A novel statistical method for classifying habitat generalists and specialists

We develop a novel statistical approach for classifying generalists and specialists in two distinct habitats. Using a multinomial model based on estimated species relative abundance in two habitats, our method minimizes bias due to differences in sampling intensities between two habitat types as well as bias due to insufficient sampling within each habitat. The method permits a robust statistical classification of habitat specialists and generalists, without excluding rare species a priori. Based on a user-defined specialization threshold, the model classifies species into one of four groups: (1) generalist; (2) habitat A specialist; (3) habitat B specialist; and (4) too rare to classify with confidence. We illustrate our multinomial classification method using two contrasting data sets: (1) bird abundance in woodland and heath habitats in southeastern Australia and (2) tree abundance in second-growth (SG) and old-growth (OG) rain forests in the Caribbean lowlands of northeastern Costa Rica. We evaluate the multinomial model in detail for the tree data set. Our results for birds were highly concordant with a previous nonstatistical classification, but our method classified a higher fraction (57.7%) of bird species with statistical confidence. Based on a conservative specialization threshold and adjustment for multiple comparisons, 64.4% of tree species in the full sample were too rare to classify with confidence. Among the species classified, OG specialists constituted the largest class (40.6%), followed by generalist tree species (36.7%) and SG specialists (22.7%). The multinomial model was more sensitive than indicator value analysis or abundance-based phi coefficient indices in detecting habitat specialists and also detects generalists statistically. Classification of specialists and generalists based on rarefied subsamples was highly consistent with classification based on the full sample, even for sampling percentages as low as 20%. Major advantages of the new method are (1) its ability to distinguish habitat generalists (species with no significant habitat affinity) from species that are simply too rare to classify and (2) applicability to a single representative sample or a single pooled set of representative samples from each of two habitat types. The method as currently developed can be applied to no more than two habitats at a time.     

Disentangling the drivers of reduced long-distance seed dispersal by birds in an experimentally fragmented landscape

Seed dispersal is a crucial component of plant population dynamics. Human landscape modifications, such as habitat destruction and fragmentation, can alter the abundance of fruiting plants and animal dispersers, foraging rates, vector movement, and the composition of the disperser community, all of which can singly or in concert affect seed dispersal. Here, we quantify and tease apart the effects of landscape configuration, namely, fragmentation of primary forest and the composition of the surrounding forest matrix, on individual components of seed dispersal of Heliconia acuminata, an Amazonian understory herb. First we identified the effects of landscape configuration on the abundance of fruiting plants and six bird disperser species. Although highly variable in space and time, densities of fruiting plants were similar in continuous forest and fragments. However, the two largest-bodied avian dispersers were less common or absent in small fragments. Second, we determined whether fragmentation affected foraging rates. Fruit removal rates were similar and very high across the landscape, suggesting that Heliconia fruits are a key resource for small frugivores in this landscape. Third, we used radiotelemetry and statistical models to quantify how landscape configuration influences vector movement patterns. Bird dispersers flew farther and faster, and perched longer in primary relative to secondary forests. One species also altered its movement direction in response to habitat boundaries between primary and secondary forests. Finally, we parameterized a simulation model linking data on fruit density and disperser abundance and behavior with empirical estimates of seed retention times to generate seed dispersal patterns in two hypothetical landscapes. Despite clear changes in bird movement in response to landscape configuration, our simulations demonstrate that these differences had negligible effects on dispersal distances. However, small fragments had reduced densities of Turdus albicollis, the largest-bodied disperser and the only one to both regurgitate and defecate seeds. This change in Turdus abundance acted together with lower numbers of fruiting plants in small fragments to decrease the probability of long-distance dispersal events from small patches. These findings emphasize the importance of foraging style for seed dispersal and highlight the primacy of habitat size relative to spatial configuration in preserving biotic interactions.     

Connectivity in an Agricultural Landscape as Reflected by Interpond Movements of a Freshwater Turtle

Abstract:  Connectivity is a measure of how landscape features facilitate movement and thus is an important factor in species persistence in a fragmented landscape. The scarcity of empirical studies that directly quantify species movement and determine subsequent effects on population density have, however, limited the utility of connectivity measures in conservation planning. We undertook a 4-year study to calculate connectivity based on observed movement rates and movement probabilities for five age-sex classes of painted turtles ( Chrysemys picta ) inhabiting a pond complex in an agricultural landscape in northern Virginia (U.S.A.). We determined which variables influenced connectivity and the relationship between connectivity and subpopulation density. Interpatch distance and quality of habitat patches influenced connectivity but characteristics of the intervening matrix did not. Adult female turtles were more influenced by the habitat quality of recipient ponds than other age-sex classes. The importance of connectivity on spatial population dynamics was most apparent during a drought. Population density and connectivity were low for one pond in a wet year but dramatically increased as other ponds dried. Connectivity is an important component of species persistence in a heterogeneous landscape and is strongly dependent on the movement behavior of the species. Connectivity may reflect active selection or avoidance of particular habitat patches. The influence of habitat quality on connectivity has often been ignored, but our findings highlight its importance. Conservation planners seeking to incorporate connectivity measures into reserve design should not ignore behavior in favor of purely structural estimates of connectivity.     

Evaluating the effect of corridors and landscape heterogeneity on dispersal probability: a comparison of three spatially explicit modelling approaches

Spatially explicit simulation models of varying degree of complexity are increasingly used in landscape and species management and conservation. The choice as to which type of model to employ in a particular situation, is however, far too often governed by logistic constraints and the personal preferences of the modeller, rather than by a critical evaluation of model performance. We present a comparison of three common spatial simulation approaches (patch-based incidence-function model (IFM), individual-based movement model (IBMM), individual-based population model including detailed behaviour and demographics (IBPM)). The IBPM was analysed in two versions (IBPM_st and IBPM_dyn). Both assumed spatial heterogeneity of the matrix, but the IBPM_dyn in addition included temporal matrix dynamics. The models were developed with a shared minimum objective, namely to predict dynamics of individuals or populations in space given a specific configuration of habitat patches. We evaluated how the choice of model influenced predictions regarding the effect of patch and corridor configuration on dispersal probabilities and the number of successful immigrants of a simulated small mammal. Model results were analysed both at the level of the entire habitat network and at the level of individual patches.All models produced similar rankings of alternative habitat networks, but large discrepancies existed between absolute estimates of dispersal probabilities and the number of successful immigrants predicted by the different models. Generally, predicted dispersal probabilities were highest in the IBMM, intermediate in the IFM and the IBPM_st and lowest in the IBPM_dyn. Observed differences were due both to differences in implementation (e.g. raster versus vector-based movement algorithms), the chosen level of detail in landscape representation (e.g. matrix complexity) and the degree of behavioural realism included in the models (e.g. demography, differentiated mortality).The advantages and disadvantages of the three modelling approaches are discussed, as are the implications of the results for the recommended use of the three types of models in practical management.     

Pattern-oriented modeling of bird foraging and pest control in coffee farms

We develop a model of how land use and habitat diversity affect migratory bird populations and their ability to suppress an insect pest on Jamaican coffee farms. Bird foraging—choosing which habitat patch and prey to use as prey abundance changes over space and time—is the key process driving this system. Following the “pattern-oriented” modeling strategy, we identified nine observed patterns that characterize the real system's dynamics. The model was designed so that these patterns could potentially emerge from it. The resulting model is individual-based, has fine spatial and temporal resolutions, represents very simply the supply of the pest insect and other arthropod food in six habitat types, and includes foraging habitat selection as the only adaptive behavior of birds. Although there is an extensive heritage of bird foraging theory in ecology, most of it addresses only the individual level and is too simple for our context. We used pattern-oriented modeling to develop and test foraging theory for this across-scale problem: rules for individual bird foraging that cause the model to reproduce a variety of patterns observed at the system level. Four alternative foraging theories were contrasted by how well they caused the model to reproduce the nine characteristic patterns. Four of these patterns were clearly reproduced with the “null” theory that birds select habitat randomly. A version of classical theory in which birds stay in a patch until food is depleted to some threshold caused the model to reproduce five patterns; this theory caused lower, not higher, use of habitat experiencing an outbreak of prey insects. Assuming that birds select the nearby patch providing highest intake rate caused the model to reproduce all but one pattern, whereas assuming birds select the highest-intake patch over a large radius produced an unrealistic distribution of movement distances. The pattern reproduced under none of the theories, a negative relation between bird density and distance to trees, appears to result from a process not in the model: birds return to trees at night to roost. We conclude that a foraging model for small insectivorous birds in diverse habitat should assume birds can sense higher food supply but over short, not long, distances.     

A Resistant-Kernel Model of Connectivity for Amphibians that Breed in Vernal Pools

Abstract:  Pool-breeding amphibian populations operate at multiple scales, from the individual pool to surrounding upland habitat to clusters of pools. When metapopulation dynamics play a role in long-term viability, conservation efforts limited to the protection of individual pools or even pools with associated upland habitat may be ineffective over the long term if connectivity among pools is not maintained. Connectivity becomes especially important and difficult to assess in regions where suburban sprawl is rapidly increasing land development, road density, and traffic rates. We developed a model of connectivity among vernal pools for the four ambystomatid salamanders that occur in Massachusetts and applied it to the nearly 30,000 potential ephemeral wetlands across the state. The model was based on a modification of the kernel estimator (a density estimator commonly used in home range studies) that takes landscape resistance into account. The model was parameterized with empirical migration distances for spotted salamanders ( Ambystoma maculatum ), dispersal distances for marbled salamanders ( A. opacum ), and expert-derived estimates of landscape resistance. The model ranked vernal pools in Massachusetts by local, neighborhood, and regional connectivity and by an integrated measure of connectivity, both statewide and within ecoregions. The most functionally connected pool complexes occurred in southeastern and northeastern Massachusetts, areas with rapidly increasing suburban development. In a sensitivity analysis estimates of pool connectivity were relatively insensitive to uncertainty in parameter estimates, especially at the local and neighborhood scales. Our connectivity model could be used to prioritize conservation efforts for vernal-pool amphibian populations at broader scales than traditional pool-based approaches.     

Echolocation behavior of the bat <Emphasis Type="Italic">Vespertilio murinus</Emphasis> reveals the border between the habitat types “edge” and “open space”

We test the hypothesis that echolocation behavior can be used to find the border between bat habitats. Assuming that bats react to background targets in “edge space” but not in “open space”, we determined the border between these two habitat types for commuting individuals of the parti-colored bat Vespertilio murinus. We recorded sequences of bats’ echolocation signals while they flew parallel to the walls of large buildings and to the ground and determined the signals’ average bandwidth, duration, and pulse interval. These parameters varied systematically with the estimated horizontal and vertical distances between the bats and the background. A distinct effect of horizontal distance to the background on echolocation behavior was found for horizontal distances of less than 6 m, thus indicating the border between edge and open space. Only a few bats flew at vertical distances below 5 m. However, enough passages at vertical distances of 5 m and above indicated that the vertical border is somewhere below a distance of 5 m. Within edge space, V. murinus reacted to the background by reducing signal duration, increasing bandwidth at closer distances, and often emitting one signal per wing beat. In open space, signal parameters did not vary as a function of distance to the background. There, V. murinus emitted the longest signals with the narrowest bandwidth and often made one or two wing beats without emitting a pulse. With our data we support with statistical methods the hypothesis that echolocation behavior reveals the border between the habitat types “edge” and “open space”.     

Genes and song: genetic and social connections in fragmented habitat in a woodland bird with limited dispersal

Understanding the processes leading to population declines in fragmented landscapes is essential for successful conservation management. However, isolating the influence of disparate processes, and dispersal in particular, is challenging. The Grey Shrike-thrush, Colluricincla harmonica, is a sedentary woodland-dependent songbird, with learned vocalizations whose incidence in suitable habitat patches falls disproportionally with decline in tree cover in the landscape. Although it has been suggested that gaps in tree cover might act as barriers to its dispersal, the species remains in many remnants of native vegetation in agricultural landscapes, suggesting that it may have responded to habitat removal and fragmentation by maintaining or even increasing dispersal distances. We quantified population connectivity of the Grey Shrike-thrush in a system fragmented over more than 120 years using genetic (microsatellites) and acoustic (song types) data. First, we tested for population genetic and acoustic structure at regional and local scales in search of barriers to dispersal or gene flow and signals of local spatial structuring indicative of restricted dispersal or localized acoustic similarity. Then we tested for effects of habitat loss and fragmentation on genetic and acoustic connectivity by fitting alternative models of mobility (isolation-by-distance [the null model] and reduced and increased movement models) across treeless vs. treed areas. Birds within -5 km of each other had more similar genotypes and song types than those farther away, suggesting that dispersal and song matching are limited in the region. Despite restricted dispersal detected for females (but not males), populations appeared to be connected by gene flow and displayed some cultural (acoustic) connectivity across the region. Fragmentation did not appear to impact greatly the dispersal of the Grey Shrike-thrush: none of the mobility models fit the genetic distances of males, whereas for females, an isolation-by-distance model could not be rejected in favor of the models of reduced or increased movement through treeless gaps. However, dissimilarities of the song types were more consistent with the model of reduced cultural connectivity through treeless areas, suggesting that fragmentation impedes song type sharing in the Grey Shrike-thrush. Our paper demonstrates that habitat fragmentation hinders important population processes in an Australian woodland bird even though its dispersal is not detectably impacted.     

An animal movement model incorporating home range and habitat selection

Wildlife biologists are often interested in how an animal uses space and the habitat resources within that space. We propose a single model that estimates an animal’s home range and habitat selection parameters within that range while accounting for the inherent autocorrelation in frequently sampled telemetry data. The model is applied to brown bear telemetry data in southeast Alaska. This article is based on a portion of this author’s Ph.D. dissertation completed in 2003 at the University of Iowa.     

Testing the robustness of management decisions to uncertainty: Everglades restoration scenarios.

To effectively manage large natural reserves, resource managers must prepare for future contingencies while balancing the often conflicting priorities of different stakeholders. To deal with these issues, managers routinely employ models to project the response of ecosystems to different scenarios that represent alternative management plans or environmental forecasts. Scenario analysis is often used to rank such alternatives to aid the decision making process. However, model projections are subject to uncertainty in assumptions about model structure, parameter values, environmental inputs, and subcomponent interactions. We introduce an approach for testing the robustness of model-based management decisions to the uncertainty inherent in complex ecological models and their inputs. We use relative assessment to quantify the relative impacts of uncertainty on scenario ranking. To illustrate our approach we consider uncertainty in parameter values and uncertainty in input data, with specific examples drawn from the Florida Everglades restoration project. Our examples focus on two alternative 30-year hydrologic management plans that were ranked according to their overall impacts on wildlife habitat potential. We tested the assumption that varying the parameter settings and inputs of habitat index models does not change the rank order of the hydrologic plans. We compared the average projected index of habitat potential for four endemic species and two wading-bird guilds to rank the plans, accounting for variations in parameter settings and water level inputs associated with hypothetical future climates. Indices of habitat potential were based on projections from spatially explicit models that are closely tied to hydrology. For the American alligator, the rank order of the hydrologic plans was unaffected by substantial variation in model parameters. By contrast, simulated major shifts in water levels led to reversals in the ranks of the hydrologic plans in 24.1-30.6% of the projections for the wading bird guilds and several individual species. By exposing the differential effects of uncertainty, relative assessment can help resource managers assess the robustness of scenario choice in model-based policy decisions.     

Effects of Patch Size and Type of Coffee Matrix on Ithomiine Butterfly Diversity and Dispersal in Cloud-Forest Fragments

Abstract: Determining the permeability of different types of landscape matrices to animal movement is essential for conserving populations in fragmented landscapes. We evaluated the effects of habitat patch size and matrix type on diversity, isolation, and dispersal of ithomiine butterflies in forest fragments surrounded by coffee agroecosystems in the Colombian Andes. Because ithomiines prefer a shaded understory, we expected the highest diversity and abundance in large fragments surrounded by shade coffee and the lowest in small fragments surrounded by sun coffee. We also thought shade coffee would favor butterfly dispersal and immigration into forest patches. We marked 9675 butterflies of 39 species in 12 forest patches over a year. Microclimate conditions were more similar to the forest interior in the shade‐coffee matrix than in the sun‐coffee matrix, but patch size and matrix type did not affect species richness and abundance in forest fragments. Furthermore, age structure and temporal recruitment patterns of the butterfly community were similar in all fragments, independent of patch size or matrix type. There were no differences in the numbers of butterflies flying in the matrices at two distances from the forest patch, but their behavior differed. Flight in the sun‐coffee matrix was rapid and directional, whereas butterflies in shade‐coffee matrix flew slowly. Seven out of 130 recaptured butterflies immigrated into patches in the shade‐coffee matrix, and one immigrated into a patch surrounded by sun coffee. Although the shade‐coffee matrix facilitated movement in the landscape, sun‐coffee matrix was not impermeable to butterflies. Ithomiines exhibited behavioral plasticity in habitat use and high mobility. These traits favor their persistence in heterogeneous landscapes, opening opportunities for their conservation. Understanding the dynamics and resource requirements of different organisms in rural landscapes is critical for identifying management options that address both animals’ and farmers’ needs.     

Habitat selection models to account for seasonal persistence in radio telemetry data

Models for the analysis of habitat selection data incorporate covariates in an independent multinomial selections model (McCracken et al. 1998) Ramsey and Usner 2003 and an extension of that model to include a persistence parameter (2003). In both cases, all parameters are assumed to be fixed through time. Radio telemetry data collected for habitat selection studies typically consist of animal relocations through time, suggesting the need for an extension to these models. We use a Bayesian approach that allows for the habitat selection probabilities, persistence parameter, or both, to change with season. These extensions are particularly important when movement patterns are expected to differ seasonally and/or when availabilities of habitats change throughout the study period due to weather or migration. We implement and compare the models using radio telemetry data for westslope cutthroat trout in two streams in eastern Oregon.     

Long‐Range Movement of Humpback Whales and Their Overlap with Anthropogenic Activity in the South Atlantic Ocean

Humpback whales (Megaptera novaeangliae) are managed by the International Whaling Commission as 7 primary populations that breed in the tropics and migrate to 6 feeding areas around the Antarctic. There is little information on individual movements within breeding areas or migratory connections to feeding grounds. We sought to better understand humpback whale habitat use and movements at breeding areas off West Africa, and during the annual migration to Antarctic feeding areas. We also assessed potential overlap between whale habitat and anthropogenic activities. We used Argos satellite‐monitored radio tags to collect data on 13 animals off Gabon, a primary humpback whale breeding area. We quantified habitat use for 3 cohorts of whales and used a state‐space model to determine transitions in the movement behavior of individuals. We developed a spatial metric of overlap between whale habitat and models of cumulative human activities, including oil platforms, toxicants, and shipping. We detected strong heterogeneity in movement behavior over time that is consistent with previous genetic evidence of multiple populations in the region. Breeding areas for humpback whales in the eastern Atlantic were extensive and extended north of Gabon late in the breeding season. We also observed, for the first time, direct migration between West Africa and sub‐Antarctic feeding areas. Potential overlap of whale habitat with human activities was the highest in exclusive economic zones close to shore, particularly in areas used by both individual whales and the hydrocarbon industry. Whales potentially overlapped with different activities during each stage of their migration, which makes it difficult to implement mitigation measures over their entire range. Our results and existing population‐level data may inform delimitation of populations and actions to mitigate potential threats to whales as part of local, regional, and international management of highly migratory marine species. Cuantificación de los Movimientos de Gran Amplitud y el Traslape Potencial con Actividad Antropogénica y las Ballenas Jorobadas en el Océano Atlántico Sur     

Modelling dispersal with diffusion and habitat selection: Analytical results for highly fragmented landscapes

Quantifying dispersal is crucial both for understanding ecological population dynamics, and for gaining insight into factors that affect the genetic structure of populations. The role of dispersal becomes pronounced in highly fragmented landscapes inhabited by spatially structured populations. We consider a landscape consisting of a set of habitat patches surrounded by unsuitable matrix, and model dispersal by assuming that the individuals follow a random walk with parameters that may be specific to the habitat type. We allow for spatial variation in patch quality, and account for edge-mediated behavior, the latter meaning that the individuals bias their movement towards the patches when close to an edge between a patch and the matrix. We employ a diffusion approximation of the random walk model to derive analytical expressions for various characteristics of the dispersal process. For example, we derive formulae for the time that an individual is expected to spend in its current patch i, and for the time that it will spend in the matrix, both conditional on the individual hitting next a given patch j before hitting any of the other patches or dying. The analytical formulae are based on the assumptions that the landscape is infinitely large, that the patches are circularly shaped, and that the patches are small compared to interpatch distances. We evaluate the effect of these assumptions by comparing the analytical results to numerical results in a real patch network that violates all of the three assumptions. We then consider a landscape that fulfills the assumptions, and show that in this case the analytical results are in a very good agreement with the numerical results. The results obtained here allow the construction of computationally efficient dispersal models that can be used as components of metapopulation models.     

Old models explain new observations of butterfly movement at patch edges

Understanding movement in heterogeneous environments is central to predicting how landscape changes affect animal populations. Several recent studies point out an intriguing and distinctive looping behavior by butterflies at habitat patch edges and hypothesize that this behavior requires a new framework for analyzing animal movement. We show that this looping behavior could be caused by a longstanding movement model, biased correlated random walk, with bias toward habitat patches. The ability of this longstanding model to explain recent observations reinforces the point that butterflies respond to habitat heterogeneity and do not move randomly through heterogeneous environments. We discuss the implications of different movement models for predicting butterfly responses to landscape change, and our rationale for retaining longstanding movement models, rather than developing new modeling frameworks for looping behavior at patch edges.     

A Habitat-Based Metapopulation Model of the California Gnatcatcher

We present an analysis of the metapopulation dynamics of the federally threatened coastal California Gnatcatcher (Polioptila c. californica) for an approximately 850 km² region of Orange County, California. We developed and validated a habitat suitability model for this species using data on topography, vegetation, and locations of gnatcatcher pair observations. Using this habitat model, we calculated the spatial structure of the metapopulation, including size and location of habitat patches and the distances among them. We used data based on field studies to estimate parameters such as survival, fecundity, dispersal, and catastrophes, and combined these parameters with the spatial structure to build a stage-structured, stochastic, spatially-explicit metapopulation model. The model predicted a fast decline and high risk of population extinction with most combinations of parameters. Results were most sensitive to density-dependent effects, the probability of weather-related catastrophes, adult survival, and adult fecundity. Based on data used in the model, the greatest difference in results was given when the simulation's time horizon was only a few decades, suggesting that modeling based on longer or shorter time horizons may underestimate the effects of alternative management actions.     

A method for assigning species into groups based on generalized Mahalanobis distance between habitat model coefficients

Habitat association models are commonly developed for individual animal species using generalized linear modeling methods such as logistic regression. We considered the issue of grouping species based on their habitat use so that management decisions can be based on sets of species rather than individual species. This research was motivated by a study of western landbirds in northern Idaho forests. The method we examined was to separately fit models to each species and to use a generalized Mahalanobis distance between coefficient vectors to create a distance matrix among species. Clustering methods were used to group species from the distance matrix, and multidimensional scaling methods were used to visualize the relations among species groups. Methods were also discussed for evaluating the sensitivity of the conclusions because of outliers or influential data points. We illustrate these methods with data from the landbird study conducted in northern Idaho. Simulation results are presented to compare the success of this method to alternative methods using Euclidean distance between coefficient vectors and to methods that do not use habitat association models. These simulations demonstrate that our Mahalanobis-distance-based method was nearly always better than Euclidean-distance-based methods or methods not based on habitat association models. The methods used to develop candidate species groups are easily explained to other scientists and resource managers since they mainly rely on classical multivariate statistical methods.     

Estimating behavioral parameters in animal movement models using a state-augmented particle filter

Data on fine-scale animal movement are being collected worldwide, with the number of species being tagged and the resolution of data rapidly increasing. In this study, a general methodology is proposed to understand the patterns in these high-resolution movement time series that relate to marine animal behavior. The approach is illustrated with dive data from a northern fur seal (Callorhinus ursinus) tagged on the Pribilof Islands, Alaska, USA. We apply a state-space model composed of a movement model and corresponding high-resolution vertical movement data. The central goal is to estimate parameters of this movement model, particularly their variation on appropriate time scales, thereby providing a direct link to behavior. A particle filter with state augmentation is used to jointly estimate the movement parameters and the state. A multiple iterated filter using overlapping data segments is implemented to match the parameter time scale with the behavioral inference. The time variation in the auto-covariance function facilitates identification of a movement model, allows separation of observation and process noise, and provides for validation of results. The analysis yields fitted parameters that show distinct time-evolving changes in fur seal behavior over time, matching well what is observed in the original data set.