Species Occurrence Dynamics Research Articles

Orchidaceae species in the flora of Krasnoyarsk suburban pine cenoses

The Orchid species cenopopulations (Cypripedium calceolus, C. macranthon, C. guttatum, Neottianthe cucullata) growing in Krasnoyarsk suburban pine cenoses at the forest-steppe were studied. Orchid species are included in the Red Book of the Krasnoyarsk Territory. The investigation objectives are Orchid species occurrence studying and population’s age structure determining in the Krasnoyarsk suburban pine cenoses, both under recreational load and in control. The results of the four species occurrence dynamics at the period 2017-2021 in the control cenosis and cenoses under the anthropogenic influence are presented. In the studied period, the Neottianthe cucullata occurrence did not change, regardless of the level of recreational impact. This species blooms in August, when the recreant’s activity decreases, which can explain its numbers preservation at the same level. The Cypripedium occurrence dynamics depends on the degree of recreational impact. As a result of the ontogenetic analysis, the populations of Neottianthe cucullata, Cypripedium macranthon, and C. guttatum in the control sample area belong to the middle-aged normal complete populations. Populations of Neottianthe cucullata, Cypripedium macranthon, C. calceolus in suburban pine cenoses under the recreational impact should be classified as middle-aged normal incomplete.

Spatial occupancy models for large data sets

Since its development, occupancy modeling has become a popular and useful tool for ecologists wishing to learn about the dynamics of species occurrence over time and space. Such models require presence–absence data to be collected at spatially indexed survey units. However, only recently have researchers recognized the need to correct for spatially induced overdisperison by explicitly accounting for spatial autocorrelation in occupancy probability. Previous efforts to incorporate such autocorrelation have largely focused on logit‐normal formulations for occupancy, with spatial autocorrelation induced by a random effect within a hierarchical modeling framework. Although useful, computational time generally limits such an approach to relatively small data sets, and there are often problems with algorithm instability, yielding unsatisfactory results. Further, recent research has revealed a hidden form of multicollinearity in such applications, which may lead to parameter bias if not explicitly addressed. Combining several techniques, we present a unifying hierarchical spatial occupancy model specification that is particularly effective over large spatial extents. This approach employs a probit mixture framework for occupancy and can easily accommodate a reduced‐dimensional spatial process to resolve issues with multicollinearity and spatial confounding while improving algorithm convergence. Using open‐source software, we demonstrate this new model specification using a case study involving occupancy of caribou (Rangifer tarandus) over a set of 1080 survey units spanning a large contiguous region (108 000 km2) in northern Ontario, Canada. Overall, the combination of a more efficient specification and open‐source software allows for a facile and stable implementation of spatial occupancy models for large data sets.

Landscape matrix mediates occupancy dynamics of Neotropical avian insectivores

In addition to patch-level attributes (i.e., area and isolation), the nature of land cover between habitat patches (the matrix) may drive colonization and extinction dynamics in fragmented landscapes. Despite a long-standing recognition of matrix effects in fragmented systems, an understanding of the relative impacts of different types of land cover on patterns and dynamics of species occurrence remains limited. We employed multi-season occupancy models to determine the relative influence of patch area, patch isolation, within-patch vegetation structure, and landscape matrix on occupancy dynamics of nine Neotropical insectivorous birds in 99 forest patches embedded in four matrix types (agriculture, suburban development, bauxite mining, and forest) in central Jamaica. We found that within-patch vegetation structure and the matrix type between patches were more important than patch area and patch isolation in determining local colonization and local extinction probabilities, and that the effects of patch area, isolation, and vegetation structure on occupancy dynamics tended to be matrix and species dependent. Across the avian community, the landscape matrix influenced local extinction more than local colonization, indicating that extinction processes, rather than movement, likely drive interspecific differences in occupancy dynamics. These findings lend crucial empirical support to the hypothesis that species occupancy dynamics in fragmented systems may depend greatly upon the landscape context.

An integrated model of habitat and species occurrence dynamics

Summary1. Relationships between animal populations and their habitats are well known and commonly acknowledged to be important by animal ecologists, conservation biologists and wildlife managers. Such relationships are most commonly viewed as static, such that habitat at time t is viewed as a determinant of animals present at that same time, t, or sometimes as a determinant of animal population or occurrence dynamics (e.g. between t and t+1).2. Here, we motivate interest in simultaneous dynamics of both habitat and occupancy state (e.g. species presence or absence) and develop models to estimate parameters that describe the dynamics of such systems.3. The models permit inference about transition probabilities for both habitat and focal species occupancy, such that habitat transitions may influence focal species transitions and vice versa.4. Example analyses using data from salamanders in the eastern United States are presented for (i) the special case in which habitat is characterized as either suitable or unsuitable and (ii) the more general case in which different habitat states are expected to influence occupancy dynamics in a less extreme manner (occupancy is possible in the various habitat states).5. We believe that the integrated inference methods presented here will be useful for a variety of ecological and conservation investigations and attain special relevance in the face of habitat dynamics driven by such factors as active management, land use changes and climate change.

Adaptability and vulnerability of high flying Neotropical aerial insectivorous bats to urbanization

AbstractAim Urbanization is a dominant demographic trend throughout the world that involves massive habitat alterations. Understanding how urbanization affects biota is a crucial prerequisite for development and application of effective species conservation programmes. Our study focuses on Neotropical high flying aerial insectivorous bats, an ecologically important, but so far seriously understudied group of vertebrates.Location Panama.Methods Using acoustic monitoring, we assessed and compared species occurrence, composition and activity of aerial insectivorous bats at three site categories located on the isthmus in Panama: forest, urban areas and a forest–town interface.Results In 2 years of field work, we recorded 44,744 bat passes over the microphone and identified a total of 25 aerial insectivorous bat species. Species richness was highest in the forest, decreased towards the forest–town interface and was lowest at the urban sites, while dominance (Berger‐Parker‐Index) increased from the forest to the urban sites. Overall, general bat activity (passes min−1) was highest at the forest–town interface and lowest at the urban sites. Multivariate analysis suggests compositional differences in species occurrence and activity among site categories with mainly molossid species occurring in urban areas.Main conclusions Our results clearly demonstrate species‐specific differences between high flying aerial insectivorous bats concerning their adaptability and vulnerability to urban areas. Our results suggest that a suite of morphological traits including species mobility determine persistence of aerial insectivorous species in cities. Our results underline the necessity for detailed assessments of species‐specific habitat requirements and dynamics of species occurrence and activity over time to develop meaningful conservation tools targeted at aerial insectivorous bats.

Unmodeled observation error induces bias when inferring patterns and dynamics of species occurrence via aural detections

The recent surge in the development and application of species occurrence models has been associated with an acknowledgment among ecologists that species are detected imperfectly due to observation error. Standard models now allow unbiased estimation of occupancy probability when false negative detections occur, but this is conditional on no false positive detections and sufficient incorporation of explanatory variables for the false negative detection process. These assumptions are likely reasonable in many circumstances, but there is mounting evidence that false positive errors and detection probability heterogeneity may be much more prevalent in studies relying on auditory cues for species detection (e.g., songbird or calling amphibian surveys). We used field survey data from a simulated calling anuran system of known occupancy state to investigate the biases induced by these errors in dynamic models of species occurrence. Despite the participation of expert observers in simplified field conditions, both false positive errors and site detection probability heterogeneity were extensive for most species in the survey. We found that even low levels of false positive errors, constituting as little as 1% of all detections, can cause severe overestimation of site occupancy, colonization, and local extinction probabilities. Further, unmodeled detection probability heterogeneity induced substantial underestimation of occupancy and overestimation of colonization and local extinction probabilities. Completely spurious relationships between species occurrence and explanatory variables were also found. Such misleading inferences would likely have deleterious implications for conservation and management programs. We contend that all forms of observation error, including false positive errors and heterogeneous detection probabilities, must be incorporated into the estimation framework to facilitate reliable inferences about occupancy and its associated vital rate parameters.

Modeling species occurrence dynamics with multiple states and imperfect detection

Recent extensions of occupancy modeling have focused not only on the distribution of species over space, but also on additional state variables (e.g., reproducing or not, with or without disease organisms, relative abundance categories) that provide extra information about occupied sites. These biologist-driven extensions are characterized by ambiguity in both species presence and correct state classification, caused by imperfect detection. We first show the relationships between independently published approaches to the modeling of multistate occupancy. We then extend the pattern-based modeling to the case of sampling over multiple seasons or years in order to estimate state transition probabilities associated with system dynamics. The methodology and its potential for addressing relevant ecological questions are demonstrated using both maximum likelihood (occupancy and successful reproduction dynamics of California Spotted Owl) and Markov chain Monte Carlo estimation approaches (changes in relative abundance of green frogs in Maryland). Just as multistate capture-recapture modeling has revolutionized the study of individual marked animals, we believe that multistate occupancy modeling will dramatically increase our ability to address interesting questions about ecological processes underlying population-level dynamics.

Occupancy Estimation and Modeling. Inferring patterns and dynamics of species occurrence

Occupancy Estimation and Modeling. Inferring patterns and dynamics of species occurrence