Occupancy Models Research Articles

Occupancy modeling on non-intrusive indoor environmental data through machine learning

The primary drivers of energy consumption within buildings are the occupants. Non-intrusive Internet of Things (IoT) technology can be utilized to detect occupancy and optimize energy performance while preserving the privacy of building occupants. This study explores the suitability of various indoor environmental data for occupancy detection in office rooms. Data was collected utilizing an IoT sensory device, recording CO2 concentration, air temperature, relative humidity, indoor air quality, sound pressure level, and illuminance in two double-occupied office rooms at a campus building in Munich, Germany. Machine learning models, namely Random Forest, XGBoost, and dense neural networks were trained on the dataset, and the models’ feature importance was analyzed through post-hoc explainability testing. The best features were then incorporated in a sliding window of 15 min to consider temporal dependencies in the models. The study also compared two hyperparameter optimization techniques: Random and Bayesian optimization.The results of this study indicate that with six days of ground truth data of sound pressure level, CO2, and illuminance, accuracy and F1-score for occupancy detection of above 0.95 and 0.93 can be respectively achieved.

Evaluating the context dependency of large river nursery habitats for fishes in the lower Red River catchment

AbstractBoth fine‐ and coarse‐scale physicochemical conditions affect the quantity and quality of nursery habitats within riverine ecosystems. Nursery habitats in large, braided, and sandbed streams such as the lower Red River of Oklahoma, Texas, and Arkansas are not well described and likely vary among species. Identification of nursery habitats is important for developing proper conservation and management actions. We used an occupancy model framework to determine how hierarchical habitat factors related to the occupancy of 38 juvenile fish species. Our findings indicate that large river nursery habitats can generally be defined by reaches with off‐channel slackwater habitat, having deep pools but shallow thalweg depths, typically located further away from dams, and with low percentages of limestone lithology. Species within the same genera often exhibited variable relationships with river slope, amount of large woody debris, channel shape, discharge, and position of reaches within the stream network. Our results indicate important species‐specific relationships that define nursery habitats, indicating an important context dependency of nursery habitats even within fishes that are taxonomically similar. If the goal is to improve recruitment by native fishes, then consideration of the important species‐specific differences would be beneficial if improvements are made to nursery habitats. Moreover, careful consideration of the effects of dam operations will help maintain proper connectivity to off‐channel habitats important in downriver portions of the river network.

Broadening applications of stochastic patch occupancy models over three decades

AbstractAimStochastic patch occupancy models (SPOMs) are a type of spatial population simulation. They are arguably well‐suited to guide conservation in human‐altered landscapes, but their appropriateness for a wide range of species and landscape types has often been questioned. Here, we provide an overview of how SPOM research has expanded over the last three decades and discuss the untapped potential for these models to inform current conservation strategies.LocationWorldwide.MethodsWe carried out a systematic review of studies that have fitted SPOMs to real species and landscapes. We assessed temporal trends in SPOMs' use in conservation and management studies, their taxonomic and geographic coverage, and the attributes of studied landscapes. We quantitatively and qualitatively evaluated whether the authors' modelling choices reflected the perceived advantages and disadvantages of SPOMs.ResultsThe proportion of SPOMs used to answer conservation questions has increased over time. Questions of where, when and how to conserve have all been addressed, sometimes considering additional aspects such as cost‐effectiveness and climate change. Taxonomic diversity coverage has increased over time, and SPOMs have been used in landscapes with a higher proportion of suitable habitat. They have, however, been predominantly applied in temperate biomes. Few studies have explored parameter extrapolation in taxonomically and ecologically related species with mixed results.Main ConclusionsOver the past three decades, authors have exploited the simplicity and flexibility of SPOMs to answer a broad range of questions with practical implications. The use of SPOMs in less fragmented landscapes, and for an increasing range of taxa, suggests that the strictest definitions of their applicability can be challenged. Stochastic patch occupancy models have untapped potential for informing conservation under climate change. Given the urgent need to plan for large numbers of species with limited data for fitting, SPOMs could better fulfil their potential to guide conservation if parameters could be extrapolated to data‐deficient landscapes and species.

Coupled occupant-suspension-seat system analysis and vehicle-specific design optimization

A suspension seat is generally designed to achieve attenuation of low frequency whole-body vibration for a broad range of vehicles. Owing to the strong dependence of its vibration isolation performance on the nature of vibration excitation, an optimal performance could be realized via optimal tuning of suspension for specific classes of vehicles. In this study, a coupled occupant suspension seat model is developed and analyzed to identify optimal design parameters for different classes of vehicles. The multibody dynamic model of the air suspension seat is formulated considering kineto-dynamics of the suspension system and the elastic motion-limiters. The component models, namely, air spring with auxiliary air volume, hydraulic damper, and cushion, are identified from the laboratory-measured static and dynamic characteristics. A two-degree-of-freedom occupant model, is integrated to the suspension seat model to account for contribution due to occupant biodynamics. Model validity is examined using the laboratory-measured responses with a rigid load and a human occupant of similar body weight, and analyzed for different body weights and excitation spectra. The results suggest strong dependency of the suspension resonance frequency on nonlinear behavior of the air spring and the seated body mass. The model is subsequently employed to identify optimal coordinates of the air spring to achieve nearly constant natural frequency for a broad range of body masses. Furthermore, the model is used to identify optimal linkage and suspension design parameters with an objective to minimize the SEAT (Seat Effective Amplitude Transmissibility) for different spectral classes of earth moving machines defined in the ISO-7096 standard, while limiting the suspension travel. It is shown that the optimal coordinates of air spring could yield nearly constant natural frequency for different body weights, while damper could help limit the suspension travel, in addition to notable reductions in SEAT, ranging from 9% to 31% for different spectral classes of vehicles.

Intriguing Occupations at Gran Dolina (Atapuerca, Spain): the Acheulean Subunits TD10.3 and TD10.4

This paper presents the zooarchaeological, technological, use-wear, and spatial analyses of the earliest sedimentary subunits of TD10 (TD10.3 and TD10.4) of the Gran Dolina site (Sierra de Atapuerca, Burgos, Spain), dated to c. 400 ka. Both units have yielded Acheulean technology, with occupational models characterized by the superimposition of multiple and independent events paired with short, sporadic occupations. Subunits TD10.3 and TD10.4 formed during a period in which the cave was largely reopened after a temporary closure. This period of reopening is evidenced by several blocks that fell from the ceiling and walls. Fifty-seven groups of refits and anthropic conjoins, of which 43 resulted from deliberate hominin activity, confirm the low disturbance of the deposits. Contrary to TD10.4, TD10.3 shows good preservation of faunal remains, although anthropogenic modifications are very scarce. Technologically, both deposits represent well-developed Acheulean assemblages, with high proportions of large-shaped tools and percussive material, which place this area among those that have yielded the most evidence of this type among all the excavated Atapuerca sites. The question of why these subunits contain so many hammerstones, manuports, and large tools associated with faunal remains that have been so scarcely modified is discussed based on data from spatial, technical, and use-wear analyses, which have identified butchery activities, and for the first time in the Pleistocene Atapuerca record, borer elements and possible thrusting stone spear tips. Furthermore, the occupational and technological characteristics of these subunits were compared with other western European archaeological sites, including the nearby site of Galería, with which a broad correlation can be made.

Occupancy model reveals limited detectability of lichens in a standardised large‐scale monitoring

AbstractQuestionWhat are the extent and the possible causes of imperfect detection in lichens? Because lichens are sessile and lack seasonality, they should be easier to survey than animals that can move or plants and fungi with seasonal morphology, and one could therefore expect relatively high detection probabilities.Location826 standardised sampling plots across Switzerland.MethodsUsing repeated detection/non‐detection data from a national lichen survey conducted by professional lichenologists, we estimated the mean and variation in detectability for 373 tree‐living species with a multi‐species occupancy model. We also quantified the effect of species conspicuousness, identifiability and observer experience on detection probability.ResultsThe average detection probability for a single survey was unexpectedly low with an average of 0.49 (range across species: 0.25–0.74). Conspicuous species showed higher average detectability (0.56) than inconspicuous species (0.41), and identifiability as well as previous experience with a species substantially increased the probability of a person detecting it. Accounting for experience, the mean detection probabilities of observers ranged from 0.32 to 0.69.ConclusionsOur study confirms that detection probability per survey is often far below 1 also in sessile organisms, even when a standardised survey is conducted by experts. When species are seasonal (plants, fungi, etc.), survey areas are larger, or field personnel are less experienced, as is the case for many surveys and monitoring programs, detectabilities are likely to be substantially lower. We therefore argue that imperfect detection should systematically be considered in the survey design and data analysis also for sessile organisms.

Population pharmacokinetics, enzyme occupancy, and pharmacodynamic modeling of soticlestat in patients with developmental and epileptic encephalopathies.

Soticlestat (TAK-935) is a first-in-class, selective inhibitor of cholesterol 24-hydroxylase (CH24H) under phase III development for the treatment of the developmental and epileptic encephalopathies (DEEs), Dravet syndrome (DS), and Lennox-Gastaut syndrome (LGS). A previous model characterized the pharmacokinetics (PKs), CH24H enzyme occupancy (EO), and pharmacodynamics (PDs) of soticlestat in healthy volunteers. The present study extended this original model for patients with DEEs and investigated sources of variability. Model-based simulations were carried out to optimize dosing strategies for use in clinical trials. Data from eight phase I and II trials of healthy volunteers or patients with DEEs receiving oral soticlestat 15-1350 mg were included, encompassing 218 individuals for population PK (PopPK) analyses and 306 individuals for PK/PD analyses. Dosing strategies were identified through model-based simulations. The final mixed-effect PopPK/EO/PD model consisted of a two-compartment PK model and an effect-site compartment in the PK/EO model; soticlestat concentrations at the effect site were linked to 24S-hydroxycholesterol plasma concentrations using a semimechanistic inhibitory indirect response model. Covariates were included to account for sources of variability. Pediatric dosing strategies were developed for four body weight bands (10 to <15, 15 to <30, 30 to <45, and 45-100 kg) to account for covariate effects by body weight. The final PopPK and PK/EO/PD models accurately described PK, EO, and PD profiles of soticlestat in healthy volunteers and patients with DEEs. Covariate analyses and model-based simulations facilitated optimization of phase III trial dosing strategies for patients with DS or LGS.

Exploring occupant detection model generalizability for residential buildings using supervised learning with IEQ sensors

This study explores two modeling approaches for occupancy detection at room level for residential buildings in Denmark. The aim is to assess the performance and generalizability of occupant detection models using XGBoost method trained on a rich dataset comprising indoor environmental quality (IEQ) variables and occupancy ground truth. A global approach (all rooms) and a room-specific approach are considered. After a thorough feature- selection and importance analysis process, the occupancy detection models (ODMs) are trained and tested in a nested cross-validation schema. The time of the day, indoor CO2 concentration, and feature transforms related to short-term IEQ dynamics were found to be the most important features of the ODMs. Both the global and room-specific models show good occupancy prediction performance, especially for bedrooms. When tested for generalizability with an unseen dataset from a different residential building, the ODMs maintain very good performance for the bedroom but not for the office room. This discrepancy could be explained by significant differences in occupancy and ventilation patterns, and large air infiltration from adjacent rooms. Although currently limited in terms of generalizability, XGBoost-based ODMs using IEQ data have the potential to provide robust and scalable occupancy detection for occupant-centric control and occupant-aware building performance assessments. The IEQ dataset with occupancy ground truth collected for this study is made available in open access.

Local floral abundance influences bumble bee occupancy more than urban‐agricultural landscape context

Abstract Loss of natural habitat due to increases in agricultural extent raises the question of whether human‐dominated landscape types can support biodiversity, particularly for declining insect pollinators. Compared to more rural agricultural landscapes, urban areas may confer benefits for bumble bee populations by providing stable and diverse floral resources. However, disentangling the effects of local‐ and landscape‐scale characteristics on bumble bee populations in human‐modified landscapes is challenging. Here, we assessed bumble bee occupancy using a repeated transect sampling design conducted during the summers of 2019 and 2020 within the metropolitan area of Madison, WI, and the surrounding agricultural landscape. We fit hierarchical occupancy models to estimate the detection (p) and occupancy () probabilities relative to local habitat quality (floral abundance and floral richness) and landscape (agricultural‐urban gradient) features for eight bumble bee species. We hypothesised that bumble bees were more likely to occupy urban areas, serving as refugia, relative to agricultural sites. We found that the detection probability of all bumble bee species was seasonal and influenced by maximum floral abundance at survey sites, independent of the surrounding land cover type. After accounting for species‐specific detection probabilities, the effect of urbanisation on bee occupancy was weak, and no species were less likely to occupy urban than rural agricultural areas. Our findings suggest that bumble bee occupancy is associated with a ‘honeypot effect’ where local resource availability, in the form of higher floral abundance, is most important in limiting the occupancy of bumble bees across urban and agricultural landscapes.

Camera traps reveal seasonal variation in activity and occupancy of the Alpine mountain hare Lepus timidus varronis

Mountain hare is a cold‐adapted species threatened by climate change, but despite its emblematic nature, our understanding of the causes of population decline remains limited. Camera traps are increasingly used in ecology as a tool for monitoring animal populations at large spatial and temporal scales. In mountain environments where field work is constrained by difficult access and harsh conditions, camera traps constitute a promising tool for surveying rare and elusive species such as the mountain hare. Our study explored the use of camera traps as a tool for studying seasonal habitat occupancy and daily activity patterns of the mountain hare, in order to carry out long‐term monitoring of populations. We installed 46 camera traps along elevation gradients in the Mont‐Blanc massif (France) from January 2018 to June 2022. We measured habitat variables at each camera trap site in order to define vegetation composition and habitat structure. We performed multi‐season and single‐season occupancy models to respectively describe habitat occupancy of the mountain hare throughout the year and identify the environmental variables influencing mountain hare presence during the breeding season. Mountain hares occupy coniferous forest in winter, and then switch to mixed areas of shrubland and grassland above treeline in spring and the beginning of summer. In spring, occupancy probability of the mountain hare increases with relative cover of mixed low shrub and herbaceous layer (i.e. the 10–40 cm vegetation layer), suggesting a link to food resources and protection from predation. Our results also confirm the nocturnal and crepuscular activity of the mountain hare during the breeding season, and strictly nocturnal activity in winter. Our results demonstrate the efficiency of camera traps as tools for monitoring mountain hare habitat occupancy in mountain environments and underline the importance of diverse habitat mosaics for the preservation of the species.

White-tailed deer detection rates increase when coyotes are present.

Predator species can indirectly affect prey species through the cost of anti-predator behavior responses, which may involve shifts in occupancy, space use, or movement. Quantifying the various strategies implemented by prey species to avoid adverse interactions with predators can lead to a better understanding of potential population-level repercussions. Therefore, the purpose of this study was to examine predator-prey interactions by quantifying the effect of predator species presence on detection rates of prey species, using coyotes (Canis latrans) and white-tailed deer (Odocoileus virginianus) in Central Appalachian forests of the eastern United States as a model predator-prey system. To test two competing hypotheses related to interspecific interactions, we modeled species detections from 319 camera traps with a two-species occupancy model that incorporated a continuous-time detection process. We found that white-tailed deer occupancy was independent of coyote occupancy, but white-tailed deer were more frequently detectable and had greater detection intensity at sites where coyotes were present, regardless of vegetation-related covariates. In addition, white-tailed deer detection rates at sites with coyotes were highest when presumed forage availability was relatively low. These findings suggest that white-tailed deer may be exhibiting an active avoidance behavioral response to predators by increasing movement rates when coyotes are present in an area, perhaps due to reactive evasive maneuvers and/or proactive attempts to reduce adverse encounters with them. Concurrently, coyotes could be occupying sites with higher white-tailed deer densities. Because white-tailed deer did not exhibit significant shifts in daily activity patterns based on coyote occupancy, we further suggest that white-tailed deer in our study system generally do not use temporal partitioning as their primary strategy for avoiding encounters with coyotes. Overall, our study implements a recently developed analytical approach for modeling multi-species occupancy from camera traps and provides novel ecological insight into the complex relationships between predator and prey species.

Precipitation explains Wood Thrush (Hylocichla mustelina) occupancy patterns in Northern Costa Rica

Introduction: The Wood Thrush is a migratory bird that has experienced dramatic declines in its populations in recent decades. This species overwinters in forest fragments with intermediate levels of habitat modification in Central America. However, more studies detailing the use of remnant forests through time are needed to elucidate the threats this species faces in the wintering grounds. Objective: To understand the effects of environmental and forest structure variables on the occupancy of Wood Thrush in Northern Costa Rica. Methods: The study area was the Área de Conservación Guanacaste (ACG), located in Northern Costa Rica, in December 2016, and during the 2018-2019 migration season. We estimated Wood Thrush occupancy and detection probability in four locations of ACG (dry forest, cloud forest, and two locations in the wet forest) using single-season occupancy models. We also estimated Wood Thrush occupancy and probability of persistence in different months in three vegetation types (open area, secondary forest, and old-growth forest) in the wet forest of ACG using a multi-season occupancy model approach. Results: Wood Thrush occupancy was best described by precipitation in the four locations of the ACG; the probability of occupancy increased with precipitation. The average occupancy of Wood Thrushes varied with vegetation type: open area with shrubs and forest edge (0.69 ± 0.09), secondary forest (0.46 ± 0.1), and old-growth forest (0.61 ± 0.1). Wood Thrush probability of persistence responded partially to changes in precipitation, with an unexpected increase in persistence when the rainfall continued decreasing in the season. Conclusion: Wood Thrush occupancy was best predicted by changes in precipitation considering a larger spatial scale. Its probability of persistence partially varied with precipitation. An increase in persistence closer to Spring migration might be explained by the start of the breeding season of resident birds, potentially reducing territorial conflicts and conserving energy before migration. The long-term protection of wet forests in Northern Costa Rica is of paramount importance for the conservation of Wood Thrushes in their wintering grounds.

Some like it burnt: species differences in small mammal assemblage in a Mediterranean basin nearly 3 years after a major fire

The habitat accommodation model (HAM) is a theoretical framework that predicts wildlife community recovery based on their habitat requirements. While post-fire habitat-related research is well documented in the Mediterranean basin, studies specifically focusing on HAM are scarce. Here, we described the small mammal assemblage in a Mediterranean area ~3 years after a fire, specifically examining three functional small mammalian categories: ground-foraging insectivorous, ground-foraging herbivorous/granivorous, and arboreal-foraging species. The study was conducted in Monte Pisano (Italy), where fire burnt ~12 km2 in September 2018. A stratified random sampling was adopted, basing on burnt status and forest type. In each of the 50 sites, during late spring-summer 2021, 12 hair-tubes were deployed, and collected hairs were taxa-attributed based on morphology. A presence/absence dataset was built, and db-RDA was used to explore assemblage composition, and single-species occupancy models to test specific hypotheses. The relative abundance of ground-foraging herbivorous/granivorous was higher in the burnt area, characterised by a dense undergrowth, which could be related to anti-predatory strategies and food opportunities. Insectivorous could be in a recolonisation phase, masking their earlier absence, which could explain why their abundance was not associated with any factor tested. Arboreal-foraging species were associated with forest type, indicating a primary role for tree cover and other factors such as rocky cover and likely in situ survival. The HAM was overall confirmed also in Mediterranean basin ecosystems. This may facilitate predictions about post-fire animal successions, which in turn may provide valuable insights into post-fire management practices and biodiversity conservation strategies.

Changes in Wolf Occupancy and Feeding Habits in the Northern Apennines: Results of Long-Term Predator-Prey Monitoring.

The comprehension of the factors that have influenced the recent changes in wolf (Canis lupus) range and diet that have occurred in our study area, characterized by a highly heterogeneous landscape, can shed light on their current process of expansion toward the plain. Wolf presence was monitored using a standardized protocol from 2007 to 2022 by carrying out eight monitoring sessions organized in seasonal surveys, during which, we collected wolf presence data. To model wolf range dynamics, we used dynamic occupancy models considering land cover types and wild ungulate abundances as covariates. Moreover, we studied the wolf diet through scat analysis, identifying the consumed items from undigested remains. Wolf occupancy in the study area progressed from mountains to lower hills gradually; the observed range dynamics were driven by prey abundance and human presence: in particular, the probability of colonization increased with roe deer (Capreolus capreolus) abundance, whereas the probability of extinction increased with urban areas. The wolf diet showed a gradual shift from the prevalent consumption of wild boar (2007-2008 and 2011-2012) to the prevalent consumption of roe deer (continuously increasing from 2015 onward). Our results might be related to a specific adaptation of the predator to the local ecology of the most consumed species: the roe deer.

Site occupancy of select mammals in the tropical forest of Eastern Himalaya

IntroductionTerrestrial mammals play a pivotal role in tropical forest ecosystems, representing a rich and functionally diverse component of these biomes. However, they confront formidable threats globally, such as hunting, habitat loss, and fragmentation, amidst the expansion of human-altered landscapes in tropical regions. Understanding the impacts of these changes on mammal communities is crucial for designing effective conservation interventions. Northeast India's tropical forests, a biodiversity hotspot, host a diverse array of mammalian fauna. The primary challenge faced by these species involves anthropogenic activities leading to the shrinkage and fragmentation of forested habitats.MethodologyIn this study, we conducted systematic camera trapping in Mehao Wildlife Sanctuary (WLS) to assess mammal status and distribution. Employing single-season occupancy models, we evaluated factors influencing mammalian species' detection probability and spatial utilization within the landscape. ResultsThe study documented 27 mammalian species, with 12 identified as "threatened" on the IUCN Red List. Species like clouded leopard, marbled cat, Gongshan muntjac, red goral, Mishmi takin, and sambar were recorded but observed infrequently. Notably, we reported the Asiatic brush-tailed porcupine's first sighting in Mehao. Our findings revealed that undisturbed forest habitats were preferred by all species. Mainland serow dominated most of the sanctuary's area, followed by northern red muntjac, yellow-throated marten, and masked palm civet.DiscussionThe response of mammalian species to ecological and anthropogenic covariates varied significantly, underscoring the necessity for species-specific management strategies alongside a landscape-scale conservation approach. These outcomes emphasize the urgency of managing and safeguarding rare and elusive mammalian species within and around Mehao WLS.

Trends in abundance and occupancy of the protected water beetle Graphoderus bilineatus in the Netherlands

The European Habitats Directive prescribes Member States to report on trends in abundance and distribution of protected species. One of these species is Graphoderus bilineatus (De Geer, 1774), a middle-sized predaceous aquatic beetle, listed in Annex II and IV of the Habitats Directive. In the Netherlands, a monitoring scheme for this species has been set up to assess the national trend as well as the trend in the national Natura2000 sites. In this scheme, a selection of 1 km2 squares is surveyed in cycles of six years using a standardized field method by professional fieldworkers. In each selected square, five locations were sampled per annum (September–October) by two different observers using hand netting. The data of the first two rounds (2011–2016 and 2017–2022) have been analysed using both an occupancy model and a Poisson GLMM. We found evidence of a declining trend in occupancy as well as in population size. The decreases were stronger outside than within Natura2000 sites and also stronger than those of three other beetle species that are often found together with G. bilineatus. In addition, considerable differences between observers were detected in the data, despite the application of a standardized field method.Implications for insect conservationGraphoderus bilineatus is declining and the decline is stronger outside Natura2000 sites then within, most likely due to differences in the development of water quality, vegetation structure and water management. Further research is required to identify the exact causes of the decline; however water quality improvement seems essential to turn the tide. The study also shows the benefits of a monitoring scheme for trend assessments. The recent decline would probably not have been noticed based on distribution data alone.

Multi-scale habitat influences sprainting and group size of a freshwater-obligate smooth-coated otter (Lutrogale perspicillata) in Tungabhadra Otter Conservation Reserve, India

BackgroundThe impact of changing land-use patterns and associated anthropogenic threats on scale-dependent habitat use of semi-aquatic mustelids in scent-marking and social behaviour can provide important insights into the habitat ecology of smooth-coated otters (Lutrogale perspicillata).MethodsWe sampled 180 stream segments (100–400 m) as spatial replicates of 60 1-km2 sites to record indirect evidence (i.e. spraints and mass latrine sites) and group sizes of smooth-coated otters along the Tungabhadra Otter Conservation Reserve (TOCR) during the dry season. To quantify habitat, we recorded stream characteristics, riparian vegetation, and anthropogenic disturbances at the local scale, and hydro-environmental characteristics and land uses at the landscape scale. Using Markovian-chain detection and occupancy models, we assessed the multi-scale habitat use of otters in their selection of suitable areas for scent-marking based on repeated presence-absence data on spraint/latrine locations along the TOCR. We further used linear regression techniques to explore relationships between the number of individuals in smooth-coated otter group and hydro-environmental characteristics, spraint/latrine encounter rate, anthropogenic pressure, land cover, topography, and vegetation.ResultsAt the local scale, the probability of spraint deposition and group size decreased with anthropogenic disturbance while the probability of spraint detections decreased with grass cover. At the landscape scale, the probability of otter site use for spraint deposition and group sizes increased in southeast flowing streams. Spraint deposition increased with the proportion of sugarcane fields, whereas in contrast, group size decreased with proportion of sugarcane fields.ConclusionsOur findings highlight the first empirical evidence on multi-scale habitat use of a southern Indian population of smooth-coated otters in an inland freshwater ecosystem surrounded by the scrub jungle–agriculture matrix. We suggest that habitat models built from analytical approaches that account for correlated detections can avoid biased predictions when estimating occupancy and detection probability of semi-aquatic or riparian mammal communities with linear distributions. Our findings indicate that human activity can impose constraints on the choice of sites used for spraint deposition and preliminary patterns in otter groups. The study provides some crucial evidence on the need to maintain areas with minimal human interference for sustainability of freshwater reserves.

Who, Why, When, and Where From? The Peopling of the Canary Islands and the Challenges of Archaeometry

Archaeologists in the Canary Islands have gathered substantial quantitative data from radiocarbon measurements and aDNA analyses. While undeniably helpful and necessary for apprehending past human activity, their interpretation, based on theories underpinning models developed for island chains, has lagged, leaving a gap in our understanding of processes of occupation and social network systems. The decontextualized nature of the archaeological landscape of the Canaries and a lack of consensus about proper radiocarbon methodologies are some of the factors contributing to heated scholarly debate. Here, for the Canary Islands, the author reviews the current literature on aDNA and discusses settlement theories, the chronological evidence used for occupation models, and how such perspectives align with current thinking on island colonization.

Range expansion of a declining forest species, the Western Gray Squirrel (Sciurus griseus), into semiarid woodland

Abstract Globally, animals that are range-restricted are frequently becoming species of conservation concern, in part due to competitive exclusion by phylogenetically and ecologically similar species that are more tolerant of human disturbance. However, climate and land use changes to natural landscapes can create pockets of refugia for range-restricted species. Western gray squirrels (Sciurus griseus) are native to the west coast of North America, principally California and western Oregon. Over the past several decades, Western Gray Squirrel populations have declined in human-dominated areas, with increased competition from introduced congeneric species native to eastern North America cited as a primary driver. Despite declines in their established range west of the Pacific Crest in western North America, western gray squirrels are extending their range into the Great Basin, where they were not historically found. Using a network of remote camera traps deployed across the Sierra Nevada–Great Basin ecotone in northwestern Nevada, we detected western gray squirrels across 16 of 100 camera-trapping sites. The majority of detections were located in piñon–juniper woodland, a land cover type not previously occupied by this species. Occupancy modeling revealed that western gray squirrels were equally likely to occur in piñon–juniper woodland compared to mature pine forest that they occupy elsewhere in their range. A species distribution model parameterized with historical gray squirrel observations (pre-1950), indicated increased climatic suitability for the species on the eastern side of the Sierra Nevada in recent decades, which may have facilitated this range expansion. Our findings reveal the potential for species declining in their historical range to colonize novel habitats that become increasingly suitable as a result of human-driven changes to ecosystems.

A unified framework for time‐to‐detection occupancy and abundance models

Abstract Time‐to‐detection (TTD) occupancy models are increasingly used to study site occupancy of organisms. Occupancy is a reduced representation of abundance (distinguishing only between and individuals), which is also often a quantity of interest. In this paper, we present a novel framework for TTD occupancy models that address limitations of existing approaches. Our approach incorporates factors that accommodate detection heterogeneity among sites/visits and inter‐visit dependency, allowing for the relaxation of some restrictive assumptions inherent in previous models. As a result, our framework offers a robust and versatile tool for analysing various ecological data sets. We employ a maximum likelihood approach to estimate model parameters and conduct inference for the proposed TTD occupancy models. A key feature of these models is the introduction of a community parameter. This parameter characterizes the similarity of detectabilities, ranging from complete independence to complete identity, across multiple site visits. This framework disentangles the detection rate, abundance and occupancy, similar to the popular N‐mixture model. For situations where abundance estimation is not the primary goal, a family of mixed gamma exponential TTD models is developed, which generally exhibit more stable numerical properties compared to N‐mixture type TTD models. The performance of the proposed models and some reduced models is evaluated through simulation studies. The results indicate that the N‐mixture TTD model tends to considerably overestimate the occupancy probability when the community parameter is less than one, a condition necessary to satisfy the strict closure population assumption. On the other hand, the standard exponential TTD occupancy model underestimates the occupancy probability in the presence of unobserved detection heterogeneity and inter‐visit dependency. An analysis of bird species in the Karoo region of South Africa demonstrates the enhanced flexibility of the proposed TTD occupancy models for data fitting. This paper demonstrates the importance of employing more flexible and general models to accurately capture the complexities of ecological systems or survey data. We provide R‐code to fit all considered models to data. The proposed TTD model framework contributes to enhancing our understanding of species occupancy distributions.