Model-Based Distance Sampling

Conventional distance sampling adopts a mixed approach, using model-based methods for the detection process, and design-based methods to estimate animal abundance in the study region, given estimated probabilities of detection. In recent years, there has been increasing interest in fully model-based methods. Model-based methods are less robust for estimating animal abundance than conventional methods, but offer several advantages: they allow the analyst to explore how animal density varies by habitat or topography; abundance can be estimated for any sub-region of interest; they provide tools for analysing data from designed distance sampling experiments, to assess treatment effects. We develop a common framework for model-based distance sampling, and show how the various model-based methods that have been proposed fit within this framework.     

Experimental establishment of a declining dry-grassland flagship species in relation to seed origin and target environment

Supporting species persistence may involve (re)connecting suitable habitats. However, for many declining species habitat suitability and drivers of establishment are poorly known. We addressed this experimentally for a declining flagship species of dry grasslands in Germany, Armeria maritima subsp. elongata. In three regions, we sowed seeds from each of eight source populations back to their origin and to eight apparently suitable, but currently unoccupied, habitats close to the source populations. Overall, seeds germinated and seedlings established equally well in occupied and potential sites indicating that suitable habitats are available, but lack seed input. Germination and establishment varied among sowing sites. Moreover, seeds from populations of lower current connectivity established less well in new sites, and establishment was more variable among seeds from smaller than from larger populations, possibly reflecting genetic consequences of habitat fragmentation. Further, establishment across different new environments differed between seeds from different populations. As this was neither related to a home-away contrast nor to geographic or environmental distance between sites it could not clearly be attributed to local adaptation. To promote long-term persistence within this dry-grassland meta-population context we suggest increasing the density of suitable habitats and supporting dispersal connecting multiple sites, e.g. by promoting sheep transhumance, to increase current populations and their connectivity, and to colonise suitable habitats with material from different sources. We suggest that sowing experiments with characteristic species, including multiple source populations and multiple recipient sites, should be used regularly to inform connecting efforts in plant conservation.     

Bayesian Spatial Point Process Modeling of Line Transect Data

This paper develops a Bayesian approach for spatial inference on animal density from line transect survey data. We model the spatial distribution of animals within a geographical area of interest by an inhomogeneous Poisson process whose intensity function incorporates both covariate effects and spatial smoothing of residual variation. Independently thinning the animal locations according to their estimated detection probabilities results into another spatial Poisson process for the sightings (the observations). Prior distributions are elicited for all unknown model parameters. Due to the sparsity of data in the application we consider, eliciting sensible prior distributions is important in order to get meaningful estimation results. A reversible jump Markov Chain Monte Carlo (MCMC) algorithm for simulation of the posterior distribution is developed. We present results for simulated data and a real data set of minke whale pods from Antarctic waters. The main advantages of our method compared to design-based analyses are that it can use data arising from sources other than specifically designed surveys and its ability to link covariate effects to variation of animal density. The Bayesian paradigm provides a coherent framework for quantifying uncertainty in estimation results.     

The roles of habitat features, disturbance, and distance from putative source populations in structuring alien plant invasions at the urban/wildland interface on the Cape Peninsula, South Africa

Natural areas are becoming increasingly fragmented and embedded in an urban matrix. Natural and semi-natural areas at the urban/wildland interface are threatened by a variety of ‘edge effects’, and are especially vulnerable to invasion by introduced plants, with suburban gardens acting as significant sources of alien propagules. Urban/wildland interfaces also provide access for humans, leading to various types of disturbance. Alien plant invasions are one of the biggest threats facing remaining natural areas on the Cape Peninsula, South Africa. The area provides an ideal opportunity to study the dynamics of invasions at the urban/wildland interface, since the largest natural area, the Table Mountain National Park (TMNP), is surrounded by the city of Cape Town. We explored invasion patterns in Newlands Forest (a small section of the TMNP) and detailed the roles of habitat features and distance from putative source populations in three main habitat types: natural Afromontane forest, riverine woodland habitats, and plantations of exotic pines (Pinus radiata and P. pinaster). We also examined the role of disturbance in driving invasions in two of these habitat types (Afromontane forest and pine plantations). We hypothesized that alien richness and alien stem density would decrease with distance from the urban/wildland interface, and that alien richness and alien stem density would increase with increasing levels of human disturbance.Distance from putative source populations and levels of anthropogenic disturbance influenced alien richness in Newlands Forest but not alien stem density. Alien richness decreased significantly with distance from presumed sources in the pine habitat, and increased significantly with disturbance in the forest habitat. Percentage overstorey cover and soil pH were important environmental variables associated with alien plant species. A socio-economic approach is discussed as being the most effective approach to the management and prevention of alien plant species in Newlands Forest.     

Bayesian Methods for Hierarchical Distance Sampling Models

The few distance sampling studies that use Bayesian methods typically consider only line transect sampling with a half-normal detection function. We present a Bayesian approach to analyse distance sampling data applicable to line and point transects, exact and interval distance data and any detection function possibly including covariates affecting detection probabilities. We use an integrated likelihood which combines the detection and density models. For the latter, densities are related to covariates in a log-linear mixed effect Poisson model which accommodates correlated counts. We use a Metropolis-Hastings algorithm for updating parameters and a reversible jump algorithm to include model selection for both the detection function and density models. The approach is applied to a large-scale experimental design study of northern bobwhite coveys where the interest was to assess the effect of establishing herbaceous buffers around agricultural fields in several states in the US on bird densities. Results were compared with those from an existing maximum likelihood approach that analyses the detection and density models in two stages. Both methods revealed an increase of covey densities on buffered fields. Our approach gave estimates with higher precision even though it does not condition on a known detection function for the density model.     

Herpetofauna diversity and microenvironment correlates across a pasture-edge-interior ecotone in tropical rainforest fragments in the Los Tuxtlas Biosphere Reserve of Veracruz, Mexico

We evaluated the relationship between amphibian and reptile diversity and microhabitat dynamics along pasture-edge-interior ecotones in a tropical rainforest in Veracruz, Mexico. To evaluate the main correlation patterns among microhabitat variables and species composition and richness, 14 ecotones were each divided into three habitats (pasture, forest edge and forest interior) with three transects per habitat, and sampled four times between June 2003 and May 2004 using equal day and night efforts. We measured 12 environmental variables describing the microclimate, vegetation structure, topography and distance to forest edge and streams.After sampling 126 transects (672 man-hours effort) we recorded 1256 amphibians belonging to 21 species (pasture: 12, edge: 14, and interior: 13 species), and 623 reptiles belonging to 33 species (pasture: 11, edge: 25, and interior: 22 species). There was a difference in species composition between pasture and both forest edge and interior habitats. A high correlation between distance to forest edge and temperature, understorey density, canopy cover, leaf litter cover, and leaf litter depth was found. There was also a strong relationship between the composition of amphibian and reptile ensembles and the measured environmental variables. The most important variables related to amphibian and reptile ensembles were canopy cover, understorey density, leaf litter cover and temperature.Based on amphibian and reptile affinity for the habitats along the ecotone, species were classified into five ensembles (generalist, pasture, forest, forest edge and forest interior species). We detected six species that could indicate good habitat quality of forest interior and their disappearance may be an indication of habitat degradation within a fragment, or that a fragment is not large enough to exclude edge effects. Different responses to spatial and environmental gradients and different degrees of tolerance to microclimatic changes indicated that each ensemble requires a different conservation strategy. We propose to maintain in the Los Tuxtlas Biosphere Reserve the forest remnants in the lowlands that have gentler slopes and a deep cover of leaf litter, a dense understorey, and high relative humidity and low temperature, to buffer the effects of edge related environmental changes and the invasion of species from the matrix.     

How peri-urban areas can strengthen animal populations within cities: A modeling approach

We explore the extent to which inner-city fauna can be enhanced by source areas in peri-urban zones as a response to a decreasing quality and size of green habitats within cities. The objectives were to get a better understanding of the interaction between animal populations of urban and peri-urban areas, and the role of urban green structures within this relationship, and to find out the extent to which peri-urban areas can contribute to urban animal populations. We illustrate the idea of peri-urban support by using a simulation model for individual animal movement, applied in a particular case-study with butterflies as model species. Results show differences in accessibility of inner-city areas between model butterfly species that differ in mobility. The impact of peri-urban individuals on populations of inner-city habitats differed among several peri-urban source-scenarios: the enlargement of the inner-city butterfly population by peri-urban individuals was determined as 7-36% for ‘moderate dispersers’ and 19-56% for ‘good dispersers’. Results also show that well-connected habitat patches within existing urban green structures were more likely to be visited by peri-urban individuals than isolated habitat patches. We conclude that peri-urban nature areas, if large enough, can have a potentially positive influence on the presence of fauna in inner-city neighborhoods. In addition, results suggest that connectivity between inner-city and peri-urban habitat patches enhances contribution of peri-urban migrants to inner-city populations. By providing a range of different habitats, from inner-city up to peri-urban area, moderately mobile habitat specialists could better compete against the small set of successful habitat generalists that are increasing in urban environments all over the world.     

Reconciling the dichotomy between single species and ecosystem conservation: black kites (Milvus migrans) and eutrophication in pre-Alpine lakes

In recent times there has been a growing dichotomy between preservation of single species and broader, ecosystem-based approaches to conservation. Freshwater habitats are among the most highly human-impacted ecosystems. We used a long-term data set on black kites (Milvus migrans), a threatened raptor dependent on aquatic habitats, to explore ways to reconcile single species and biodiversity-driven approaches to conservation. In the pre-Alpine lakes of northern Italy, black kite populations showed medium-low density, extremely low breeding success and widespread declines. Spatio-temporal variations showed density and breeding success to be positively related to ecosystem productivity (as estimated by phosphorus concentrations in lakes), availability of aquatic habitats and grassland, and to be negatively related to extent of farmland and fish harvest by professional fishermen. Fish species richness, used as a surrogate of biodiversity, was highest in one oligotrophic lake, but on average increased with increasing ecosystem productivity (i.e. lake eutrophication). Given expected future declines in ecosystem productivity, kite conservation will be helped by enhancing populations of alternative prey in terrestrial habitats (e.g. through incentives for grassland), and higher regulation of fish harvest. On the other hand, ecosystem management may profit from the use of black kites or other aerial piscivores as indicators of biodiversity and of diffuse ecosystem stress, such as sustainability of fishing practices.     

Modelling of wildlife fatality hotspots along the Snowy Mountain Highway in New South Wales, Australia

The effects of roads on the natural environment is of growing concern world-wide and foremost amongst these effects are the fatalities of wildlife killed in collisions with vehicles. Aside from animal welfare and human safety considerations, fatalities may have significant impacts on the population dynamics of species living adjacent to roads and thus can adversely affect the viability of local populations. As such, the need to quantify and mitigate road-based fatalities is paramount. With a vast expanse of roads it is imperative to identify where animals are most likely to be killed (i.e. hotspots) and what are the contributing factors. In order to identify hotspots, we develop a modelling approach for both presence and presence/absence data. We use data collected from the Snowy Mountain Highway in southern New South Wales, Australia, to compare the effectiveness of this approach for five species/groups of species. We observed that models of species killed in a clumped fashion were effective at identifying hotspots, while for species where fatalities were distributed evenly along the road the models were less effective. We recommend that where actual presence data exists spatial clustering is the preferred method of hotspot identification. Predictive models of presence/absence date should be constructed if the intention is to extrapolate to additional areas. The added benefit of predictive models are that they enable the identification of explanatory factors and this knowledge enables species-specific management strategies to be developed and implemented at hotspot locations.     

Dragonfly crisis in Japan: A likely consequence of recent agricultural habitat degradation

Many Japanese dragonfly species depend on habitat complexes maintained in rice paddy systems. We postulated that recent alterations to habitat complexes in paddy systems have had adverse effects on dragonfly populations, especially those ‘once common species’ that have come to depend primarily on paddy systems following losses of natural floodplain habitats. A high proportion of Japanese lentic dragonfly species depends on paddy fields or agricultural ponds that have been extensively degraded, while lotic species can often use both paddies and natural river systems. Thus we also postulated that lentic species are more susceptible to changes in agricultural habitats and are subject to higher extinction risks than lotic species. We aimed to extend previous work on estimating dragonfly extinction risk by developing mechanistic insights into the processes involved. Postulates were tested by analyzing relationships between (1) previous quantitative extinction risk assessments for dragonfly species and (2) species’ ecological characteristics (i.e., distribution range and habitat type [lentic or lotic]). Lentic species were disproportionately represented among those with elevated extinction risk. Species with large distribution ranges were also subject to higher extinction risks than those with narrower ranges, reflecting a driving force acting at a national scale (i.e., intensive degradation of paddy systems).     

Does the matrix matter? A forest primate in a complex agricultural landscape

Many threatened primates now exist in fragmented forest habitats. The survival of these populations may depend on their ability to utilise agricultural or other matrix habitats between forest fragments, but this is poorly known. Here, we systematically investigate an arboreal primate’s use of a heterogeneous matrix in a fragmented forest landscape: the Angola black-and-white colobus (Colobus angolensis palliatus) in southern Kenya. We used a novel technique, based on semi-structured interviews with local informants, to address the difficulty of sampling relatively rare but important events, such as dispersal between fragments. We found that colobus frequently travelled and foraged in indigenous matrix vegetation (such as mangrove, wooded shrubland and shrubland) up to 4 km from the nearest forest fragments. Agricultural habitats, such as perennial plantation (coconut, mango and cashew nut) were also used by colobus for travelling and foraging (in remnant indigenous trees). The probability of sighting colobus in the matrix increased with the proportion of both tall (>6 m) vegetation cover and food tree cover, but declined with distance from forest habitat. Our findings suggest that certain matrix habitats are important for C. a. palliatus, and that future primate conservation initiatives might benefit from adopting a ‘landscape-level’ approach to habitat management, particularly in fragmented forest systems.     

Animal habitat isolation by roads and agricultural fields

Natural areas are continuously disappearing. Surviving patches resemble islands in terms of limited area, isolation and distance from each other.Road construction and agricultural activities contribute to habitat isolation. Field studies suggest that roads represent barriers and cut off the gene flow by dividing animal populations into fractions on either side of the road.Several mobility diagrams show significant isolation effects of roads on populations of forest-dwelling mice (Apodemus flavicollis) and carabid beetles.Small habitat islands tend to hold more animal species than expected according to the island biogeographic theory. The $\text{N}{}_{\mathrm{s}}\text{N}{}_{\mathrm{i}}$ ratio is highest in small isolates, indicating continuous movement of individual animals from surrounding agricultural areas resulting in unstable species composition.     

Analysis of Population Change and Movement Using Robust Design Removal Data

In capture-mark-reencounter studies, Pollock’s robust design combines methods for open populations with methods for closed populations. Open population features of the robust design allow for estimation of rates of death or permanent emigration, and closed population features enhance estimation of population sizes. We describe a similar design, but for use with removal data. Data collection occurs on secondary sampling occasions clustered within primary sampling periods. Primary sampling periods are intervals of brief enough duration that it can be safely assumed that the population is unchanged by births, deaths, immigration or emigration during them; all population change and movement occurs between primary sampling periods. Our model provides a basis for inference about population size, changes in population size, and movement rates among sample locations between primary sampling periods. Movement rates are modeled as functions of distance and time. Capture probabilities are modeled as a function of effort. We apply the model to data obtained in attempting to eradicate an introduced population of veiled chameleons (Chamaeleo calyptratus) on the island of Maui in Hawaii.Supplementary materials accompanying this paper appear online.     

Complementary Hotspot Inventory - A method for identification of important areas for biodiversity at the forest stand level

Forest stands are the basic planning units of managed forest landscapes, and the structural composition of these units is important for conservation of biodiversity. We present a methodological approach for identification and mapping of important structural and environmental features of forest stands. Based on an analysis of habitats of red-listed species and a synthesis of results from research on spatial distribution of forest species, we developed a habitat inventory approach (Complementary Hotspot Inventory, CHI) that is currently used in forestry planning in Norway. The CHI maps fine-scale hotspots for 12 habitat types that are further classified according to positions along main environmental gradients (productivity and humidity). Consisting of different substrates in different environments, these habitats to a large degree support different species assemblages. By incorporating both the hotspot and the complementary approach, the CHI produces data tuned for later conservation measures. The high spatial resolution of data facilitates the use of conservation measures at different spatial scales, from single-tree retention to forest reserves. A validation test of habitats identified by CHI showed that the density of red-listed species was four times that of randomly selected old forests.     

Reflected Stochastic Differential Equation Models for Constrained Animal Movement

Movement for many animal species is constrained in space by barriers such as rivers, shorelines, or impassable cliffs. We develop an approach for modeling animal movement constrained in space by considering a class of constrained stochastic processes, reflected stochastic differential equations. Our approach generalizes existing methods for modeling unconstrained animal movement. We present methods for simulation and inference based on augmenting the constrained movement path with a latent unconstrained path and illustrate this augmentation with a simulation example and an analysis of telemetry data from a Steller sea lion (Eumatopias jubatus) in southeast Alaska.     

Bayesian Inference for Animal Space Use and Other Movement Metrics

The analysis of animal movement and resource use has become a standard tool in the study of animal ecology. Telemetry devices have become quite sophisticated in terms of overall size and data collecting capacity. Statistical methods to analyze movement have responded, becoming ever more complex, often relying on state-space modeling. Estimation of movement metrics such as utilization distributions have not followed suit, relying primarily on kernel density estimation. Here we consider a method for making inference about space use that is free of all of the major problems associated with kernel density estimation of utilization distributions such as autocorrelation, irregular time gaps, and error in observed locations. Our proposed method is based on a data augmentation approach that defines use as a summary of the complete path of the animal which is only partially observed. We use a sample from the posterior distribution of the complete path to construct a posterior sample for the metric of interest. Three basic importance sampling based methods for sampling from the posterior distribution of the path are proposed and compared. We demonstrate the augmentation approach by estimating a spatial map of diving intensity for female northern fur seals in the Pribilof Islands, Alaska.     

Models for Jointly Estimating Abundances of Two Unmarked Site-Associated Species Subject to Imperfect Detection

In ecological field surveys, it is often of interest to estimate the abundance of species. It is frequently the case that unmarked animals are counted on different sites over several time occasions. A natural starting point to model these data, while accounting for imperfect detection, is by using Royle’s N-mixture model (Biometrics 60:108–115, 2004). Subsequently, many multivariate extensions have been proposed to model communities as a whole. However, these approaches are used to study species richness and other community-level variables and do not focus on the relationship between two site-associated species. Here, we extend the N-mixture modelling framework to model two site-associated species abundances jointly and propose to measure the influence of one species’ abundance on the populations of the other and study how this changes over time and space. By including a new parameter in the abundance distribution of one of the species, linking it to abundance of the other, our proposed model treats extra variability as an effect induced by an associated species’ abundance and allows one to study how environmental covariates may affect this. Using results from simulation studies, we show that the model is able to recover true parameter estimates. We illustrate our approach using data from bald eagles and mallards obtained in the 2015 survey of the North American Breeding Bird Survey. By using the joint model, we were able to separate overdispersion from mallard-induced variability and hence what would be accounted for with a dispersion parameter in the univariate framework for the eagles was explained by covariates related to mallard abundance in the joint model. Our approach represents an attractive, yet simple, way of modelling site-associated species populations jointly. Conservation ecologists can use the approach to devise management strategies based on the strength of association between species, which may be due to direct interactions and/or environmental effects affecting both species’ populations. Also, mathematical ecologists can use this framework to develop tools for studying population dynamics under different scenarios. Supplementary materials accompanying this paper appear on-line.     

A new method based on taxonomic sufficiency to simplify studies on Neotropical ant assemblages

Insects, particularly ants, are good bioindicators of the state of ecosystems. Nevertheless, incorporating them into conservation surveys is expensive due to problems associated with their identification, which is exacerbated by the fact that there are fewer and fewer taxonomists working today. “Taxonomic sufficiency” (TS), which identifies organisms to a level of taxonomic resolution sufficient enough to satisfy the objectives of a study, has never been applied to Neotropical ant communities. We analysed five Neotropical datasets representing ant assemblages collected with different sampling methods in various habitats. We first treated them using two complementary and cumulative TS methods, higher-taxon and “indicator taxa” surrogacies, before testing a new approach called “mixed-level method” that combines the two previous approaches. For the higher-taxon surrogacy, we showed that, above species, genus is the most informative taxonomic level. Then, mixed-level method provided more information on ant assemblages than did the two others, even though the “indicator taxa” surrogacy was based on relevant indicator genera. Although habitat type has no effect on its efficiency, this new method is influenced by the dataset structure and the type of sampling method used to collect data. We have thus developed a new method for analyzing Neotropical ant faunas that enables the taxonomic work linked to the identification of problematic species to be significantly reduced, while conserving most of the information on the ant assemblage. This method should enhance the work of Neotropical entomologists not specialised in taxonomy, particularly those concerned with biological conservation and indication.     

A Bayesian multinomial model for analyzing categorical habitat selection data

Modeling the number of uses of discrete habitat types by animals with a multinomial distribution, we illustrate the use of Bayesian methods to estimate selection. An advantage of this approach in assessing selection is the construction of credibility intervals that do not rely on large sample normal theory. In addition, credibility intervals for ranked selection of habitats are easily obtained. Bayes factors and Bayesian p values (posterior predictive values) are used to test the hypothesis of selection for each animal, test selection across all animals and for multiple comparisons among habitats. We compare our method to alternative methods for a real dataset. Freely available WinBUGS software is used to fit the model and test hypotheses.     

Using multiple metrics to assess the effects of forest succession on population status: A comparative study of two terrestrial salamanders in the US Pacific Northwest

Investigations to determine stable or source-sink animal population dynamics are challenging and often infeasible for most species due to the time and expense of mark-recapture studies and the challenge of life histories attributes that result in low detectability and low recapture probabilities. Often, managers rely solely on occupancy or relative abundance patterns to assess a species’ sensitivity to environmental changes. Greater insight into population-level responses to environmental change can be gained by consideration of a combination of readily obtainable metrics, including occupancy, relative abundance, demographic structure and body condition. We examined how these metrics can improve our understanding of population-level responses to forest disturbance, using datasets for two exemplar species of terrestrial salamanders resident to the Pacific Northwestern USA. We compared population metrics for the Del Norte salamander (Plethodon elongatus) and the Siskiyou Mountains salamander (Plethodon stormi) across the seral continuum represented by four forest age classes: pre-canopy, young, mature, and old-growth. We compared these data with those collected from reference stands in mature (P. stormi) or old-growth (P. elongatus) forest containing robust populations. P. elongatus was twice as common as P. stormi. Both occupancy and salamander counts were lowest at pre-canopy sites for both species. Although there were numerous P. elongatus detections in young forests, higher proportions of these individuals were juveniles and sub-adults when compared to populations in late-seral forests. We found a negative relationship between the proportion of immature animals and total counts at a site, indicating that the high proportion of young animals in young forest stands is likely due to dispersal of young salamanders from nearby source populations and/or low survival of adult animals in young forests. We also found reduced body condition of P. stormi populations in young forests. Our results suggest that there are costs to populations occupying early seral forests, such as skewed age class structure and reduced body condition that are indicative of sink populations. Consideration of population-level metrics beyond occupancy and relative abundance can provide important insights when assessing a species’ sustainability in managed forest landscapes.