be effective in minimizing introgression while allowing the reintroduced red wolf population to grow. Our results suggest sterilization can be an effective short-term strategy to reduce the likelihood of extirpation in colonizing populations of red wolves. Whether red wolf numbers are increased by sterilization depends on the level of sterilization effort and the acting reproductive barriers. Our results provide an outline of the conditions likely required for successful reestablishment and long-term maintenance of populations of wild red wolves in the presence of coyotes. Our modeling approach may prove generally useful in providing insight into situations involving complex species interactions when data are few.     

Genetic Structure and Migration in Native and Reintroduced Rocky Mountain Wolf Populations

Gray wolf (Canis lupus) recovery in the Rocky Mountains of the U.S. is proceeding by both natural recolonization and managed reintroduction. We used DNA microsatellite analysis of wolves transplanted from Canada to two reintroduction sites in the U.S. to study population structure in native and reintroduced wolf populations. Gene flow due to migration between regions in Canada is substantial, and all three recovery populations in the U.S. had high genetic variation. The reintroduced founders were moderately genetically divergent from the naturally colonizing U.S. population. These findings corroborate that the reintroduction more than meets generally accepted genetic guidelines. Maintaining this variation, however, will depend on ample reproduction in the first few generations. In the long term genetic variation will best be retained if migration occurs among the recolonizing and the two transplanted populations. Evidence from field observation and genetic studies shows extensive dispersal by wolves, and we conclude that exchange among these groups due to natural dispersal is likely if public tolerance and legal protection are adequate outside lands designated for wolf recovery.     

The Application of Neutral Landscape Models in Conservation Biology

Neutral landscape models, derived from percolation theory in the field of landscape ecology, are grid-based maps in which complex habitat distributions are generated by random or fractal algorithms. This grid-based representation of landscape structure is compatible with the raster-based format of geographical information systems (GIS), which facilitates comparisons between theoretical and real landscapes. Neutral landscape models permit the identification of critical thresholds in connectivity, which can be used to predict when landscapes will become fragmented. The coupling of neutral landscape models with generalized population models, such as metapopulation theory, provides a null model for generating predictions about population dynamics in fragmented landscapes. Neutral landscape models can contribute to the following applications in conservation: (1) incorporation of complex spatial patterns in (meta)population models; (2) identification of species' perceptions of landscape structure; (3) determination of landscape connectivity; (4) evaluation of the consequences of habitat fragmentation for population subdivision; (5) identification of the domain of metapopulation dynamics; (6) prediction of the occurrence of extinction thresholds; ( 7) determination of the genetic consequences of habitat fragmentation; and (8) reserve design and ecosystem management. This generalized, spatially explicit framework bridges the gap between spatially implicit, patch-based models and spatially realistic GIS applications which are usually parameterized for a single species in a specific landscape. Development of a generalized, spatially explicit framework is essential in conservation biology because we will not be able to develop individual models for every species of management concern.     

Improving supplementary feeding in species conservation

Supplementary feeding is often a knee‐jerk reaction to population declines, and its application is not critically evaluated, leading to polarized views among managers on its usefulness. Here, we advocate a more strategic approach to supplementary feeding so that the choice to use it is clearly justified over, or in combination with, other management actions and the predicted consequences are then critically assessed following implementation. We propose combining methods from a set of specialist disciplines that will allow critical evaluation of the need, benefit, and risks of food supplementation. Through the use of nutritional ecology, population ecology, and structured decision making, conservation managers can make better choices about what and how to feed by estimating consequences on population recovery across a range of possible actions. This structured approach also informs targeted monitoring and more clearly allows supplementary feeding to be integrated in recovery plans and reduces the risk of inefficient decisions. In New Zealand, managers of the endangered Hihi (Notiomystis cincta) often rely on supplementary feeding to support reintroduced populations. On Kapiti island the reintroduced Hihi population has responded well to food supplementation, but the logistics of providing an increasing demand recently outstretched management capacity. To decide whether and how the feeding regime should be revised, managers used a structured decision making approach informed by population responses to alternative feeding regimes. The decision was made to reduce the spatial distribution of feeders and invest saved time in increasing volume of food delivered into a smaller core area. The approach used allowed a transparent and defendable management decision in regard to supplementary feeding, reflecting the multiple objectives of managers and their priorities.     

Demographic Limitations of the Ability of Habitat Restoration to Rescue Declining Populations

Abstract:  Habitat restoration is often recommended in conservation without first evaluating whether populations are in fact habitat limited and thus whether declining populations can be stabilized or recovered through habitat restoration. We used a spatially structured demographic model coupled with a dynamic neutral landscape model to evaluate whether habitat restoration could rescue populations of several generic migratory songbirds that differed in their sensitivity to habitat fragmentation (i.e., severity of edge effects on nesting success). Simulating a best-case scenario, landscapes were instantly restored to 100% habitat before, at, or after habitat loss exceeded the species' vulnerability threshold. The vulnerability threshold is a measure of extinction risk, in which the change in population growth rate ( δλ ) scaled to the rate of habitat loss ( δh ) falls below −1% ( δλ/δh ≤ −0.01). Habitat restoration was most effective for species with low-to-moderate edge sensitivities and in landscapes that had not previously experienced extensive fragmentation. To stabilize populations of species that were highly edge sensitive or any species in heavily fragmented landscapes, restoration needed to be initiated long before the vulnerability threshold was reached. In practice, habitat restoration is generally not initiated until a population is at risk of extinction, but our model results demonstrate that some populations cannot be recovered at this point through habitat restoration alone. At this stage, habitat loss and fragmentation have seriously eroded the species' demographic potential such that halting population declines is limited more by demographic factors than the amount of available habitat. Evidence that populations decline in response to habitat loss is thus not sufficient to conclude that habitat restoration will be sufficient to rescue declining populations.     

Assessing the effects of disease and bleaching on Florida Keys corals by fitting population models to data

Coral diseases have increased in frequency over the past few decades and have important influences on the structure and composition of coral reef communities. However, there is limited information on the etiologies of many coral diseases, and pathways through which coral diseases are acquired and transmitted are still in question. Furthermore, it is difficult to assess the impacts of disease on coral populations because outbreaks often co-occur with temperature-induced bleaching and anthropogenic stressors. We developed spatially explicit population models of coral disease and bleaching dynamics to quantify the impact of six common diseases on Florida Keys corals, including aspergillosis, dark spots, white band, white plague, white patch, and Caribbean yellow band. Models were fit to an 8-year data set of coral abundance, disease prevalence, and bleaching prevalence. Model selection was used to assess alternative pathways for disease transmission, and the influence of environmental stressors, including sea temperature and human population density, on disease prevalence and coral mortality. Classic disease transmission from contagious to susceptible colonies provided the best-fit model only for aspergillosis. For other diseases, external disease forcing, such as through a vector or directly from pathogens in the environment, provided the best fit to observed data. Estimates of disease reproductive ratio values (R₀) were less than one for each disease, indicating coral colonies were below densities required for diseases to become established through contagious spread alone. Incidences of white band and white patch disease were associated with greater susceptibility or slower recovery of bleached colonies, and no disease outbreaks were associated with periods of elevated sea temperatures alone. Projections of best-fit models indicated that, atleast during the period of this study, disease and bleaching did not have substantial impacts on populations and impaired rates of population growth appeared to be attributable to other stressors. By applying epidemiological models to field data, our study gives qualitative insights into the dynamics of coral diseases, relative stressor impacts, and directions for future research.     

How does the spatial structure of habitat loss affect the eco-epidemic dynamics?

Habitat loss is considered as one of the primary causes of species extinction, especially for a species that also suffers from an epidemic disease. Little attention has been paid to the combined effect of habitat loss and epidemic transmission on the species spatiotemporal dynamics. Here, a spatial model of the parasite–host/prey–predator eco-epidemiological system with habitat loss was studied. Habitat patches in the model, instead of undergoing a random loss, were spatially clustered by different degrees. Not only the quantity of habitat loss but also its clustering degree was shown to affect the equilibrium of the system. The infection rate and the probability of successful predation were keys to determine the spatial patterns of species. The epidemic disease is more likely to break out if only a small amount of suitable patches were lost. Counter-intuitively, infected preys are more sensitive to habitat loss than predators if the lost patches are highly clustered. This result is new to eco-epidemiology and implies a possibility of using spatial arrangement of suitable (or unsuitable) patches to control the spread of epidemics in the ecological system.     

Simulation and analysis of outbreaks of bark beetle infestations and their management at the stand level

Outbreaks of bark beetles in forests can result in substantial economic losses. Understanding the factors that influence the development and spread of bark beetle outbreaks is crucial for forest management and for predicting outbreak risks, especially with the expected global warming. Although much research has been done on the ecology and phenology of bark beetles, the complex interplay between beetles, host trees, beetle antagonists and forest management makes predicting beetle population development especially difficult. Using the recent infestations of the European Spruce Bark Beetle (Ips typographus L. Col. Scol.) in the Bavarian Forest National Park (Germany) as a case study, we developed a spatially explicit agent-based simulation model (SAMBIA) that takes into account individual trees and beetles. This model primarily provides a tool for analysing and understanding the spatial and temporal aspects of bark beetles outbreaks at the stand scale. Furthermore, the model should allow an estimation of the effectiveness of concurrent impacts of both antagonists and management to confine outbreak dynamics in practice. We also used the model to predict outbreak probabilities in various settings. The simulation results indicated a distinct threshold behaviour of the system in response to pressure by antagonists or management of the bark beetle population. Despite the different scenarios considered, we were able to extract from the simulations a simple rule of thumb for the successful control of an outbreak: if roughly 80% of individual beetles are killed by antagonists or foresters, outbreaks will rarely take place. Our model allows the core dynamics of this complex system to be reduced to this inherent common denominator.     

Aphid population response to agricultural landscape change: A spatially explicit,individual-based model

A spatially explicit individual-based simulation model has been developed to represent aphid population dynamics in agricultural landscapes. The application of the model to Rhopalosiphum padi (L.) population dynamics is detailed, including an outline of the construction of the model, its parameterisation and validation. Over time, the aphids interact with the landscape and with one another. The landscape is modified by varying a simple pesticide regime, and the multi-scale spatial and temporal implications for a population of aphids is analysed. The results show that a spatial modelling approach that considers the effects on the individual of landscape properties and factors such as wind speed and wind direction provides novel insight into aphid population dynamics both spatially and temporally. This forms the basis for the development of further simulation models that can be used to analyse how changes in landscape structure impact upon important species distributions and population dynamics.     

Controlling range expansion in habitat networks by adaptively targeting source populations

Controlling the spread of invasive species, pests, and pathogens is often logistically limited to interventions that target specific locations at specific periods. However, in complex, highly connected systems, such as marine environments connected by ocean currents, populations spread dynamically in both space and time via transient connectivity links. This results in nondeterministic future distributions of species in which local populations emerge dynamically and concurrently over a large area. The challenge, therefore, is to choose intervention locations that will maximize the effectiveness of the control efforts. We propose a novel method to manage dynamic species invasions and outbreaks that identifies the intervention locations most likely to curtail population expansion by selectively targeting local populations most likely to expand their future range. Critically, at any point during the development of the invasion or outbreak, the method identifies the local intervention that maximizes the long‐term benefit across the ecosystem by restricting species’ potential to spread. In so doing, the method adaptively selects the intervention targets under dynamically changing circumstances. To illustrate the effectiveness of the method we applied it to controlling the spread of crown‐of‐thorns starfish (Acanthaster sp.) outbreaks across Australia's Great Barrier Reef. Application of our method resulted in an 18‐fold relative improvement in management outcomes compared with a random targeting of reefs in putative starfish control scenarios. Although we focused on applying the method to reducing the spread of an unwanted species, it can also be used to facilitate the spread of desirable species through connectivity networks. For example, the method could be used to select those fragments of habitat most likely to rebuild a population if they were sufficiently well protected.     

Local population size in a flightless insect: importance of patch structure-dependent mortality

In spatially heterogeneous systems, utilizing population models to integrate the effects of multiple population rates can yield powerful insights into the relative importance of the component rates. The relative importance of demographic rates and dispersal in shaping the distribution of the western tussock moth (Orgyia vetusta) among patches of its host plant was explored using stage-structured population models. Tussock moth dispersal occurs passively in first-instar larvae and is poor or absent in all other life stages. Spatial surveys suggested, however, that moth distribution is not well explained by passive dispersal; moth populations were greater on small patches and on isolated ones. Further analysis showed that several local demographic rates varied significantly with patch characteristics. Two mortality factors in particular may explain the observed patterns. First, crawler mortality both increased with patch size and was density-dependent. A single-patch difference equation model showed mortality related to patch size is strong enough to overcome the homogenizing effect of density dependence; greater equilibrium densities were predicted for smaller patches. Second, although three rates were found to vary with local patch density, only pupal parasitism by a chalcid wasp could potentially account for higher moth abundances on isolated patches. A spatially explicit simulation model of the multiple-patch system showed that spatial variation in pupal parasitism is indeed strong enough to generate such a pattern. These results demonstrate that habitat spatial structure can affect multiple population processes simultaneously, and even relatively low attack rates imposed on a reproductively valuable life stage of the host can have a dominant effect on population distribution among habitat patches.     

Modeling range dynamics in heterogeneous landscapes: invasion of the hemlock woolly adelgid in eastern North America

Range expansion by native and exotic species will continue to be a major component of global change. Anticipating the potential effects of changes in species distributions requires models capable of forecasting population spread across realistic, heterogeneous landscapes and subject to spatiotemporal variability in habitat suitability. Several decades of theory and model development, as well as increased computing power and availability of fine-resolution GIS data, now make such models possible. Still unanswered, however, is the question of how well this new generation of dynamic models will anticipate range expansion. Here we develop a spatially explicit stochastic model that combines dynamic dispersal and population processes with fine-resolution maps characterizing spatiotemporal heterogeneity in climate and habitat to model range expansion of the hemlock woolly adelgid (HWA; Adelges tsugae). We parameterize this model using multiyear data sets describing population and dispersal dynamics of HWA and apply it to eastern North America over a 57-year period (1951-2008). To evaluate the model, the observed pattern of spread of HWA during this same period was compared to model predictions. Our model predicts considerable heterogeneity in the risk of HWA invasion across space and through time, and it suggests that spatiotemporal variation in winter temperature, rather than hemlock abundance, exerts a primary control on the spread of HWA. Although the simulations generally matched the observed current extent of the invasion of HWA and patterns of anisotropic spread, it did not correctly predict when HWA was observed to arrive in different geographic regions. We attribute differences between the modeled and observed dynamics to an inability to capture the timing and direction of long-distance dispersal events that substantially affected the ensuing pattern of spread.     

Why are metapopulations so rare?

Roughly 40 years after its introduction, the metapopulation concept is central to population ecology. The notion that local populations and their dynamics may be coupled by dispersal is without any doubt of great importance for our understanding of population-level processes. A metapopulation describes a set of subpopulations linked by (rare) dispersal events in a dynamic equilibrium of extinctions and recolonizations. In the large body of literature that has accumulated, the term "metapopulation" is often used in a very broad sense; most of the time it simply implies spatial heterogeneity. A number of reviews have recently addressed this problem and have pointed out that, despite the large and still growing popularity of the metapopulation concept, there are only very few empirical examples that conform with the strict classical metapopulation (CM) definition. In order to understand this discrepancy between theory and observation, we use an individual-based modeling approach that allows us to pinpoint the environmental conditions and the life-history attributes required for the emergence of a CM structure. We find that CM dynamics are restricted to a specific parameter range at the border between spatially structured but completely occupied and globally extinct populations. Considering general life-history attributes, our simulations suggest that CMs are more likely to occur in arthropod species than in (large) vertebrates. Since the specific type of spatial population structure determines conservation concepts, our findings have important implications for conservation biology. Our model suggests that most spatially structured populations are panmictic, patchy, or of mainland-island type, which makes efforts spent on increasing connectivity (e.g., corridors) questionable. If one does observe a true CM structure, this means that the focal metapopulation is on the brink of extinction and that drastic conservation measures are needed.     

Modelling with uncertainty: Introducing a probabilistic framework to predict animal population dynamics

Predictive population models designed to assist managers and policy makers require an explicit treatment of inherent uncertainty and variability. These are particular concerns when modelling non-native and reintroduced species, when data have been collected within one geographical or ecological context but predictions are required for another, or when extending models to predict the consequences of environmental change (e.g., climate or land-use). We present an aspatial, probabilistic framework of hierarchical process models for predicting population growth even when data are sparse or of poor quality. Insight into the factors affecting population dynamics in real landscapes can be provided and Kullback–Leibler distances are used to compare the relative output of models. This flexible yet robust framework gives easily interpretable results, allowing managers as well as modellers to invalidate anomalous models and apply others to real-life scenarios.We illustrate the framework’s power with a meta-analysis of European wild boar (Sus scrofa) data. We test hypotheses about the effect of geographic region, hunting and mast years on wild boar population growth, to build models of wild boar dynamics for the UK. The framework quantifies the importance of hunting pressure as a driver of population growth, and confirms that reproductive success is greatly decreased in poor mast years, suggesting that the key to predicting wild boar dynamics is to ascertain local hunting pressure and to better understand changing food availability. Geography had no significant effect, indicating that it is not a good proxy for modelling the impact of change in climate or land-use on wild boar populations at the European scale. We use the framework to predict population abundance 9 years after an isolated population of wild boar established in the UK; in a comparison with the only field data and two independent modelling exercises, our framework provides the most robust and informative results.     

Effectiveness of Corridors Relative to Enlargement of Habitat Patches

Abstract:  The establishment of biological corridors between two otherwise isolated habitat patches is a common yet contentious strategy for conserving populations in fragmented landscapes. We compared the effectiveness of corridors with the effectiveness of an alternate conservation strategy, the enlargement of existing habitat patches. We used a spatially explicit population model that simulated population size in two kinds of patches. One patch had a corridor that connected it to a larger "source" patch and the other patch was unconnected and enlarged at the periphery by an area the same size as the corridor. Patch isolation, corridor width, patch size, and the probability that individuals would cross the border from habitat to matrix were varied independently. In general, population size was greater in enlarged patches than in connected patches when patches were relatively large and isolated. Corridor width and the probability of crossing the border from habitat to matrix did not affect the relative benefit of corridors versus patch enlargement. Although biological corridors may mitigate potential effects of inbreeding depression at long time scales, our results suggest that they are not always the best method of conserving fragmented populations.     

The influence of environmental spatial structure on the life-history traits and diversity of species in a metacommunity

Several models have been proposed to understand how so many species can coexist in ecosystems. Despite evidence showing that natural habitats are often patchy and fragmented, these models rarely take into account environmental spatial structure. In this study we investigated the influence of spatial structure in habitat and disturbance regime upon species’ traits and species’ coexistence in a metacommunity. We used a population-based model to simulate competing species in spatially explicit landscapes. The species traits we focused on were dispersal ability, competitiveness, reproductive investment and survival rate. Communities were characterized by their species richness and by the four life-history traits averaged over all the surviving species. Our results show that spatial structure and disturbance have a strong influence on the equilibrium life-history traits within a metacommunity. In the absence of disturbance, spatially structured landscapes favour species investing more in reproduction, but less in dispersal and survival. However, this influence is strongly dependent on the disturbance rate, pointing to an important interaction between spatial structure and disturbance. This interaction also plays a role in species coexistence. While spatial structure tends to reduce diversity in the absence of disturbance, the tendency is reversed when disturbance occurs. In conclusion, the spatial structure of communities is an important determinant of their diversity and characteristic traits. These traits are likely to influence important ecological properties such as resistance to invasion or response to climate change, which in turn will determine the fate of ecosystems facing the current global ecological crisis.     

Long-Term Population Development of a Reintroduced Beaver (Castor fiber) Population in Sweden

Deliberate reintroductions of locally exterminated animal species to areas within their former ranges is an increasingly important conservation tool. Most reintroductions are fairly recent and still in an initial phase of population development. There are few long-term studies of reintroduced populations. The aim of this study was to see if the population development of the reintroduced European beaver ( Castor fiber ) population in Sweden exhibits the same pattern of population development as other introductions, in accordance with general theories, and to discuss possible management consequences. Since the European beaver was reintroduced to Sweden 70 years ago, the population has developed in a way predicted by the Riney-Caughley model for introduced ungulates, exhibiting an irruption and a subsequent decline. In two study areas, the rate of population increase (r) turned negative after 34 and 25 years and at densities of 0.25 and 0.20 colonies/km², respectively. The data suggest that management policy for an irruptive species should allow hunting during the rapid-increase phase, thus maintaining food resources and avoiding uncontrolled population decline.     

The Conservation Relevance of Epidemiological Research into Carnivore Viral Diseases in the Serengeti

Abstract:  Recent outbreaks of rabies and canine distemper in wildlife populations of the Serengeti show that infectious disease constitutes a significant cause of mortality that can result in regional extirpation of endangered species even within large, well-protected areas. Nevertheless, effective management of an infectious disease depends critically on understanding the epidemiological dynamics of the causative pathogen. Pathogens with short infection cycles cannot persist in small populations in the absence of a more permanent reservoir of infection. Development of appropriate interventions requires detailed data on transmission pathways between reservoirs and wildlife populations of conservation concern. Relevant data can be derived from long-term population monitoring, epidemic and case-surveillance patterns, genetic analyses of rapidly evolving pathogens, serological surveys, and intervention studies. We examined studies of carnivore diseases in the Serengeti. Epidemiological research contributes to wildlife conservation policy in terms of management of endangered populations and the integration of wildlife conservation with public health interventions. Long-term, integrative, cross-species research is essential for formulation of effective policy for disease control and optimization of ecosystem health.