The impact of the landscape matrix on patterns of animal movement and population dynamics has been widely recognized by ecologists. However, few tools are available to model the matrix's influence on the length, relative quality, and redundancy of dispersal routes connecting habitat patches. Many GIS software packages can use land use/land cover maps to identify the route of least resistance between two points-the least-cost path. The limitation of this type of analysis is that only a single path is identified, even though alternative paths with comparable costs might exist. In this paper, we implemented two graph theory methods that extend the least-cost path approach: the Conditional Minimum Transit Cost (CMTC) tool and the Multiple Shortest Paths (MSPs) tool. Both methods enable the visualization of multiple dispersal routes that, together, are assumed to form a corridor. We show that corridors containing alternative dispersal routes emerge when favorable habitat is randomly distributed in space. As clusters of favorable habitat start forming, corridors become less redundant and dispersal bottlenecks become visible. Our approach is illustrated using data from a real landscape in the Brazilian Atlantic forest. We explored the effect of small, localized disturbance on dispersal routes linking conservation units. Simulated habitat destruction caused the appearance of alternative dispersal routes, or caused existing corridors to become narrower. These changes were observed even in the absence of significant differences in the length or cost of least-cost paths. Last, we discuss applications to animal movement studies and conservation initiatives.
Despite vast evidence of species turnover displayed by Neotropical bat communities in response to forest fragmentation, the exact shape of the relationship between fragment area and abundance for individual bat species is still unclear. Bats' ample variation in diet, morphology, and movement behaviour can potentially influence species' perception of the landscape. Thus, studies describing fragment area at a single spatial scale may fail to capture the amount of forest available from the perspective of individual bat species. In the present paper, we study the influence of forest cover on bats inhabiting a fragmented forest in Mexico, focusing on some of the most common frugivore species: Artibeus jamaicensis, Carollia spp. (C. brevicauda/C. perspicillata) and Sturnira spp. (S. lilium/S. ludovici). We quantified forest cover at scales ranging from 50 to 2000 m, and measured the influence of forest cover on bat capture success, a surrogate for abundance. The three species displayed positive and significant scale-dependent associations with forest cover. Abundance of A. jamaicensis increased with forest cover measured at scales ranging between 500 and 2000 m, while Carollia spp. responded more strongly to variation in forest cover measured at scales 100-500 m. For Sturnira spp., abundance was a function of presence of creeks near mist-netting sites, and amount of secondary forest present at a 200 m scale. The observed variation in responses to forest cover can be explained in light of interspecific differences in diet, home range, and body size. Our results illustrate a method for measuring the effect of forest fragmentation on mobile species and suggest that changes in abundance in fragmented landscapes emerge from the interaction between species' traits and landscape structure.
There is an increasing recognition that individual-level spatial and temporal heterogeneity may play an important role in metapopulation dynamics and persistence. In particular, the patterns of contact within and between aggregates (e.g., demes) at different spatial and temporal scales may reveal important mechanisms governing metapopulation dynamics. Using 7 years of data on the interaction between the anther smut fungus (Microbotryum violaceum) and fire pink (Silene virginica), we show how the application of spatially explicit and implicit network models can be used to make accurate predictions of infection dynamics in spatially structured populations. Explicit consideration of both spatial and temporal organization reveals the role of each in spreading risk for both the host and the pathogen. This work suggests that the application of spatially explicit network models can yield important insights into how heterogeneous structure can promote the persistence of species in natural landscapes.
The temporal stability of aggregate community and ecosystem properties is influenced by the variability of component populations, the interactions among populations, and the influence of environmental fluctuations on populations. Environmental fluctuations that enhance population variability are generally expected to destabilize community and ecosystem properties, but this will depend on the degree to which populations are synchronized in their dynamics. Here we use seminatural experimental ponds to show that reduced synchrony among zooplankton taxa increases the temporal stability of zooplankton density, abundance, and ecosystem productivity influctuating environments. However, asynchrony only occurs at long timescales (similar to 80-day periods) and under recurring environmental perturbations. At shorter timescales (similar to 10-day periods) and in constant environments, synchronous dynamics dominate. Our findings support recent theory indicating that compensatory dynamics can stabilize communities and ecosystems. They further indicate that environmental fluctuations can enhance the likelihood of long-period asynchrony and thus stabilize community and ecosystem properties despite their short term destabilizing effects.
Aggregate community-level response to disturbance is a principle concern in ecology because post-disturbance dynamics are integral to the ability of ecosystems to maintain function in an uncertain world. Community-level responses to disturbance can be arrayed along a spectrum ranging from synchronous oscillations where all species rise and fall together, to compensatory dynamics where total biomass remains relatively constant despite fluctuations in the densities of individual species. An important recent insight is that patterns of synchrony and compensation can vary with the timescale of analysis and that spectral time series methods can enable detection of coherent dynamics that would otherwise be obscured by opposing patterns occurring at different scales. Here I show that application of wavelet analysis to experimentally manipulated plankton communities reveals strong synchrony after disturbance. The result is paradoxical because it is well established that these communities contain both disturbance-sensitive and disturbance-tolerant species leading to compensation within functional groups. Theory predicts that compensatory substitution of functionally equivalent species should stabilize ecological communities, yet I found at the whole-community level a large increase in seasonal biomass variation. Resolution of the paradox hinges on patterns of seasonality among species. The compensatory shift in community composition after disturbance resulted in a loss of cold-season dominants, which before disturbance had served to stabilize biomass throughout the year. Species dominating the disturbed community peaked coherently during the warm season, explaining the observed synchrony and increase in seasonal biomass variation. These results suggest that theory relating compensatory dynamics to ecological stability needs to consider not only complementarity in species responses to environmental change, but also seasonal complementarity among disturbance-tolerant and disturbance-sensitive species.
Many ecosystem services are delivered by organisms that depend on habitats that are segregated spatially or temporally from the location where services are provided. Management of mobile organisms contributing to ecosystem services requires consideration not only of the local scale where services are delivered, but also the distribution of resources at the landscape scale, and the foraging ranges and dispersal movements of the mobile agents. We develop a conceptual model for exploring how one such mobile-agent-based ecosystem service (MABES), pollination, is affected by land-use change, and then generalize the model to other MABES. The model includes interactions and feedbacks among policies affecting land use, market forces and the biology of the organisms involved. Animal-mediated pollination contributes to the production of goods of value to humans such as crops; it also bolsters reproduction of wild plants on which other services or service-providing organisms depend. About one-third of crop production depends on animal pollinators, while 60-90% of plant species require an animal pollinator. The sensitivity of mobile organisms to ecological factors that operate across spatial scales makes the services provided by a given community of mobile agents highly contextual. Services vary, depending on the spatial and temporal distribution of resources surrounding the site, and on biotic interactions occurring locally, such as competition among pollinators for resources, and among plants for pollinators. The value of the resulting goods or services may feed back via market-based forces to influence land-use policies, which in turn influence land management practices that alter local habitat conditions and landscape structure. Developing conceptual models for MABES aids in identifying knowledge gaps, determining research priorities, and targeting interventions that can be applied in an adaptive management context.
Biologists seek an understanding of the processes underlying spatial biodiversity patterns. Neutral theory links those patterns to dispersal, speciation and community drift. Here, we advance the spatially explicit neutral model by representing the metacommunity as a network of smaller communities. Analytic theory is presented for a set of equilibrium diversity patterns in networks of communities, facilitating the exploration of parameter space not accessible by simulation. We use this theory to evaluate how the basic properties of a metacommunity - connectivity, size, and speciation rate - determine overall metacommunity gamma-diversity, and how that is partitioned into alpha- and beta-components. We find spatial structure can increase gamma-diversity relative to a well-mixed model, even when theta is held constant. The magnitude of deviations from the well-mixed model and the partitioning into alpha- and beta-diversity is related to the ratio of migration and speciation rates. gamma-diversity scales linearly with metacommunity size even as alpha- and beta-diversity scale nonlinearly with size.
The response of ecological communities to anthropogenic disturbance is of both scientific and practical interest. Communities where all species respond to disturbance in a similar fashion (synchrony) will exhibit large fluctuations in total biomass and dramatic changes in ecosystem function. Communities where some species increase in abundance while others decrease after disturbance (compensation) can maintain total biomass and ecosystem function in the face of anthropogenic change. We examined dynamics of the Little Rock Lake (Wisconsin, USA) zooplankton community in the context of an experimental pH manipulation conducted in one basin of the lake. A novel application of wavelets was used to partition patterns of synchrony and compensation by time scale. We find interestingly that some time series show both patterns of synchrony and compensation depending on the scale of analysis. Within the unmanipulated basin, we found subtle patterns of synchrony and compensation within the community, largely at a one-year time scale corresponding to seasonal variation. Within the acidified lake basin, dynamics shifted to longer time scales corresponding to the pattern of pH manipulation. Comparisons between pairs of species in different functional groups showed both strong compensatory and synchronous responses to disturbance. The strongest compensatory signal was observed for two species of Daphnia whose life history traits lead to synchrony at annual time scales, but whose differential sensitivity to acidification led to compensation at multiannual time scales. The separation of time scales inherent in the wavelet method greatly facilitated interpretation as patterns resulting from seasonal drivers could be separated from patterns driven by pH manipulation.
Species distributional limits may coincide with hard dispersal barriers or physiological thresholds along environmental gradients, but they may also be influenced by species interactions. We explore a number of models of interspecific interactions that lead to (sometimes abrupt) distribution limits in the presence and absence of environmental gradients. We find that gradients in competitive ability can lead to spatial segregation of competitors into distinct ranges, but that spatial movement tends to broaden the region of sympatry between the two species, and that Allee effects tend to sharpen these boundaries. We generalize these simple models to include metapopulation dynamics and other types of interactions including predator-prey and host-parasite interactions. We derive conditions for range limits in each case. We also consider models that include coevolution and gene flow and find that character displacement along environmental gradients can lead to stable parapatric distributions. We conclude that it is essential to consider coevolved species interactions as a potential mechanism limiting species distributions, particularly when barriers to dispersal are weak and environmental gradients are gradual.
Biologists have long been fascinated by species' borders, and with good reason. Understanding the ecological and evolutionary dynamics of species' borders may prove to be the key that unlocks new understanding across a wide range of biological phenomena. After all, geographic range limits are a point of entry into understanding the ecological niche and threshold responses to environmental change. Elucidating patterns of gene flow to, and returning from, peripheral populations can provide important insights into the nature of adaptation, speciation and coevolution. Species' borders form natural laboratories for the study of the spatial structure of species interactions. Comparative studies from the center to the margin of species' ranges allow us to explore species' demographic responses along gradients of increasing environmental stress. Range dynamics further permit investigation into invasion dynamics and represent bellwethers for a changing climate. This set of papers explores ecological and evolutionary dynamics of species' borders from diverse empirical and theoretical perspectives.
With the increasing concern about species conservation, a need exists for quantitaive characterization of species' geographic range and their borders. In this paper, we survey tools appropriate for the quantification of static spatial patterns related to geographical ranges and their borders. We then build on these static methods to consider the problem of changes in geographic range through time. Methods discussed are illustrated using lark sparrow data from the North American Breeding Bird Survey. While there is no such thing as the ``best\''\ or ``only\''\ method to analyze species geographical range and border, we show that a series of methods can be used in sequence to provide complementary and useful quantitative information for species occupancy of range. Indeed, the location of species' borders estimated at different times can be compared to identify locations where species expand or go locally extinct. The ability to delineate accurately species' ranges will be useful to conservation biologists, managers and ecologists.
Statistical models of environment-abundance relationships may be influenced by spatial autocorrelation in abundance, environmental variables, or both, Failure to account for spatial autocorrelation can lead to incorrect conclusions regarding both the absolute and relative importance of environmental variables as determinants of abundance. We consider several classes of statistical models that are appropriate for modeling environment-abundance relationships in the presence of spatial autocorrelation, and apply these to three case studies: 1) abundance of voles in relation to habitat characteristics; 2) a plant competition experiment; and 3) abundance of Orbatid mites along environmental gradients. We find that when spatial pattern is accounted for in the modeling process, conclusions about environmental control over abundance can change dramatically. We conclude with five lessons: 1) spatial models are easy to calculate with several of the most common statistical packages; 2) results from spatially-structured models may point to conclusions radically different from those suggested by a spatially independent model; 3) not all spatial autocorrelation in abundances results from spatial population dynamics; it may also result from abundance associations with environmental variables not included in the model; 4) the different spatial models do have different mechanistic interpretations in terms of ecological processes - thus ecological model selection should take primacy over statistical model selection; 5) the conclusions of the different spatial models are typically fairly similar - making any correction is more important than quibbling about which correction to make.