Mark-recapture Research Articles

Abundance estimation of plains zebras via search–encounter sampling

Spatial capture–recapture (SCR) using search–encounter methods estimate population abundance from encounters of individually recognisable animals along an a priori-designated search path. We applied search–encounter SCR methods and photographic sampling to estimate the abundance of plains zebras (Equus quagga) at Telperion and Ezemvelo nature reserves, South Africa. We analysed encounter data by comparing four hazard-function models for the detection process. The abundance estimate under three models was just above 1000 animals (95% credible intervals c. 960, 1220) versus 811 (719, 917) for the remaining model. The former estimates were broadly similar to aerial counts conducted around the same time. Standard deviation in locations around individual activity centres (σmove\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\sigma _{move}$$\\end{document}) was c. 0.8 km, with little difference between models. In situations where structured surveys are not possible, the approach presented here has the potential to estimate abundance from opportunistic animal encounters (e.g. generated via citizen science schemes) within an SCR framework.

Estimating the size of populations at risk for malaria: a case study in cattle herders and agricultural workers in Northern Namibia

Cattle herders and agricultural workers have been identified has key high-risk populations for malaria in northern Namibia. Population size estimates for these groups are lacking but are important for planning, monitoring and evaluating the effectiveness of targeted strategies towards malaria elimination in the region. In this analysis, we extend population size estimation methods routinely used in HIV research, specifically social mapping and multiple source capture-recapture, to the context of malaria to estimate how many cattle herders and agricultural workers lived in two regions of northern Namibia over the course of the 2019–2020 malaria season. Both methods estimated two to three times more agricultural workers than cattle herders but size estimates based on the multiple source capture-recapture method were two to three times greater than the mapping-based, highlighting important methodological considerations to apply such methods to these highly mobile populations. In particular, we compared open versus closed populations assumptions for the capture-recapture method and assessed the impact of sensitivity analyses on the procedure to link records across multiple data sources on population size estimates. Our results are important for national control programs to target their resources and consider integrating routine population size estimation of high risk populations in their surveillance activities.

Estimation of the Population Size of Street- and Venue-Based Female Sex Workers and Sexually Exploited Minors in Rwanda in 2022: 3-Source Capture-Recapture.

HIV surveillance among key populations is a priority in all epidemic settings. Female sex workers (FSWs) globally as well as in Rwanda are disproportionately affected by the HIV epidemic; hence, the Rwanda HIV and AIDS National Strategic Plan (2018-2024) has adopted regular surveillance of population size estimation (PSE) of FSWs every 2-3 years. We aimed at estimating, for the fourth time, the population size of street- and venue-based FSWs and sexually exploited minors aged ≥15 years in Rwanda. In August 2022, the 3-source capture-recapture method was used to estimate the population size of FSWs and sexually exploited minors in Rwanda. The field work took 3 weeks to complete, with each capture occasion lasting for a week. The sample size for each capture was calculated using shinyrecap with inputs drawn from previously conducted estimation exercises. In each capture round, a stratified multistage sampling process was used, with administrative provinces as strata and FSW hotspots as the primary sampling unit. Different unique objects were distributed to FSWs in each capture round; acceptance of the unique object was marked as successful capture. Sampled FSWs for the subsequent capture occasions were asked if they had received the previously distributed unique object in order to determine recaptures. Statistical analysis was performed in R (version 4.0.5), and Bayesian Model Averaging was performed to produce the final PSE with a 95% credibility set (CS). We sampled 1766, 1848, and 1865 FSWs and sexually exploited minors in each capture round. There were 169 recaptures strictly between captures 1 and 2, 210 recaptures exclusively between captures 2 and 3, and 65 recaptures between captures 1 and 3 only. In all 3 captures, 61 FSWs were captured. The median PSE of street- and venue-based FSWs and sexually exploited minors in Rwanda was 37,647 (95% CS 31,873-43,354), corresponding to 1.1% (95% CI 0.9%-1.3%) of the total adult females in the general population. Relative to the adult females in the general population, the western and northern provinces ranked first and second with a higher concentration of FSWs, respectively. The cities of Kigali and eastern province ranked third and fourth, respectively. The southern province was identified as having a low concentration of FSWs. We provide, for the first time, both the national and provincial level population size estimate of street- and venue-based FSWs in Rwanda. Compared with the previous 2 rounds of FSW PSEs at the national level, we observed differences in the street- and venue-based FSW population size in Rwanda. Our study might not have considered FSWs who do not want anyone to know they are FSWs due to several reasons, leading to a possible underestimation of the true PSE.

Intersectional inequities and longitudinal prevalence estimates of opioid use disorder in Massachusetts 2014–2020: a multi-sample capture-recapture analysis

As overdoses continue to increase worldwide, accurate estimates are needed to understand the size of the population at risk and address health disparities. Capture-recapture methods may be used in place of direct estimation at nearly any geographic level (e.g., city, state, country) to estimate the size of the population with opioid use disorder (OUD). We performed a multi-sample capture-recapture analysis with persons aged 18-64 years to estimate the prevalence of OUD in Massachusetts from 2014 to 2020, stratified by sex and race/ethnicity. We used seven statewide administrative data sources linked at the individual level. We developed log-linear models to estimate the unknown OUD-affected population. Uncertainty was characterized using 95% confidence intervals (95% CI) on the total counts and prevalence estimates. The estimated OUD prevalence increased from 5.47% (95% CI=4.89%, 5.98%) in 2014 to 5.79% (95% CI=5.34%, 6.19%) in 2020. Prevalence among Hispanic females doubled (2.46% in 2014 to 4.23% in 2020) and prevalence rose to nearly 10% among Black non-Hispanic males and Hispanic males from 2014 through 2019. Estimates for Black non-Hispanic females more than doubled from 2014 through 2019 (3.39% to 7.09%), and then decreased to 5.69% in2020. This study is the first to provide OUD prevalence trend estimates by binary sex and race/ethnicity at a state level using capture-recapture methods. Using these methods as the international overdose crisis worsens can allow jurisdictions to appropriately allocate resources and targeted interventions to marginalised populations. NIDA.

The importance of independence in unmarked spatial capture–recapture analysis

Wildlife populations can be unmarked, meaning individuals lack distinguishing features for individual identification. Populations may also exhibit non‐independent movements, meaning individuals move together. For populations of either unmarked or non‐independent individuals, models based on spatial capture–recapture (SCR) approaches can be used to estimate abundance, density, and other parameters critical for monitoring, management, and conservation. However, when individuals are both unmarked and non‐independent, few model options are available. One approach has been to apply unmarked models and not address the non‐independence despite unquantified impacts on bias, precision, and the ability to make robust ecological inferences. We conducted a simulation study to quantify the impact of non‐independence on the performance of spatial count (SC) and spatial partial identity models (SPIM) – two SCR‐based unmarked modeling approaches – and used the performance of fully marked and independent SCR as a reference. We varied the levels of non‐independence (aggregation and cohesion), detection probability, and the number of partial identity covariates used to resolve identities in SPIM estimation. We expected abundance estimates to be increasingly biased and precise as aggregation and cohesion increased. Results showed that models indeed became less robust to increasing non‐independence, but importantly suggested that only SPIM could be reliably applied under low levels of cohesion when sufficient partial identity covariates are available. SC yielded consistently biased estimates with poor precision. SCR was consistently robust across combinations of aggregation and cohesion, as expected. We therefore advise against the use of SC models for estimating population parameters when individuals are known to be non‐independent, caution that SPIM may be used under narrow ecological conditions, and encourage continued investigations into sampling design and methods development for estimating populations of unmarked and non‐independent individuals.

Incidence of Multiple Sclerosis in Uruguay: A Prospective Population-Based Study

Background: The worldwide incidence of multiple sclerosis (MS) is estimated at 0.5–10 cases per 100,000 person-years and is probably increasing. In 2014, a previous study estimated the incidence of multiple sclerosis in Uruguay at 1.2 cases per 100,000 person-years. Objectives: We conducted an observational, prospective, population-based study to determine MS incidence from diagnosis in Uruguay. Methods: The population studied included people older than 18 years of age who were living in Uruguay between July 1, 2019, and June 30, 2021. The diagnosis was based on 2017 McDonald criteria. Multiple data sources were employed including neurologists, magnetic resonance imaging centers, laboratories performing oligoclonal band testing, neurophysiology laboratories, neurorehabilitation centers, the institution Fondo Nacional de Recursos, and the MS Patients’ Association of Uruguay (EMUR). The capture-recapture method was used to estimate incidence. Results: 155 new MS cases were confirmed after review. The median age was 35 (range 18–62). Thirteen patients (8.38%) were diagnosed with late-onset MS. The crude incidence rate was 2.89 cases per 100,000 person-years, 3.95 among females, and 1.72 among male patients. The incidence rate estimated using the capture-recapture method was 3.18 (95% CI: 3.02–3.34). Conclusions: According to the Atlas of MS, Uruguay has a low incidence rate (2.0–3.99), even though it is one of the highest in Latin America. Our country aligns with the global trend of increasing incidence. Age and sex distribution were similar to other studies, with a high incidence of patients with late-onset multiple sclerosis. The capture-recapture method confirms the exhaustivity of our investigation.

Small-scale movements and site fidelity of two sympatric sea turtle species at a remote atoll

Understanding natural movement patterns and ecological roles of marine megafauna is a research priority best studied in areas with minimal human impact. The spatial distribution patterns specifically for immature turtles at foraging grounds have been highlighted as a research gap for effective management and conservation strategies for sea turtle populations. Capture–mark–recapture (CMR) records (n = 2287) of 1672 immature green (Chelonia mydas) (n = 1158) and hawksbill turtles (Eretmochelys imbricata) (n = 514) from a long-term (1981–2021) in-water CMR program at Aldabra Atoll, Seychelles, were analyzed for 10 sites (0.35–25 km apart). Site fidelity was not correlated with either season or turtle size. Green turtles had lower site fidelity than hawksbill turtles. Green turtles showed avoidance (i.e., opposite of fidelity) of three sites, while hawksbill turtles displayed high fidelity to two sites. Sites displaying non-random behavior (avoidance and/or fidelity) did not share the same benthic habitat types. Results indicate that fidelity can be detected at a fine scale with CMR, but that further exploration into the habitat characteristics of the sites and the ecological roles of both species at the atoll is needed.

First density estimates for a recovering bobcat population in Ohio using DNA from scat

AbstractThe recovery of mammalian species in the US Midwest through natural recolonization constitutes a conservation success story, yet management remains challenging due to many unknowns related to population dynamics and numeric trends. Abundance is a critical parameter for management decisions, and estimating the density and abundance of elusive species, such as terrestrial carnivores, remains challenging despite recent technological advances. In this study, we evaluated density and abundance of a recovering carnivore species, the bobcat (Lynx rufus) in two areas of Ohio using non‐invasive DNA from scat. The target areas in eastern and southern Ohio have been shown to have uneven dynamics and recolonization success and we expected that this would be reflected in differences in density and abundance. We collected 298 bobcat scats between July 2018 and April 2019 on 150 km of repeated transects. Of these, 102 scats were successfully genotyped, and 55 individuals were identified (33 in eastern Ohio and 22 in southern Ohio). Using Spatially Explicit Capture–Recapture models, we estimated 18.9 ± 4.1 and 10.9 ± 2.7 bobcats/100 km2 in eastern and southern Ohio study areas, respectively. Our results support prior telemetry data which indicated that bobcats in eastern Ohio had smaller home‐ranges than bobcats in southern Ohio, and thus could support a higher density of individuals. The higher densities were similar to other eastern US populations and are much higher than other Midwestern recovering populations. Our results provide a snapshot of the population status and can be used to determine sustainable management strategies for Ohio's bobcat population.

A Capture-Recapture-based Ascertainment Probability Weighting Method for Effect Estimation With Under-ascertained Outcomes.

Outcome under-ascertainment, characterized by the incomplete identification or reporting of cases, poses a substantial challenge in epidemiologic research. While capture-recapture methods can estimate unknown case numbers, their role in estimating exposure effects in observational studies is not well established. This paper presents an ascertainment probability weighting framework that integrates capture-recapture and propensity score weighting. We propose a nonparametric estimator of effects on binary outcomes that combines exposure propensity scores with data from two conditionally independent outcome measurements to simultaneously adjust for confounding and under-ascertainment. Demonstrating its practical application, we apply the method to estimate the relationship between health care work and coronavirus disease 2019 testing in a Swedish region. We find that ascertainment probability weighting greatly influences the estimated association compared to conventional inverse probability weighting, underscoring the importance of accounting for under-ascertainment in studies with limited outcome data coverage. We conclude with practical guidelines for the method's implementation, discussing its strengths, limitations, and suitable scenarios for application.

Spatial ecotoxicology: what we know about the relationship between avian movements and contaminant levels

Birds are widely used as indicators of environmental contamination because they integrate signals across space and time. However, this advantage also means that locating the source of pollution can be challenging, especially for species that migrate large distances. Historically, the assignment of contaminant burden to particular life stages or locations has been made by sampling tissues with varying time signals and associating those signals with locations assigned from band recoveries or stable isotope analyses. Unfortunately, these assignments are geographically coarse. More recently, tracking devices have been increasingly used to determine more precisely where and when contamination is likely to occur. Here, we review current knowledge on using tracking devices to examine the relationship between avian movements and contaminant loads. We found 42 published articles with samples collected from 1986 to 2021 that used tracking devices to examine the relationship between avian movement and contaminant loads, where studies were primarily concentrated in the northern hemisphere, notably in the North Atlantic. Tracking methodology varied widely across studies to date, but the use of radiotransmitters and satellite tags generally decreased as newer technologies, such as global positioning systems and geolocation sensors, were developed. Blood and feathers were the most commonly used tissues to assess contaminant concentrations, but sample sizes were often low (<40, the recommended sample size for some tracking or contaminant studies), and one-quarter of studies did not statistically test the relationship between tracking data and contaminant concentrations. Moving forward, studies should (1) consider statistical power; (2) consider tissue turnover rates, contaminant turnover rates, and tracking device resolution; (3) examine tissues that inform different time scales; 4) explore the impacts of contaminants on behaviour and movement; and 5) increase collaboration, standardization, and information sharing across existing tracking or contaminant monitoring programs. Focusing on these aspects will enhance our ability to identify the source, transport, and fate of contaminants in avian species across the globe.

Abundance estimates of Gunnison's prairie dogs compared to the number of active burrows

AbstractReliable estimates of prairie dog (Cynomys spp.) population size and distribution are critical for assessing the status of prairie dogs and for selecting sites to reintroduce black‐footed ferrets (Mustela nigripes). The density of active prairie dog burrows has commonly been used as an index of prairie dog abundance. Indices derived from active burrow counts were developed for black‐tailed (C. ludovicianus) and white‐tailed (C. leucurus) prairie dogs, but their efficacy has not been evaluated for all prairie dog species and studies affirming their validity with robust abundance estimators are few. We indexed or estimated the abundance of Gunnison's prairie dogs (C. gunnisoni) in the Aubrey Valley, Arizona, USA, in 2006 at 2 different time periods using 4 different methods—maximum above ground counts (MAGC), minimum number known alive (MNKA), capture‐mark‐recapture (CMR), and mark‐resight—and compared these estimates to active burrow counts in 2005 and 2006. We found no positive relationship between active burrow counts and any abundance estimators. Mark‐resight estimates of abundance were greater than the MNKA and were positively correlated with both the MNKA (r2 = 0.30) and CMR estimates (r2 = 0.49). Both CMR estimates and MAGC were typically below the MNKA and therefore biased low. Our results indicated that more rigorous estimation methods may be necessary to accurately estimate prairie dog abundance and assess habitat quality for ferret conservation.

Shorter telomeres are associated with shell anomalies in a long‐lived tortoise

AbstractAge‐related telomere length (TL) variation is relatively well‐described for mammals, birds and other model organisms. Nevertheless, it remains largely unknown in ectotherms, especially turtles and tortoises, which are extremely long‐lived species with slow or negligible senescence. In this study, we described TL dynamics in wild spur‐thighed tortoises (Testudo graeca), one of the chelonian species with the lowest aging rates. By combining cross‐sectional (single) and longitudinal (capture–recapture) samplings, we assessed the relationship between TL and individual characteristics (sex, age, individual growth rate, body condition index, presence of shell anomalies). We did not find any association between TL and sex, individual growth rate, or body condition. However, the relationship with age remains uncertain, likely due to the complex dynamics of TL over time. Interestingly, shorter telomeres correlated significantly with shell anomalies, which are usually assumed as a fitness proxy for reptiles. Overall, our results suggest TL as a potential indicator for ontogenetic studies on tortoises, while its utility as a marker of biological age appears limited.

Outbreak of severe community-acquired bacterial infections among children in North Rhine-Westphalia (Germany), October to December 2022

PurposeIn late 2022, a surge of severe S. pyogenes infections was reported in several European countries. This study assessed hospitalizations and disease severity of community-acquired bacterial infections with S. pyogenes, S. pneumoniae, N. meningitidis, and H. influenzae among children in North Rhine-Westphalia (NRW), Germany, during the last quarter of 2022 compared to long-term incidences.MethodsHospital cases due to bacterial infections between October and December 2022 were collected in a multicenter study (MC) from 59/62 (95%) children's hospitals in NRW and combined with surveillance data (2016–2023) from the national reference laboratories for streptococci, N. meningitidis, and H. influenzae. Overall and pathogen-specific incidence rates (IR) from January 2016 to March 2023 were estimated via capture–recapture analyses. Expected annual deaths from the studied pathogens were calculated from national death cause statistics.ResultsIn the MC study, 153 cases with high overall disease severity were reported with pneumonia being most common (59%, n = 91). IRs of bacterial infections declined at the beginning of the COVID-19 pandemic and massively surged to unprecedented levels in late 2022 and early 2023 (overall hospitalizations 3.5-fold), with S. pyogenes and S. pneumoniae as main drivers (18-fold and threefold). Observed deaths during the study period exceeded the expected number for the entire year in NRW by far (7 vs. 0.9).DiscussionThe unprecedented peak of bacterial infections and deaths in late 2022 and early 2023 was caused mainly by S. pyogenes and S. pneumoniae. Improved precautionary measures are needed to attenuate future outbreaks.

Estimating internal transmitter and external tag retention by Walleye in the Laurentian Great Lakes over multiple years

AbstractObjectiveBoth electronic tags (e.g., acoustic and radio transmitters) and conventional external tags are used to evaluate movement and population dynamics of fish. External tags are also sometimes used to facilitate the recovery of internal electronic tags or other instrumentation because healing can make it difficult to identify fish with internal tags based on appearance alone. With both tag types, tag shedding and failure of electronic tags can affect accuracy and precision of study results.MethodsWe used a decade (2011–2021) of recapture data for Walleye Sander vitreus tagged in the Laurentian Great Lakes, where fish were double‐ or triple‐tagged with external tags (T‐bar, loop, or internal anchor tags) and internal acoustic transmitters, to quantify external tag and internal transmitter shedding and transmitter failure rates.ResultIn total, 1125 (33%) Walleye were recovered that had retained at least one external tag or internal transmitter. No confirmed cases of transmitter shedding were observed; 15 of 899 transmitters (2%) that were checked for functionality failed prior to the expected battery expiration. The retention of external T‐bar tags 1 year after release differed depending on whether the tag was placed anterior or posterior to the secondary dorsal fin (anterior, fish length = 420 mm: 73% retention; anterior, fish length = 700 mm: 73%, posterior: 63%) but was <26% after 4 years for both tag positions and fish sizes. Internal anchor tags had an 88% 1‐year retention probability and 81% 4‐year retention probability. Loop tags had the highest 1‐year retention (89%) but after 4 years retention (28–34% depending on agency) was comparable to that of T‐bar tags.ConclusionBetter understanding of tag retention characteristics through long‐term tagging studies such as this can inform study design, be considered in model design, and ultimately improve inferences from mark–recapture studies.

Two-step semiparametric empirical likelihood inference from capture–recapture data with missing covariates

Two-step semiparametric empirical likelihood inference from capture–recapture data with missing covariates

Airborne imagery does not preclude detectability issues in estimating bird colony size

Aerial images obtained by drones are increasingly used for ecological research such as wildlife monitoring. Yet detectability issues resulting from animal activity or visibility are rarely considered, although these may lead to biased population size and trend estimates. In this study, we investigated detectability in a census of Malagasy pond heron Ardeola idae colonies on the island of Mayotte. We conducted repeated drone flights over breeding colonies in mangrove habitats during two breeding seasons. We then identified individuals and nests in the images and fitted closed capture-recapture models on nest-detection histories. We observed seasonal variation in the relative abundance of individuals, and intra-daily variation in the relative abundance of individuals—especially immature birds—affecting the availability of nests for detection. The detection probability of nests estimated by capture–recapture varied between 0.58 and 0.74 depending on flyover days and decreased 25% from early to late morning. A simulation showed that three flyovers are necessary to detect a 5–6% decline in colonies of 50 to 200 nests. These results indicate that the detectability of nests of forest-canopy breeding species from airborne imagery can vary over space and time; we recommend the use of capture-recapture methods to control for this bias.

The central role of the identifying assumption in population size estimation.

The problem of estimating the size of a population based on a subset of individuals observed across multiple data sources is often referred to as capture-recapture or multiple-systems estimation. This is fundamentally a missing data problem, where the number of unobserved individuals represents the missing data. As with any missing data problem, multiple-systems estimation requires users to make an untestable identifying assumption in order to estimate the population size from the observed data. If an appropriate identifying assumption cannot be found for a data set, no estimate of the population size should be produced based on that data set, as models with different identifying assumptions can produce arbitrarily different population size estimates-even with identical observed data fits. Approaches to multiple-systems estimation often do not explicitly specify identifying assumptions. This makes it difficult to decouple the specification of the model for the observed data from the identifying assumption and to provide justification for the identifying assumption. We present a re-framing of the multiple-systems estimation problem that leads to an approach that decouples the specification of the observed-data model from the identifying assumption, and discuss how common models fit into this framing. This approach takes advantage of existing software and facilitates various sensitivity analyses. We demonstrate our approach in a case study estimating the number of civilian casualties in the Kosovo war.

A flexible framework for spatial capture-recapture with unknown identities.

Camera traps or acoustic recorders are often used to sample wildlife populations. When animals can be individually identified, these data can be used with spatial capture-recapture (SCR) methods to assess populations. However, obtaining animal identities is often labor-intensive and not always possible for all detected animals. To address this problem, we formulate SCR, including acoustic SCR, as a marked Poisson process, comprising a single counting process for the detections of all animals and a mark distribution for what is observed (eg, animal identity, detector location). The counting process applies equally when it is animals appearing in front of camera traps and when vocalizations are captured by microphones, although the definition of a mark changes. When animals cannot be uniquely identified, the observed marks arise from a mixture of mark distributions defined by the animal activity centers and additional characteristics. Our method generalizes existing latent identity SCR models and provides an integrated framework that includes acoustic SCR. We apply our method to estimate density from a camera trap study of fisher (Pekania pennanti) and an acoustic survey of Cape Peninsula moss frog (Arthroleptella lightfooti). We also test it through simulation. We find latent identity SCR with additional marks such as sex or time of arrival to be a reliable method for estimating animal density.

Discussion on "The central role of the identifying assumption in population size estimation" by Serge Aleshin-Guendel, Mauricio Sadinle, and Jon Wakefield.

In this discussion response, we consider some practical implications of the authors' consideration of the no-highest-order interaction (NHOI) model for multiple systems estimation, which permits the authors to derive the explicit (albeit untestable) identifying assumption related to the unobserved (or missing) individuals. In particular, we discuss several aspects, from the standard process of model selection to potential poor predictive performance due to over-fitting and the implications of data reduction. We discuss these aspects in relation to the case study presented by the authors relating to the number of civilian casualties within the Kosovo war, and conduct further preliminary simulations to investigate these issues further. The results suggest that the NHOI models considered, despite having a potentially useful theoretical result in relation to the underlying identifying assumption, may perform poorly in practice.

That's not the Mona Lisa! How to interpret spatial capture-recapture density surface estimates.

Spatial capture-recapture methods are often used to produce density surfaces, and these surfaces are often misinterpreted. In particular, spatial change in density is confused with spatial change in uncertainty about density. We illustrate correct and incorrect inference visually by treating a grayscale image of the Mona Lisa as an activity center intensity or density surface and simulating spatial capture-recapture survey data from it. Inferences can be drawn about the intensity of the point process generating activity centers, and about the likely locations of activity centers associated with the capture histories obtained from a single survey of a single realization of this process. We show that treating probabilistic predictions of activity center locations as estimates of the intensity of the process results in invalid and misleading ecological inferences, and that predictions are highly dependent on where the detectors are placed and how much survey effort is used. Estimates of the activity center density surface should be obtained by estimating the intensity of a point process model for activity centers. Practitioners should state explicitly whether they are estimating the intensity or making predictions of activity center location, and predictions of activity center locations should not be confused with estimates of the intensity.