Assessing the impacts of imperfect detection on estimates of diversity and community structure through multispecies occupancy modeling

Detecting all species in a given survey is challenging, regardless of sampling effort. This issue, more commonly known as imperfect detection, can have negative impacts on data quality and interpretation, most notably leading to false absences for rare or difficult‐to‐detect species. It is important that this issue be addressed, as estimates of species richness are critical to many areas of ecological research and management. In this study, we set out to determine the impacts of imperfect detection, and decisions about thresholds for inclusion in occupancy, on estimates of species richness and community structure. We collected data from a stream fish assemblage in Algonquin Provincial Park to be used as a representation of ecological communities. We then used multispecies occupancy modeling to estimate species‐specific occurrence probabilities while accounting for imperfect detection, thus creating a more informed dataset. This dataset was then compared to the original to see where differences occurred. In our analyses, we demonstrated that imperfect detection can lead to large changes in estimates of species richness at the site level and summarized differences in the community structure and sampling locations, represented through correspondence analyses.     

Fire,landscape change and models of small mammal habitat suitability at multiple spatial scales

Fire is an important process in many ecosystems, but inappropriate fire regimes can adversely affect biodiversity. We identified a naturally flammable heathy woodland ecosystem where the use of planned fire had increased the extent of older vegetation, and quantified the abundance of two small native mammals in this landscape (silky mouse Pseudomys apodemoides and heath rat P. shortridgei). We defined four time‐since‐fire (TSF) categories representing a 2‐ to 55‐year post‐fire sequence and, on the basis of a habitat accommodation model, predicted that both species would select younger age‐classes over older ones. We also predicted that (i) much of the variance in vegetation structure would remain unexplained by TSF and (ii) statistical models of mammal abundance and occupancy including structural variables as predictors would be better than models including TSF. Pseudomys apodemoides selected 17‐ to 23‐year‐old sites, while there was no evidence that P. shortridgei selected a particular TSF category, findings that were inconsistent with our predictions. In line with our predictions, relatively large portions of the variance in vegetation structure remained unexplained by TSF (adjustedr² for four structural variables: 0.24, 0.29, 0.35 and 0.57), and in three of four cases there was strong evidence that statistical models of mammal abundance and occupancy including structural variables were better than those including TSF. At the site scale (hectares), P. shortridgei abundance was positively related to the cover of dead material at the base of Xanthorrhoea plants and at the trap scale (metres), the trapability of both species was significantly related to vegetation volume at 0–20 cm. Our findings suggest that TSF may not be a good proxy for either vegetation structure or species abundance/occupancy.     

The importance of spatial scale in habitat selection by European beaver

We evaluated habitat selection by European beaver Castor fiber L. across a spatial gradient from local (within the family territory) to a broad, ecoregional scale. Based on aerial photography, we assessed the habitat composition of 150 beaver territories along the main water bodies of the Vistula River delta (northern Poland) and compared these data with 183 randomly selected sites not occupied by the species. The beavers preferred habitats with high availability of woody plants, including shrubs, and avoided anthropogenically modified habitats, such as arable lands. Within a single family territory, we observed decreasing woody plant cover with increasing distance from a colony centre, which suggests that beaver habitat preferences depend on the assessment of both the abundance and spatial distribution of preferred habitat elements. We tested the importance of spatial scale in beaver habitat selection with principal coordinates of neighbour matrices analysis, which showed that the geographical scale explained 46.7% of the variation in habitat composition, while the local beaver density explained only 10.3% of this variability. We found two main spatial gradients that were related to the broad spatial scale: first, the most important gradient was related to the largest distances between beaver sites and was independent of woody plant cover and the local beaver site density. The second most important gradient appeared more locally and was associated with these variables. Our results indicate that European beaver habitat selection was affected by different scale‐related phenomena related 1) to central place foraging behaviour, which resulted in the clumped distribution of woody plants within the territory, and 2) local population density and woody plant cover. Finally, 3) habitat selection occurs independently across the largest spatial scale studied (e.g. between watersheds), which was probably due to the limited natal dispersal range of the animals.     

Habitat selection of breeding riparian birds in an urban environment: untangling the relative importance of biophysical elements and spatial scale

Aim Urbanization is a leading threat to global biodiversity, yet little is known about how the spatial arrangement and composition of biophysical elements – buildings and vegetation – within a metropolitan area influence habitat selection. Here, we ask: what is the relative importance of the structure and composition of these elements on bird species across multiple spatial scales? Location The temperate metropolitan area of Cincinnati, Ohio, USA. Methods We surveyed breeding birds on 71 plots along an urban gradient. We modelled relative density for 48 bird species in relation to local woody vegetation composition and structure and to tree cover, grass cover and building density within 50–1000 m of each plot. We used an information‐theoretic approach to compare models and variables. Results At the proximate scale, native tree and understory stem frequency were the most important vegetation variables explaining bird distributions. Species’ responses to landscape biophysical features and spatial scales varied. Most native species responded positively to vegetation measures and negatively to building density. Models combining both local vegetation and landscape information represented best or competitive models for the majority of species, while models containing only local vegetation characteristics were rarely competitive. Smaller spatial scales (≤ 500 m) were most important for 36 species, and eight species had best models at larger scales (> 500 m); however, several species had competitive models across multiple scales. Main conclusions Habitat selection by birds within the urban matrix is the result of a combination of factors operating at both proximate and broader spatial scales. Efforts to manage and design urban areas to benefit native birds require both fine‐scale (e.g., individual landowners and landscape design) and larger landscape actions (e.g., regional comprehensive planning).     

Functional spatial scale of community composition change in response to windthrow disturbance in a deciduous temperate forest

Community dynamics in local habitats are affected by landscape characteristics such as the area and connectivity of surrounding habitats at a functional spatial scale where the community responds to landscape structure. However, the functional spatial scale at which community composition is affected by landscape structure has never been explored. We assessed the functional spatial scales of composition change in birds and in three types of arthropod communities (canopy, forest-floor and flying ones) with regard to landscape heterogeneity resulting from a large typhoon in a temperate forest of Japan. We examined the effects of tree-fall disturbance on the communities at various spatial scales, with special attention to compositional evenness. The spatial scale of the best-fitting model, which was selected from models fitted to the disturbance area at stepwise spatial scales, was interpreted as the community-specific functional spatial scale. The composition of all communities studied was all significantly dependent on gap area. The functional spatial scale was highest in birds (370 m in radius), intermediate in flying arthropods (90 m) and lowest in canopy and forest-floor arthropods (10 m). This result may reflect typical dispersal ability and the spatial range of resource use in the community. Compositional changes in each community were consistent with theory regarding traits and responses of component taxa, although the enhancement of evenness was observed only in the arthropod communities. These results imply that management and reserve selection based on functional spatial scales can be effective in the conservation of biodiversity and ecosystem services at the community level.     

The importance of incorporating imperfect detection in biodiversity assessments: a case study of small mammals in an Australian region

Aim Assessments of biodiversity are an essential requirement of conservation management planning. Species distributional modelling is a popular approach to quantifying biodiversity whereby occurrence data are related to environmental covariates. An important confounding factor that is often overlooked in the development of such models is uncertainty due to imperfect detection. Here, I demonstrate how an analytical approach that accounts for the bias due to imperfect detection can be applied retrospectively to an existing biodiversity survey data set to produce more realistic estimates of species distributions and unbiased covariate relationships. Location Pilbara biogeographic region, Australia. Methods As a component of the Pilbara survey, presence/absence (i.e. undetected) data on small ground‐dwelling mammals were collected. I applied a multiseason occupancy modelling approach to six of the most common species encountered during this survey. Detection and occupancy rates, as well as extinction and colonization probabilities, were determined, and the influence of covariates on these parameters was examined using the multi‐model inference approach. Results Detection probabilities for all six species were considerably lower than 1.0 and varied across time and species. Naïve estimates of occupancy underestimated occupancy rates corrected for species detectability by up to 45%. Seasonal variation in occupancy status was attributed to changes in detection for two of the focal species, while reproductive events explained variation in occupancy in three others. Covariates describing the substrate strongly influenced site occupancy for most of the species modelled. A comparison of the occupancy model with a generalized linear model, assuming perfect detection, showed that the effects of the covariates were underestimated in the latter model. Main conclusions The application of the multiseason occupancy modelling approach to the Pilbara mammal data set demonstrated a powerful framework for examining changes in site occupancy, as well as local colonization and extinction rates of species which are not confounded by variable species detection rates.     

Guidelines for a priori grouping of species in hierarchical community models

Recent methodological advances permit the estimation of species richness and occurrences for rare species by linking species‐level occurrence models at the community level. The value of such methods is underscored by the ability to examine the influence of landscape heterogeneity on species assemblages at large spatial scales. A salient advantage of community‐level approaches is that parameter estimates for data‐poor species are more precise as the estimation process “borrows” from data‐rich species. However, this analytical benefit raises a question about the degree to which inferences are dependent on the implicit assumption of relatedness among species. Here, we assess the sensitivity of community/group‐level metrics, and individual‐level species inferences given various classification schemes for grouping species assemblages using multispecies occurrence models. We explore the implications of these groupings on parameter estimates for avian communities in two ecosystems: tropical forests in Puerto Rico and temperate forests in northeastern United States. We report on the classification performance and extent of variability in occurrence probabilities and species richness estimates that can be observed depending on the classification scheme used. We found estimates of species richness to be most precise and to have the best predictive performance when all of the data were grouped at a single community level. Community/group‐level parameters appear to be heavily influenced by the grouping criteria, but were not driven strictly by total number of detections for species. We found different grouping schemes can provide an opportunity to identify unique assemblage responses that would not have been found if all of the species were analyzed together. We suggest three guidelines: (1) classification schemes should be determined based on study objectives; (2) model selection should be used to quantitatively compare different classification approaches; and (3) sensitivity of results to different classification approaches should be assessed. These guidelines should help researchers apply hierarchical community models in the most effective manner.     

Freshwater fishes of the Burdekin River, Australia: biogeography, history and spatial variation in community structure

Spatial variation in freshwater fish community structure in a large, structurally monotonous sub-tropical Australian river over 1989–1992 is described. The number of species collected (25) over the period of study, was low, given the large size of the river's catchment. The low diversity of fishes present in the river was suggested to be due to a combination of factors including the imposition of an ancient downstream barrier to fish movement (the Burdekin Falls), substantial volcanic activity during the late Tertiary, past climatic stress and little variation in habitat structure over the range of sites examined. Notwithstanding the low species richness, the Burdekin River's freshwater fish fauna is distinctive, containing elements of the fauna of both eastern and northern Australia, and this was suggested to reflect aspects of ancient landscape evolution. Spatial variation in fish community structure was most strongly influenced by the presence of the Burdekin Falls (the present site of a very large reservoir) and secondarily by minor differences in habitat structure of main channel and tributary streams.     

Predicting changes in the abundance of African wetland birds by incorporating abundance–occupancy relationships into habitat association models

Aim To map changes in the abundance of African wetland birds using remotely derived habitat data. We show that abundance–occupancy relationships can be coupled with habitat association models to map changes in abundance. As conservation resources are more easily allocated when spatial and temporal patterns of abundance are known, our method provides guidance for conservation planning. Location Papyrus, Cyperus papyrus, swamps in east central Africa. Methods Presence/absence surveys of six bird species in 93 wetlands were used to construct models predicting probability of occurrence from habitat characteristics. Densities were then determined from surveys in 23 additional wetlands and modelled as functions of occurrence probability. We then used satellite imagery to derive habitat characteristics remotely in two time periods (1984–87 and 2000–03) and used the modelled relationships between (1) habitat and occupancy and (2) occupancy and density, to infer changes in abundance in all c. 30,000 wetlands within the study area. Results Wetlands within the region declined by 8.6% between the two time periods, but by > 75% in regions of high human population density. Bird densities were also highest in these regions, which comprised wetlands subject to high levels of disturbance. The geographical coincidence of high densities and habitat loss and the existence of positive associations between bird density and occurrence meant that birds declined by much more than the average rate of their habitat. Main conclusions Targeting conservation efforts in areas with high drainage would protect a high proportion of the bird populations. Encouraging people to derive income from disturbance to which the birds are tolerant, rather than drainage, is likely to be an effective strategy. Because habitat characteristics are a key driver of abundance–occupancy relationships, we conclude that there is wide‐scale scope to couple abundance–occupancy relationships with remote habitat mapping to efficiently inform conservation planning.     

The problem and promise of scale in multilayer animal social networks

Scale remains a foundational concept in ecology.Spatial scale,for instance,has become a central consideration in the way we understand landscape ecology and animal space use.Meanwhile,scale-dependent social processes can range from fine scale interactions to co-occurrence and overlapping home ranges.Furthermore,sociality can vary within and across seasons.Multilayer networks promise the explicit integration of the social,spatial,and temporal contexts.Given the complex interplay of sociality and animal space use in heterogeneous landscapes,there remains an important gap in our understanding of the influence of scale on animal social networks.Using an empirical case study,we discuss ways of considering social,spatial,and temporal scale in the context of multilayer caribou social networks.Effective integration of social and spatial processes,including biologically meaningful scales,within the context of animal social networks is an emerging area of research.We incorporate perspectives that link the social environment to spatial processes across scales in a multilayer context.     

Sharing detection heterogeneity information among species in community models of occupancy and abundance can strengthen inference

1. The estimation of abundance and distribution and factors governing patterns in these parameters is central to the field of ecology. The continued development of hierarchical models that best utilize available information to inform these processes is a key goal of quantitative ecologists. However, much remains to be learned about simultaneously modeling true abundance, presence, and trajectories of ecological communities.
2. Simultaneous modeling of the population dynamics of multiple species provides an interesting mechanism to examine patterns in community processes and, as we emphasize herein, to improve species‐specific estimates by leveraging detection information among species. Here, we demonstrate a simple but effective approach to share information about observation parameters among species in hierarchical community abundance and occupancy models, where we use shared random effects among species to account for spatiotemporal heterogeneity in detection probability.
3. We demonstrate the efficacy of our modeling approach using simulated abundance data, where we recover well our simulated parameters using N‐mixture models. Our approach substantially increases precision in estimates of abundance compared with models that do not share detection information among species. We then expand this model and apply it to repeated detection/non‐detection data collected on six species of tits (Paridae) breeding at 119 1 km² sampling sites across a P. montanus hybrid zone in northern Switzerland (2004–2020). We find strong impacts of forest cover and elevation on population persistence and colonization in all species. We also demonstrate evidence for interspecific competition on population persistence and colonization probabilities, where the presence of marsh tits reduces population persistence and colonization probability of sympatric willow tits, potentially decreasing gene flow among willow tit subspecies.
4. While conceptually simple, our results have important implications for the future modeling of population abundance, colonization, persistence, and trajectories in community frameworks. We suggest potential extensions of our modeling in this paper and discuss how leveraging data from multiple species can improve model performance and sharpen ecological inference.

     

Estimating species' absence, colonization and local extinction in patchy landscapes: an application of occupancy models with rodents

Making an inference on the absence of a species in a site is often problematic, due to detection probability being, in most cases, <1. Inference is more complicated if detection probability, together with distribution patterns, vary during the year, since the possibility of inferring a species absence, at reasonable costs, may be possible only in certain periods. Our aim here is to show how such challenging situations can be by tackled by applying some recently developed occupancy models combined with sample size (number of repeated surveys) estimation. We thus analysed the distribution of two rodents Myodes glareolus and Mus musculus domesticus in a fragmented landscape in central Italy pointing out how it is possible to identify true absences, non-detections, extinctions/colonizations and determine seasonal values of detection probability.     

Shifts in the community composition of caddisflies (Insecta: Trichoptera) in a subtropical river over three decades

1. Trichoptera is an ecologically and taxonomically diverse order, and caddisfly species are under increasing pressure from anthropogenic threats to larval habitats, rivers, and streams. 2. This study evaluated long-term changes in caddisfly communities of the Ogeechee River, a subtropical blackwater river in the south-eastern U.S. Coastal Plain, to understand how changes manifest as a result of ongoing human impacts. Two datasets separated by more than 30 years were used, each representing a 2-year monthly quantitative sampling effort (1981–1983; 2015–2017). 3. Community structure of the Ogeechee River caddisflies significantly changed, though not in ways that were predicted. The average sensitivity values of the caddisfly community declined, contrary to the expectation that increasing human impacts on a river ecosystem would promote the survival of more pollution-tolerant taxa. 4. Generic richness increased in the 2010s from the 1980s, perhaps as a result of relaxed competition following declines of large, dominant taxa. The increases in various taxa have resulted in similar overall abundance metrics between time periods, although other studies of Ogeechee River invertebrates indicate that the biomass of the new taxa is far lower than that produced by the assemblages of the 1980s. Functional richness, evenness, and dispersion were higher in the 2010s, but divergence was not. 5. This suggests that more nuanced monitoring efforts, focused on the threats to ecological function and the role of caddisflies (and other sensitive freshwater organisms), will be required to evaluate the changes in community structure and determine which taxa are most adversely affected.     

Directional growth of a clonal bromeliad species in response to spatial habitat heterogeneity

Habitat selection by directional growth of plants has previously been investigated but field evidence for this phenomenon is extremely scarce. In this study we demonstrate directional clonal growth in Aechmea nudicaulis, a monocarpic, perennial bromeliad native to spatially heterogeneous sandy coastal plains (restinga) in Brazil. This habitat is characterized by a matrix of bare sand with interspersed vegetation islands. Due to very high soil surface temperatures and other stress factors such as drought, A. nudicauliscan only germinate inside vegetation islands. Nevertheless, this species is very common on bare sand. In this study we tested the hypothesis that clonal fragments occurring at the border and inside vegetation islands show habitat selection by growing preferentially towards the bare sand habitat (i.e. away from the center of vegetation islands).We randomly chose 116 clonal fragments in two distinct micro-environments (inside vegetation islands, and in the border area between bare sand and vegetation islands) in the natural habitat of A.nudicaulisand measured their growth direction in relation to the island center. We measured the growth directions of entire clonal fragments (defined as the line that connects the oldest and the youngest ramets of a clonal fragment) as well as the growth direction of the youngest internode on each fragment (the growth direction of the youngest ramet in relation to its parent ramet). We used Monte Carlo simulations to test for deviations from randomness in the growth direction of clonal fragments and individual internodes. The clonal fragments of A.nudicaulis showed a significant tendency to grow away from the center of vegetation islands. In other words, the main growth direction of clonal fragments growing inside vegetation islands or at the border between bare sand and vegetation islands was preferentially directed towards bare sand environments. Individual internodes at the border of vegetation islands also exhibited this tendency to grow towards the outside of vegetation islands, but internodes growing inside vegetation islands did not show directional growth. These results provide the first field evidence for habitat selection through directional growth of a clonal plant species.Co-ordinationg editor: J. Tuomi     

Environment is more relevant than spatial structure as a driver of regional variation in tropical tree community richness and composition

Background: Understanding how factors related to environment and geographical distance explain community variation allows insights about how ecological niche and neutral processes control tropical community assembly.

Aims: Quantify how variation in regional tree community richness and composition in a humid tropical forest across a mountain chain are related to niche and putative neutral processes.

Methods: We used a variation partitioning routine based on Redundancy Analysis to model tropical tree community richness and composition within three distinct elevation belts, as a function of environment and spatial structure, using data from 32 studies in the Serra do Mar Range, south-eastern Brazil.

Results: Environmental effects were greater than spatial structure effects to explain community variation in the three elevation belts. There was a trend of decreasing spatial structure effects while environmental effects remained constant from lower to higher elevations. Patterns were congruent for species richness and composition.

Conclusions: We suggest that on tropical mountains, niche-related processes are equally relevant for tropical forest community assembly at all elevations, while neutral processes become weaker towards higher elevations. Determining if this trend is a consequence of the greater heterogeneity of environmental conditions associated with higher elevations in tropical mountainous terrain remains an important area of research.