Estimating Population Density Per Unit Area from Mark, Release, Recapture Data

A graphic method for quickly estimating an animal population density and the precision of the estimate in field survey is proposed in this paper. The properties of this method are as follows : (1) The density estimation is made only from the frequency of sampling usits having zero individuals and one individual assuming a negative binomial or Poisson distribution as the spatial pattern of the animal; (2) No preliminary survey before the main survey is required; (3) Estimates of the population density and the precision of these estimates are obtained in the field; (4) If required, one can improve the precision by taking more additioanl sampling units immediately in the field; (5) Much time and effort in counting individuals and estimating their density may be saved by using this method.

Evaluating presence and abundance of small carnivores is essential for their conservation. In Italy, there is scarce information on European pine marten distribution, and no data are published on its abundance. Camera traps have been widely used to estimate population density applying capture–recapture models for species in which individual recognition is possible. Here we estimate the abundance of European pine martens in central Italy using camera trapping and a model that allows the estimation of population density without the need for individual recognition Rowcliffe et al. (Anim Conserv 11:185–186, 2008). Camera trapping was also used to evaluate habitat use patterns by martens. Fifteen camera traps were deployed in 90 placements for 15 days each, for a total of 1,334 camera days. Pine martens were captured in 24% of camera trap placements with a mean trap success rate of 0.33 photographs per camera placement. Estimated pine marten population density in the study area was 0.34 individuals km−2. Marten trap rate was not strongly associated with any habitat type, although there were trends towards lower probability of records at locations with high coverage of cultivated fields and higher probability of records at locations with high coverage of human-made woodland. The results suggest that pine martens in this area are not confined to wooded habitat. To our knowledge, this study is the first application of the Rowcliffe et al. (Anim Conserv 11:185–186, 2008) method to a wild carnivore population and, furthermore, the first estimation of population density of pine martens in Italy.

Populations of largemouth bass Micropterus salmoides longer than 199 mm total length (TL) in hatchery ponds were estimated by using both mark–recapture and an electrofishing catch-per-effort (CPE) model. and these estimates were compared to actual densities of largemouth bass obtained after draining the pond. Mark–recapture underestimated populations of largemouth bass in 11of 13 ponds. Error in mark–recapture estimation of numbers of largemouth bass decreased as the percentage of the population that was marked increased. Population estimates that used a previously published electrofishing CPE model underestimated population densities of largemouth bass obtained by pond draining, with errors ranging from 62.9 to 89.4%. Electrofishing CPE was significantly (P < 0.05) correlated with population density of largemouth bass but was not correlated with conductivity, turbidity, or plant biomass (P > 0.05 for all). A model to predict density of largemouth bass longer than 199 mm TL in ponds was developed by regressing actual population density against electrofishing CPE.

Accurate estimation of population parameters for imperiled wildlife is crucial for effective conservation decision‐making. Population density is commonly used for monitoring imperiled species across space and time, and spatial capture–recapture (SCR) models can produce unbiased density estimates. However, many imperiled species are restricted to fragmented remnant habitats in landscapes severely modified by humans, which can alter animal space use in ways that violate typical SCR model assumptions, possibly cryptically biasing density estimates and misinforming conservation actions. Using data from a two‐year camera‐trapping survey in the Central Pacific Coast region, Mexico, we demonstrate the potential importance to endangered jaguar (Panthera onca) conservation of considering non‐circular home ranges when estimating population density with SCR. Strong evidence existed that jaguars had elliptical home ranges wherein movements primarily occurred along linearly arranged coastal habitats that the camera array aligned with. Accounting for this movement with the SCR anisotropic detection function transformation, density estimates were 30%–32% higher than estimates from standard SCR models that assumed circular home ranges. Given much of suitable jaguar habitat in Mexico is fragmented and linearly oriented along coastlines and mountain ranges, accommodating irregular space use in SCR may be critical for obtaining reliable density estimates to inform effective jaguar conservation.

Estimating density of elusive carnivores with capture–recapture analyses is increasingly common. However, providing unbiased and precise estimates is still a challenge due to uncertainties arising from the use of (1) bait or lure to attract animals to the detection device and (2) ad hoc boundary‐strip methods to compensate for edge effects in area estimation. We used photographic‐sampling data of the Malagasy civet Fossa fossana collected with and without lure to assess the effects of lure and to compare the use of four density estimators which varied in methods of area estimation. The use of lure did not affect permanent immigration or emigration, abundance and density estimation, maximum movement distances, or temporal activity patterns of Malagasy civets, but did provide more precise population estimates by increasing the number of recaptures. The spatially‐explicit capture–recapture (SECR) model density estimates ±SE were the least precise as they incorporate spatial variation, but consistent with each other (Maximum likelihood‐SECR = 1.38 ± 0.18, Bayesian‐SECR = 1.24 ± 0.17 civets/km 2 ), whereas estimates relying on boundary‐strip methods to estimate effective trapping area did not incorporate spatial variation, varied greatly and were generally larger than SECR model estimates. Estimating carnivore density with ad hoc boundary‐strip methods can lead to overestimation and/or increased uncertainty as they do not incorporate spatial variation. This may lead to inaction or poor management decisions which may jeopardize at‐risk populations. In contrast, SECR models free researchers from making subjective decisions associated with boundary‐strip methods and they estimate density directly, providing more comparable and valuable population estimates.

Density estimation for unmarked animals is particularly challenging, yet density estimates are often necessary for effective wildlife management. Raccoons (Procyon lotor) are the primary terrestrial wildlife reservoir for Lyssavirus rabies within the United States. The raccoon rabies variant (RRVV) is actively managed at landscape scales using oral rabies vaccination (ORV) within the eastern United States. To effectively manage RRVV, it is important to know the density of raccoons to appropriately scale the density of ORV baits distributed on the landscape. We compared methods to estimate raccoon densities from camera‐trap data versus more intensive capture‐mark‐recapture (CMR) estimates across 2 land cover types (upland pine and bottomland hardwood) in the southeastern United States during 2019 and 2020. We evaluated the effect of alternative camera configurations and durations of camera trapping on density estimates and used an N‐mixture model to estimate raccoon densities, including covariates on abundance and detection. We further compared different methods of scaling camera‐based counts, with the maximum number of raccoons seen on any given image within a day best explaining density. Camera‐trap density estimates were moderately correlated with CMR estimates (r = 0.56). However, densities from camera‐trap data were more reliable when classifying category of density as an index used to inform management (83% correct when compared to CMR estimates), although the densities in our study fell into the 2 lowest density classes only. Using more cameras reduced bias and uncertainty around density estimates; however, if ≤6 camera traps were used at a site, a line transect approach proved less biased than a grid design. Camera trapping should be conducted for at least 3 weeks for more accurate estimates of raccoon population density in our study area (&lt;5% bias). We show that camera‐trap data can be used to assign raccoon densities to management‐relevant density index bins, but more studies are needed to ensure reliability across a greater range of environmental conditions and raccoon densities.

Summary1.Many animal species are detected primarily by sound. Although songs, calls and other sounds are often used for population assessment, as in bird point counts and hydrophone surveys of cetaceans, there are few rigorous methods for estimating population density from acoustic data.2.The problem has several parts – distinguishing individuals, adjusting for individuals that are missed, and adjusting for the area sampled. Spatially explicit capture–recapture (SECR) is a statistical methodology that addresses jointly the second and third parts of the problem. We have extended SECR to use uncalibrated information from acoustic signals on the distance to each source.3.We applied this extension of SECR to data from an acoustic survey of ovenbirdSeiurus aurocapilladensity in an eastern US deciduous forest with multiple four‐microphone arrays. We modelled average power from spectrograms of ovenbird songs measured within a window of 0·7 s duration and frequencies between 4200 and 5200 Hz.4.The resulting estimates of the density of singing males (0·19 ha−1SE 0·03 ha−1) were consistent with estimates of the adult male population density from mist‐netting (0·36 ha−1SE 0·12 ha−1). The fitted model predicts sound attenuation of 0·11 dB m−1(SE 0·01 dB m−1) in excess of losses from spherical spreading.5.Synthesis and applications.Our method for estimating animal population density from acoustic signals fills a gap in the census methods available for visually cryptic but vocal taxa, including many species of bird and cetacean. The necessary equipment is simple and readily available; as few as two microphones may provide adequate estimates, given spatial replication. The method requires that individuals detected at the same place are acoustically distinguishable and all individuals vocalize during the recording interval, or that theper capitarate of vocalization is known. We believe these requirements can be met, with suitable field methods, for a significant number of songbird species.

Removal sampling, sweepnet sampling, and visual count sampling conducted while walking at constant velocity through a field were used to sample populations of adults of five coccinellid species in plots established in spring wheat fields, Triticum aestivum L. Estimates of absolute population density obtained from two 20-min removal samples taken from each of six 5- by 5-m sub-plots per plot proved reliable and were used to convert estimates obtained from sweepnet sampling (180 sweeps per plot) and visual counts (36 min per plot walking at 10 m/min) into absolute estimates of population density. Population density estimates obtained by removal sampling were quite precise except for species with low capture efficiencies and low population densities.Crop plant growth stage influenced the numbers of beetles caught in sweepnet samples and was incorporated in regression models for converting sweepnet catch to absolute density. Values of R2 of regressions ranged from 0.51 to 0.90, depending on species. Visual counts were influenced by temperature and aphid density, and these variables were incorporated in regression models. Values of R2 for regressions relating visual counts to population densities ranged from 0.63 to 0.94, depending on species.

Dispersal is an important step in animal's life cycle, one consequence of which is reducing local mate and resource competition. Dispersal is often achieved during one unique special movement, from the birthplace to a new appropriate area where to settle and reproduce. However, in species in which this special movement is limited by life history tradeoffs, we may expect dispersal to be promoted also by routine movements occurring throughout the animal’s life and stimulated by other activities like foraging or the search of nesting conditions. Here we employ a multidisciplinary approach consisting of computer simulations, mark–recapture and genetic data to better understand the role of colony relocations as dispersal strategy in the gypsy ant Aphaenogaster senilis. Contrary to expectations, our results show that colony relocations do not result in effective dispersal as evidenced by mark–recapture and genetic data. Furthermore, simulations showed that successive colony relocations did not follow a constant direction, but occurred either in a randomly changing direction or followed a circular trajectory, indicating limited effective dispersal. We also found a general lack of inbreeding and significant population viscosity between neighbouring colonies suggesting that relocations may act as a balancing strategy between these two processes. We discuss the results in terms of their evolutionary and ecological significance, and highlight future directions of research towards the understanding of dispersal strategies in colonial species.

The Population Density Tables (PDT) project at Oak Ridge National Laboratory (www.ornl.gov) is developing population density estimates for specific human activities under normal patterns of life based largely on information available in open source. Currently, activity-based density estimates are based on simple summary data statistics such as range and mean. Researchers are interested in improving activity estimation and uncertainty quantification by adopting a Bayesian framework that considers both data and sociocultural knowledge. Under a Bayesian approach, knowledge about population density may be encoded through the process of expert elicitation. Due to the scale of the PDT effort which considers over 250 countries, spans 50 human activity categories, and includes numerous contributors, an elicitation tool is required that can be operationalized within an enterprise data collection and reporting system. Such a method would ideally require that the contributor have minimal statistical knowledge, require minimal input by a statistician or facilitator, consider human difficulties in expressing qualitative knowledge in a quantitative setting, and provide methods by which the contributor can appraise whether their understanding and associated uncertainty was well captured. This paper introduces an algorithm that transforms answers to simple, non-statistical questions into a bivariate Gaussian distribution as the prior for the Beta distribution. Based on geometric properties of the Beta distribution parameter feasibility space and the bivariate Gaussian distribution, an automated method for encoding is developed that responds to these challenging enterprise requirements. Though created within the context of population density, this approach may be applicable to a wide array of problem domains requiring informative priors for the Beta distribution.

Wildlife density estimates provide an idea of the current state of populations, and in some cases, reflect the conservation status of ecosystems, essential aspects for effective management actions. In Mexico, several regions have been identified as high priority areas for the conservation of species that have some level of risk, like the Yucatan Peninsula (YP), where the country has the largest population of jaguars. However, little is known about the current status of threatened and endangered felids, which coexist in the Northeastern portion of the Peninsula. Our objective was to estimate the wild cats' density population over time at El Eden Ecological Reserve (EEER) and its surrounding areas. Camera trap surveys over four years (2008, 2010, 2011 and 2012) were conducted, and data were obtained with the use of capture-recapture models for closed populations (CAPTURE + MMDM or 1/2 MMDM), and the spatially explicit capture-recapture model (SPACECAP). The species studied were jaguar (Panthera onca), puma (Puma concolor), ocelot (Leopardus pardalis), jaguarundi (Puma yaguaroundi) and margay (Leopardus wiedii). Capture frequency was obtained for all five species and the density for three (individuals/100km2). The density estimated with The Mean Maximum Distance Moved (MMDM), CAPTURE, ranged from 1.2 to 2.6 for jaguars, from 1.7 to 4.3 for pumas and from 1.4 to 13.8 for ocelots. The density estimates in SPACECAP ranged from 0.7 to 3.6 for jaguars, from 1.8 to 5.2 for pumas and 2.1 to 5.1 for ocelots. Spatially explicit capture recapture (SECR) methods in SPACECAP were less likely to overestimate densities, making it a useful tool in the planning and decision making process for the conservation of these species. The Northeastern portion of the Yucatan Peninsula maintains high populations of cats, the EEER and its surrounding areas are valuable sites for the conservation of this group of predators. Rev. Biol.

The worldwide extinction of large terrestrial mammals in the late Pleistocene has been attributed to climate change, overkill by human populations colonizing new continents, or some combination of these two processes. Lack of precision in chronologies for human colonization and mega- faunal extinction suggests that the role of overkill will be difficult or impossible to resolve from the archaeological and fossil record. In this study, we used a simple two species predator-prey model to examine the population density and hunting efficiency of a colonizing Aboriginal population necessary for overkill to have led to extinction (equilibrium density=0), of a range of different sized megafauna (250–1000 kg bodyweight) inhabiting an hypothetical tract of north Australian Eucalyptus savanna. We referred our modelling to this region because estimates of contemporary Aboriginal population density arguably set an upper limit for those occurring during the Pleistocene, and data are available on harvesting rates of large introduced mammals such as buffalo. Modelling results indicated a compensatory trade-off between the effect of Aboriginal population density and hunting efficiency (measured as the rate of effective search for prey) on equilibrium megafauna densities. The modelling also demonstrated that although intrinsic rate of population increase and density at carrying-capacity for mammals increase with declining body size, smaller megafauna would have been more readily exterminated than larger megafauna because they would have been harvested at a higher rate to satisfy the demand for meat. However, while at contemporary Aboriginal densities it appears plausible that over-harvesting could have affected the fate of smaller megafauna (<250 kg), hunting efficiencies required to drive medium (500 kg) and larger (1000 kg) sized megafauna to extinction appear unrealistically high. This conclusion would be reinforced if Aborigines were able to switch prey at low megafauna density, a contingency not considered in our model. Collectively, these results suggest that for overkill to have driven medium to large marsupial megafauna extinct in the northern Eucalyptus savannas, Aboriginal densities must have been considerably higher than contemporary levels, or Aboriginal hunters astonishingly efficient. Alternatively, climate change in the late Pleistocene may have played an important role in the extinction of Australian megafauna.

Incidental sounds produced by Phyllophaga crinita (Burmeister) and Cyclocephala lurida (Bland) (Coleoptera: Scarabaeidae) white grubs were monitored with single- and multiple-sensor acoustic detection systems in turf fields and golf course fairways in Texas. The maximum detection range of an individual acoustic sensor was measured in a greenhouse as approximately the area enclosed in a 26.5-cm-diameter perimeter (552 cm2). A single-sensor acoustic system was used to rate the likelihood of white grub infestation at monitored sites, and a four-sensor array was used to count the numbers of white grubs at sites where infestations were identified. White grub population densities were acoustically estimated by dividing the estimated numbers of white grubs by the area of the detection range. For comparisons with acoustic monitoring methods, infestations were assessed also by examining 10-cm-diameter soil cores collected with a standard golf cup-cutter. Both acoustic and cup-cutter assessments of infestation and estimates of white grub population densities were verified by excavation and sifting of the soil around the sensors after each site was monitored. The single-sensor acoustic method was more successful in assessing infestations at a recording site than was the cup-cutter method, possibly because the detection range was larger than the area of the soil core. White grubs were recovered from >90% of monitored sites rated at medium or high likelihood of infestation. Infestations were successfully identified at 23 of the 24 sites where white grubs were recovered at densities >50/m2, the threshold for economic damage. The four-sensor array yielded the most accurate estimates of the numbers of white grubs in the detection range, enabling reliable, nondestructive estimation of white grub population densities. However, tests with the array took longer and were more difficult to perform than tests with the single sensor.

ABSTRACTMotivationPopulation density is a fundamental parameter in ecology and conservation, and taxonomic and geographic patterns of population density have been an important focus of macroecological research. However, population density data are time‐consuming and costly to collect, so their availability is limited. Leveraging decades of research, TetraDENSITY 1.0 was developed as a global repository containing over 18,000 population density estimates for &gt; 2100 terrestrial vertebrate species, aiding researchers in investigating patterns of population density, its intrinsic and extrinsic drivers, and for developing predictive models. Here we present a substantially expanded version of the database, which now includes marine tetrapods and encompasses over 54,300 estimates for 3717 species associated with error estimates and geographical coordinates when available, hence enabling meta‐analytical approaches and better spatial matching of estimates with environmental conditions.Main Types of Variables ContainedPopulation density estimates and associated errors, time and location of data collection, taxonomic information, estimation method.Spatial LocationGlobal.Time Period and Grain1925–2024.Major Taxa and Level of MeasurementAmphibia, Reptilia, Aves and Mammalia. Estimates reported at the population level.Software Format.csv.

Knowledge on mortality causes is key for an effective management of animal populations and can help to restore depleted fish stocks. Here we investigated the mortality dynamics of coastal Atlantic cod (Gadus morhua) in Skagerrak, southern Norway, by analyzing local mark–recapture and recovery data collected from 2005 to 2013 (N = 9360 fish, mean length = 41 cm, range = 16–93 cm). By applying multi-event models to the data, we could link field observations to multiple “dead states” and estimate the proportion of deaths associated with different fishing gears while controlling for unobserved mortality and detection errors. Deaths due to hand lines and fixed gear types were dominant compared with other causes, especially in legal-sized cod (≥40 cm). Gear-specific mortality changed over time and between size classes, but annual survival remained low and stable (∼0.3). Assuming fully additive mortality, we predicted annual survival of cod to be above 0.5 if only one or both of the dominant gear types were removed, providing insights on the relative impact of diverse harvesting practices on local population dynamics.