Effects of anthropogenic landscapes on population maintenance of waterbirds

Anthropogenic impacts have reduced natural areas but increased the area of anthropogenic landscapes. There is debate about whether anthropogenic landscapes (e.g., farmlands, orchards, and fish ponds) provide alternatives to natural habitat and under what circumstances. We considered whether anthropogenic landscapes can mitigate population declines for waterbirds. We collected data on population trends and biological traits of 1203 populations of 579 species across the planet. Using Bayesian generalized linear mixed models, we tested whether the ability of a species to use an anthropogenic landscape can predict population trends of waterbird globally and of species of conservation concern. Anthropogenic landscapes benefited population maintenance of common but not less-common species. Conversely, the use of anthropogenic landscapes was associated with population declines for threatened species. Our findings delineate some limitations to the ability of anthropogenic landscapes to mitigate population declines, suggesting that the maintenance of global waterbird populations depends on protecting remaining natural areas and improving the habitat quality in anthropogenic landscapes. Article impact statement: Protecting natural areas and improving the quality of anthropogenic landscapes as habitat are both needed to achieve effective conservation.     

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.     

Efficacy of Land-Cover Models in Predicting Isolation of Marbled Salamander Populations in a Fragmented Landscape

Abstract:  Amphibians worldwide are facing rapid declines due to habitat loss and fragmentation, disease, and other causes. Where habitat alteration is implicated, there is a need for spatially explicit conservation plans. Models built with geographic information systems (GIS) are frequently used to inform such planning. We explored the potential for using GIS models of functional landscape connectivity as a reliable proxy for genetically derived measures of population isolation. We used genetic assignment tests to characterize isolation of marbled salamander populations and evaluated whether the relative amount of modified habitat around breeding ponds was a reliable indicator of population isolation. Using a resampling analysis, we determined whether certain land-cover variables consistently described population isolation. We randomly drew half the data for model building and tested the performance of the best models on the other half 100 times. Deciduous forest was consistently associated with lower levels of population isolation, whereas salamander populations in regions of agriculture and anthropogenic development were more isolated. Models that included these variables and pond size explained 65–70% of variation in genetically inferred isolation across sites. The resampling analysis confirmed that these habitat variables were consistently good predictors of isolation. Used judiciously, simple GIS models with key land-cover variables can be used to estimate population isolation if field sampling and genetic analysis are not possible.     

The Value of Using Feasibility Models in Systematic Conservation Planning to Predict Landholder Management Uptake

Understanding the social dimensions of conservation opportunity is crucial for conservation planning in multiple‐use landscapes. However, factors that influence the feasibility of implementing conservation actions, such as the history of landscape management, and landholders’ willingness to engage are often difficult or time consuming to quantify and rarely incorporated into planning. We examined how conservation agencies could reduce costs of acquiring such data by developing predictive models of management feasibility parameterized with social and biophysical factors likely to influence landholders’ decisions to engage in management. To test the utility of our best‐supported model, we developed 4 alternative investment scenarios based on different input data for conservation planning: social data only; biological data only; potential conservation opportunity derived from modeled feasibility that incurs no social data collection costs; and existing conservation opportunity derived from feasibility data that incurred collection costs. Using spatially explicit information on biodiversity values, feasibility, and management costs, we prioritized locations in southwest Australia to control an invasive predator that is detrimental to both agriculture and natural ecosystems: the red fox (Vulpes vulpes). When social data collection costs were moderate to high, the most cost‐effective investment scenario resulted from a predictive model of feasibility. Combining empirical feasibility data with biological data was more cost‐effective for prioritizing management when social data collection costs were low (<4% of the total budget). Calls for more data to inform conservation planning should take into account the costs and benefits of collecting and using social data to ensure that limited funding for conservation is spent in the most cost‐efficient and effective manner.     

Incorporating geodiversity into conservation decisions

In a rapidly changing climate, conservation practitioners could better use geodiversity in a broad range of conservation decisions. We explored selected avenues through which this integration might improve decision making and organized them within the adaptive management cycle of assessment, planning, implementation, and monitoring. Geodiversity is seldom referenced in predominant environmental law and policy. With most natural resource agencies mandated to conserve certain categories of species, agency personnel are challenged to find ways to practically implement new directives aimed at coping with climate change while retaining their species‐centered mandate. Ecoregions and ecological classifications provide clear mechanisms to consider geodiversity in plans or decisions, the inclusion of which will help foster the resilience of conservation to climate change. Methods for biodiversity assessment, such as gap analysis, climate change vulnerability analysis, and ecological process modeling, can readily accommodate inclusion of a geophysical component. We adapted others’ approaches for characterizing landscapes along a continuum of climate change vulnerability for the biota they support from resistant, to resilient, to susceptible, and to sensitive and then summarized options for integrating geodiversity into planning in each landscape type. In landscapes that are relatively resistant to climate change, options exist to fully represent geodiversity while ensuring that dynamic ecological processes can change over time. In more susceptible landscapes, strategies aiming to maintain or restore ecosystem resilience and connectivity are paramount. Implementing actions on the ground requires understanding of geophysical constraints on species and an increasingly nimble approach to establishing management and restoration goals. Because decisions that are implemented today will be revisited and amended into the future, increasingly sophisticated forms of monitoring and adaptation will be required to ensure that conservation efforts fully consider the value of geodiversity for supporting biodiversity in the face of a changing climate.     

Managing the Koala Problem: Interdisciplinary Perspectives

Abstract: There is a complex scientific, ethical, and cultural debate in Australia about how best to conserve koalas and their habitat. Despite the diverse array of management and research options promoted by scientists, wildlife agency staff, and koala advocates, there remains a gap in our acknowledgment of the social factors influencing decision making about koala conservation. Koala management research has generated valuable scientific knowledge about koala biology and ecology but has been weak about organizational and policy processes and about the cultures within which we produce, disseminate, and legitimize this kind of knowledge. We suggest that more effective koala conservation will result from making the political and cultural influences on decision making regarding the koala more explicit in research, management, and policy-making forums. Research must be conducted in the context of the cultural significance of the koala. The koala's survival depends on preserving the valuable lands that these creatures (and many others) inhabit. Ultimately, the koala symbolizes conflicting land-use values and illustrates the need for greater collaboration, cooperation, and trust among social and natural scientists in the conduct of koala conservation research, management, and policy.     

Appreciating Ecological Complexity: Habitat Contours as a Conceptual Landscape Model

Abstract:  Organisms respond to their surroundings at multiple spatial scales, and different organisms respond differently to the same environment. Existing landscape models, such as the "fragmentation model" (or patch-matrix-corridor model) and the "variegation model," can be limited in their ability to explain complex patterns for different species and across multiple scales. An alternative approach is to conceptualize landscapes as overlaid species-specific habitat contour maps. Key characteristics of this approach are that different species may respond differently to the same environmental conditions and at different spatial scales. Although similar approaches are being used in ecological modeling, there is much room for habitat contours as a useful conceptual tool. By providing an alternative view of landscapes, a contour model may stimulate more field investigations stratified on the basis of ecological variables other than human-defined patches and patch boundaries. A conceptual model of habitat contours may also help to communicate ecological complexity to land managers. Finally, by incorporating additional ecological complexity, a conceptual model based on habitat contours may help to bridge the perceived gap between pattern and process in landscape ecology. Habitat contours do not preclude the use of existing landscape models and should be seen as a complementary approach most suited to heterogeneous human-modified landscapes.     

Modeling Opportunity Costs of Conservation in Transitional Landscapes

Abstract:  Conservation scientists recognize the urgency of incorporating opportunity costs into conservation planning. Despite this, applications to date have been limited, perhaps partly because of the difficulty in determining costs in regions with limited data on land prices and ownership. We present methods for estimating opportunity costs of land preservation in landscapes or ecoregions that are a changing mix of agriculture and natural habitat. Our approach derives from the literature on estimating land values as opportunity costs of alternate land uses and takes advantage of general availability of necessary data, even in relatively data-poor regions. The methods integrate probabilities of habitat conversion with region-wide estimates of economic benefits from agricultural land uses and estimate land values with a discount rate to convert annual values into net present values. We applied our method in a landscape undergoing agricultural conversion in Paraguay. Our model of opportunity costs predicted an independent data set of land values and was consistent with implicit discount rates of 15–25%. Model-generated land values were strongly correlated with actual land values even after correcting for the effect of property size and proportion of property that was forested. We used the model to produce a map of opportunity costs and to estimate the costs of conserving forest within two proposed corridors in the landscape. This method can be applied to conservation planning in situations where natural habitat is currently being converted to market-oriented land uses. Incorporating not only biological attributes but also socioeconomic data can help in the design of efficient networks of protected areas that represent biodiversity at minimum costs.     

Emergent conservation outcomes of shared risk perception in human-wildlife systems

Human perception of risks related to economic damages caused by nearby wildlife can be transmitted through social networks. Understanding how sharing risk information within a human community alters the spatial dynamics of human-wildlife interactions has important implications for the design and implementation of effective conservation actions. We developed an agent-based model that simulates farmer livelihood decisions and activities in an agricultural landscape shared with a population of a generic wildlife species (wildlife-human interactions in shared landscapes [WHISL]). In the model, based on risk perception and economic information, farmers decide how much labor to allocate to farming and whether and where to exclude wildlife from their farms (e.g., through fencing, trenches, or vegetation thinning). In scenarios where the risk perception of farmers was strongly influenced by other farmers, exclusion of wildlife was widespread, resulting in decreased quality of wildlife habitat and frequency of wildlife damages across the landscape. When economic losses from encounters with wildlife were high, perception of risk increased and led to highly synchronous behaviors by farmers in space and time. Interactions between wildlife and farmers sometimes led to a spillover effect of wildlife damage displaced from socially and spatially connected communities to less connected neighboring farms. The WHISL model is a useful conservation-planning tool because it provides a test bed for theories and predictions about human-wildlife dynamics across a range of different agricultural landscapes.     

Improving effectiveness of systematic conservation planning with density data

Systematic conservation planning aims to design networks of protected areas that meet conservation goals across large landscapes. The optimal design of these conservation networks is most frequently based on the modeled habitat suitability or probability of occurrence of species, despite evidence that model predictions may not be highly correlated with species density. We hypothesized that conservation networks designed using species density distributions more efficiently conserve populations of all species considered than networks designed using probability of occurrence models. To test this hypothesis, we used the Zonation conservation prioritization algorithm to evaluate conservation network designs based on probability of occurrence versus density models for 26 land bird species in the U.S. Pacific Northwest. We assessed the efficacy of each conservation network based on predicted species densities and predicted species diversity. High‐density model Zonation rankings protected more individuals per species when networks protected the highest priority 10‐40% of the landscape. Compared with density‐based models, the occurrence‐based models protected more individuals in the lowest 50% priority areas of the landscape. The 2 approaches conserved species diversity in similar ways: predicted diversity was higher in higher priority locations in both conservation networks. We conclude that both density and probability of occurrence models can be useful for setting conservation priorities but that density‐based models are best suited for identifying the highest priority areas. Developing methods to aggregate species count data from unrelated monitoring efforts and making these data widely available through ecoinformatics portals such as the Avian Knowledge Network will enable species count data to be more widely incorporated into systematic conservation planning efforts.     

Thresholds in Songbird Occurrence in Relation to Landscape Structure

Abstract:  Theory predicts the occurrence of threshold levels of habitat in landscapes, below which ecological processes change abruptly. Simulation models indicate that below critical thresholds, fragmentation of habitat influences patch occupancy by decreasing colonization rates and increasing rates of local extinction. Uncovering such putative relationships is important for understanding the demography of species and in developing sound conservation strategies. Using segmented logistic regression, we tested for thresholds in occurrence of 15 bird species as a function of the amount of suitable habitat at multiple scales (150–2000-m radii). Suitable habitat was defined quantitatively based on previously derived, spatially explicit distribution models for each species. The occurrence of 10 out of 15 species was influenced by the amount of habitat at a landscape scale (≥500-m radius). Of these species all but one were best predicted by threshold models. Six out of nine species exhibited asymptotic thresholds; the effects of habitat loss intensified at low amounts of habitat in a landscape. Landscape thresholds ranged from 8.6% habitat to 28.7% (     = 18.5 ± 2.6%[95% CI]). For two species landscape thresholds coincided with sensitivity to fragmentation; both species were more likely to occur in large patches, but only when the amount of habitat in a landscape was low. This supports the fragmentation threshold hypothesis. Nevertheless, the occurrence of most species appeared to be unaffected by fragmentation, regardless of the amount of habitat present at landscape extents. The thresholds we identified may be useful to managers in establishing conservation targets. Our results indicate that findings of landscape-scale studies conducted in regions with relatively high proportions of habitat and low fragmentation may not be applicable in regions with low habitat proportions and high fragmentation.     

Graph theory as a proxy for spatially explicit population models in conservation planning.

Spatially explicit population models (SEPMs) are often considered the best way to predict and manage species distributions in spatially heterogeneous landscapes. However, they are computationally intensive and require extensive knowledge of species' biology and behavior, limiting their application in many cases. An alternative to SEPMs is graph theory, which has minimal data requirements and efficient algorithms. Although only recently introduced to landscape ecology, graph theory is well suited to ecological applications concerned with connectivity or movement. This paper compares the performance of graph theory to a SEPM in selecting important habitat patches for Wood Thrush (Hylocichla mustelina) conservation. We use both models to identify habitat patches that act as population sources and persistent patches and also use graph theory to identify patches that act as stepping stones for dispersal. Correlations of patch rankings were very high between the two models. In addition, graph theory offers the ability to identify patches that are very important to habitat connectivity and thus long-term population persistence across the landscape. We show that graph theory makes very similar predictions in most cases and in other cases offers insight not available from the SEPM, and we conclude that graph theory is a suitable and possibly preferable alternative to SEPMs for species conservation in heterogeneous landscapes.     

Conservation Planning in Forest Landscapes of Fennoscandia and an Approach to the Challenge of Countdown 2010

Abstract:  Effective management of biodiversity in production landscapes requires a conservation approach that acknowledges the complexity of ecological and cultural systems in time and space. Fennoscandia has experienced major loss of forest biodiversity caused by intensive forestry. Therefore, the Countdown 2010 initiative to halt the loss of biodiversity in Europe is highly relevant to forest management in this part of the continent. As a contribution to meeting the challenge posed by Countdown 2010, we developed a spatially explicit conservation-planning exercise that used regional knowledge on forest biodiversity to provide support for managers attempting to halt further loss of biological diversity in the region. We used current data on the distribution of 169 species (including 68 red-listed species) representing different forest habitats and ecologies along with forest data within the frame of modern conservation software to devise a map of priority areas for conservation. The top 10% of priority areas contained over 75% of red-listed species locations and 41% of existing protected forest areas, but only 58% of these top priorities overlapped with core areas identified previously in a regional strategy that used more qualitative methods. We argue for aggregating present and future habitat value of single management units to landscape and regional scales to identify potential bottlenecks in habitat availability linked to landscape dynamics. To address the challenge of Countdown 2010, a general framework for forest conservation planning in Fennoscandia needs to cover different conservation issues, tools, and data needs.     

Independent effects of fragmentation on forest songbirds: an organism-based approach.

The degree to which spatial patterns influence the dynamics and distribution of populations is a central question in ecology. This question is even more pressing in the context of rapid habitat loss and fragmentation, which threaten global biodiversity. However, the relative influence of habitat loss and landscape fragmentation, the spatial patterning of remaining habitat, remains unclear. If landscape pattern affects population size, managers may be able to design landscapes that mitigate habitat loss. We present the results of a mensurative experiment designed to test four habitat loss vs. fragmentation hypotheses. Unlike previous studies, we measured landscape structure using quantitative, spatially explicit habitat distribution models previously developed for two species: Blackburnian Warbler (Dendroica fusca) and Ovenbird (Seiurus aurocapilla). We used a stratified sampling design that reduced the confounding of habitat amount and fragmentation variables. Occurrence and reoccurrence of both species were strongly influenced by characteristics at scales greater than the individual territory, indicating little support for the random-sample hypothesis. However, the type and spatial extent of landscape influence differed. Both occurrence and reoccurrence of Blackburnian Warblers were influenced by the amount of poor-quality matrix at 300- and 2000-m spatial extents. The occurrence and reoccurrence of Ovenbirds depended on a landscape pattern variable, patch size, but only in cases when patches were isolated. These results support the hypothesis that landscape pattern is important for some species only when the amount of suitable habitat is low. Although theoretical models have predicted such an interaction between landscape fragmentation and composition, to our knowledge this is the first study to report empirical evidence of such nonlinear fragmentation effects. Defining landscapes quantitatively from an organism-based perspective may increase power to detect fragmentation effects, particularly in forest mosaics where boundaries between patches and matrix are ambiguous. Our results indicate that manipulating landscape pattern may reduce negative impacts of habitat loss for Ovenbird, but not Blackburnian Warbler. We emphasize that most variance in the occurrence of both species was explained by local scale or landscape composition variables rather than variables reflecting landscape pattern.     

Incorporating Habitat Mapping into Practical Koala Conservation on Private Lands

Abstract: Identifying and conserving faunal habitat on private lands has been conducted largely on a site-by-site basis as development proposals arise. We sought to map koala habitat at a scale suitable for use by a local planning authority so that habitat remnants could be protected and managed while remaining in private ownership. At this scale, the level of detail and accuracy needed by local planners required a new approach to mapping koala habitat. Two independent techniques, community and field surveys, were employed. We mailed a survey to every household in Coffs Harbour shire. Respondents told of 3309 koala sightings. We conducted a field survey, a plot-based scat (  fecal pellet) search, to determine which vegetation types and tree species were preferred by koalas. We surveyed 119 sites, which contained 42 different vegetation types. Of these, 37 (31%) had been used by koalas. The outcomes of the community and field surveys were combined to produce a distribution map of koala habitat. The most striking outcome has been the use of our results by the local government authority, Coffs Harbour City Council: planners have incorporated the koala habitat map into their local environmental plan. Our procedure offers a rigorous, repeatable, and publicly accessible method for identifying and mapping important habitat for the purposes of land-use planning, an essential procedure for conserving habitat outside the reserve system.     

An agent-based model of red colobus resources and disease dynamics implicates key resource sites as hot spots of disease transmission

The effect of anthropogenic landscape change on disease in wildlife populations represents a growing conservation and public health concern. Red colobus monkeys (Procolobus rufomitratus), an endangered primate species, are particularly susceptible to habitat alteration and have been the focus of a great deal of disease and ecological research as a result. To infer how landscape changes can affect host and parasite dynamics, a spatially explicit agent-based model is created to simulate movement and foraging of this primate, based on a resource landscape estimated from extensive plot-derived tree population data from Kibale National Park, Uganda. Changes to this resource landscape are used to simulate effects of anthropogenic forest change. With each change in the landscape, disease outcomes within the simulated red colobus population are monitored using a hypothetical microparasite with a directly transmitted life cycle. The model predicts an optimal distribution of resources which facilitates the spread of an infectious agent through the simulated population. The density of resource rich sites and the overall heterogeneity of the landscape are important factors contributing to this spread. The characteristics of this optimal distribution are similar to those of logged sections of forest adjacent to our study area.     

Effect of Human Disturbance on Bee Communities in a Forested Ecosystem

Abstract:  It is important for conservation biologists to understand how well species persist in human-dominated ecosystems because protected areas constitute a small fraction of the Earth's surface and because anthropogenic habitats may offer more opportunities for conservation than has been previously thought. We investigated how an important functional group, pollinators (bees; Hymenoptera: Apiformes), are affected by human land use at the landscape and local scales in southern New Jersey (U.S.A.). We established 40 sites that differed in surrounding landscape cover or local habitat type and collected 2551 bees of 130 species. The natural habitat in this ecosystem is a forested, ericaceous heath. Bee abundance and species richness within forest habitat decreased, not increased, with increasing forest cover in the surrounding landscape. Similarly, bee abundance was greater in agricultural fields and suburban and urban developments than in extensive forests, and the same trend was found for species richness. Particular species groups that might be expected to show greater sensitivity to habitat loss, such as floral specialists and bees of small or large body size, did not show strong positive associations with forest habitat. Nevertheless, 18 of the 130 bee species studied were positively associated with extensive forest. One of these species is a narrow endemic that was last seen in 1939. Our results suggest that at least in this system, moderate anthropogenic land use may be compatible with the conservation of many, but not all, bee species.     

Interactive effects of natural and human disturbances on vegetation dynamics across landscapes.

Accurate measures of human effects on landscape processes require consideration of both the direct impacts from human activities and the indirect consequences of the interactions between humans and the landscape. This is particularly evident in systems experiencing regular natural disturbances such as in the mountainous areas of southwestern China, where the remaining population of giant pandas (Ailuropoda melanoleuca) is supported. Here the spatiotemporal patterns of human impacts, forests, and bamboo episodic die-offs combine to determine the distribution of panda habitat. To study the complex interactions of humans and landscapes, we developed an integrated spatiotemporally explicit model of household activities, natural vegetation dynamics, and their impacts on panda habitat. Using this model we examined the direct consequences of local fuelwood collection and household creation on areas of critical giant panda habitat and the indirect impacts when coupled with vegetation dynamics. Through simulations, we found that over the next 30 years household impacts would result in the loss of up to 30% of the habitat relied on by pandas during past bamboo die-offs. The accumulation and spatial distribution of household impacts would also have a considerable indirect influence on the spatial distribution of understory bamboo. While human impacts influence both bamboo die-off and regeneration, over 19% of pre-existing low-elevation bamboo habitat may be lost following an episodic die-off depending on the severity of the impacts and timing of the die-offs. Our study showed not only the importance of the spatial distribution of direct household impacts on habitat, but also the far-reaching effects of the indirect interactions between humans and the landscapes they are modifying.     

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.