Uncertainty In Population Estimates Research Articles

Generating unbiased estimates of burrowing seabird populations

Maximising survey efficiency can help reduce the tradeoff between spending limited conservation resources on identifying population changes and responding to those changes through management. Burrow‐nesting seabirds are particularly challenging to survey because nests cannot be counted directly. We evaluated a stratified random survey design for generating unbiased population estimates simultaneously for four petrel species nesting on Macquarie Island, Australia, where the survey cue, burrow entrances, is similar for all species. We also compared the use of design‐based and model‐based analyses for minimising uncertainty in estimates. We recorded 2845 Antarctic prion burrows, 306 white‐headed petrel burrows and two blue petrel burrows while distance‐sampling along 154 km of transects. For blue petrels and grey petrels, we completed nocturnal searches along a further 71 km and searched 249 km of tracks during follow‐up ground searches. We failed to generate unbiased population estimates for two rare and localised species, blue and grey petrels, from our stratified random survey. Only for the most widespread and abundant species, Antarctic prion, did the estimate have reasonable power to detect a rapid population change. Model‐based analyses of the stratified random survey data did not improve upon traditional design‐based analyses in terms of uncertainty in population estimates, but they did provide useful spatial representation of current populations. Models that used the targeted survey data did not reflect current population sizes and distributions of the two rare and localised species. We found that when species ecologies, distributions and abundances vary, a multi‐method approach to surveys is needed. Species with low abundance that occur patchily across large islands are likely to be best estimated using targeted surveys, whereas widespread and abundant species can be accurately and precisely estimated from randomised surveys using informative model‐based analyses.

Estimates of marine turtle nesting populations in the south-west Indian Ocean indicate the importance of the Chagos Archipelago

AbstractGlobal marine turtle population assessments highlight the importance of the south-west Indian Ocean region, despite data gaps for the Chagos Archipelago. The archipelago hosts nesting hawksbill Eretmochelys imbricata and green turtles Chelonia mydas, both heavily exploited for 2 centuries until protection in 1968–1970. We assessed available nesting habitat and spatial distribution of nesting activity during rapid surveys of 90% of the archipelago's coastline in 1996, 1999, 2006 and 2016. We quantified seasonality and mean annual egg clutch production from monthly track counts during 2006–2018 along a 2.8 km index beach on Diego Garcia island. An estimated 56% (132 km) of coastline provided suitable nesting habitat. Diego Garcia and Peros Banhos atolls accounted for 90.4% of hawksbill and 70.4% of green turtle nesting. Hawksbill turtles showed distinct nesting peaks during October–February, and green turtles nested year-round with elevated activity during June–October. Estimates of 6,300 hawksbill and 20,500 green turtle clutches laid annually during 2011–2018 indicate that nesting on the Chagos Archipelago has increased 2–5 times for hawksbill turtles and 4–9 times for green turtles since 1996. Regional estimates indicate green turtles produce 10 times more egg clutches than hawksbill turtles, and the Chagos Archipelago accounts for 39–51% of an estimated 12,500–16,000 hawksbill and 14–20% of an estimated 104,000–143,500 green turtle clutches laid in the south-west Indian Ocean. The improved status may reflect > 40 years without significant exploitation. Long-term monitoring is needed to captureinterannual variation in nesting numbers and minimize uncertainty in population estimates.

Modelling the rate of successful search of red foxes during population control

Context Relative abundance indices of wildlife can be scaled to give estimates of absolute abundance. Choice of scaling parameter depends on the data available and assumptions made about the relationship between the index and absolute abundance. Predation-mechanics theory suggests that a parameterisation involving the rate of successful search, s, will be useful where the area searched is unknown. An example arises during fox culling on shooting estates in Britain, where detection and cull data from gamekeepers using a spotlight and rifle are available, and can potentially be used to understand the population dynamics of the local population. Aims We aimed to develop an informative prior for s for use within a Bayesian framework to fit a fox population-dynamics model to detection data. Methods We developed a mechanistic model with a rate of successful search parameter for the gamekeeper–fox system. We established a mechanistic prior for s, using Monte Carlo simulation to combine relevant information on its component factors (detection probability, observer field of view and speed of travel). We obtained empirical estimates of s from a distance-sampling study of fox populations using similar survey methods, and used these as data in a Bayesian model to develop a mechanistic–empirical prior. We then applied this informative prior within a state–space model to estimate fox density from fox-detection rate on four estates. Key results The mechanistic–empirical prior for the rate of successful search was lognormally distributed with a median of 2.01 km2 h–1 (CV = 0.56). Underlying assumptions of the parameterisation were met. Local fox-density estimates obtained using informative priors closely reflected regional density. Conclusions A mechanistic understanding of the search process leading to fox detections by gamekeepers, and the use of Bayesian models, allowed the use of diverse sources of information to develop an informative prior for s that was useful in estimating fox density from detection data. Implications Careful use of prior knowledge within a Bayesian modelling framework can reduce uncertainty in population estimates derived from index data, and lead to improved management decisions. The mechanistic approach we have used will have parallel applications in many other contexts.

Impact of in-Sewer Degradation of Pharmaceutical and Personal Care Products (PPCPs) Population Markers on a Population Model.

A key uncertainty of wastewater-based epidemiology is the size of the population which contributed to a given wastewater sample. We previously developed and validated a Bayesian inference model to estimate population size based on 14 population markers which: (1) are easily measured and (2) have mass loads which correlate with population size. However, the potential uncertainty of the model prediction due to in-sewer degradation of these markers was not evaluated. In this study, we addressed this gap by testing their stability under sewer conditions and assessed whether degradation impacts the model estimates. Five markers, which formed the core of our model, were stable in the sewers while the others were not. Our evaluation showed that the presence of unstable population markers in the model did not decrease the precision of the population estimates providing that stable markers such as acesulfame remained in the model. However, to achieve the minimum uncertainty in population estimates, we propose that the core markers to be included in population models for other sites should meet two additional criteria: (3) negligible degradation in wastewater to ensure the stability of chemicals during collection; and (4) < 10% in-sewer degradation could occur during the mean residence time of the sewer network.

Uncertainty in Population Estimates for Endangered Animals and Improving the Recovery Process.

Simple SummaryThe objective of our study was to evaluate the mention of uncertainty (i.e., variance) associated with population size estimates within U.S. recovery plans for endangered animals. To do this we reviewed all finalized recovery plans for listed terrestrial vertebrate species. We found that more recent recovery plans reported more estimates of population size and uncertainty. Also, bird and mammal recovery plans reported more estimates of population size and uncertainty. We recommend that updated recovery plans combine uncertainty of population size estimates with a minimum detectable difference to aid in successful recovery. United States recovery plans contain biological information for a species listed under the Endangered Species Act and specify recovery criteria to provide basis for species recovery. The objective of our study was to evaluate whether recovery plans provide uncertainty (e.g., variance) with estimates of population size. We reviewed all finalized recovery plans for listed terrestrial vertebrate species to record the following data: (1) if a current population size was given, (2) if a measure of uncertainty or variance was associated with current estimates of population size and (3) if population size was stipulated for recovery. We found that 59% of completed recovery plans specified a current population size, 14.5% specified a variance for the current population size estimate and 43% specified population size as a recovery criterion. More recent recovery plans reported more estimates of current population size, uncertainty and population size as a recovery criterion. Also, bird and mammal recovery plans reported more estimates of population size and uncertainty compared to reptiles and amphibians. We suggest the use of calculating minimum detectable differences to improve confidence when delisting endangered animals and we identified incentives for individuals to get involved in recovery planning to improve access to quantitative data.

Basin characteristics and temperature improve abundance estimates from standard index netting of rainbow trout (Oncorhynchus mykiss) in small lakes

Fisheries management often requires efficient methods for assessing populations across a variety of sampling units. We develop a model to assess the status of rainbow trout (Oncorhynchus mykiss) in lakes using a fixed length of multimesh gillnets. We use mark-recapture data to examine how gillnet capture efficiency varies with lake-basin characteristics. Once we accounted for variation in lake-size (net-effort density), we found that capture efficiency was best explained by surface water temperature at the time of gillnetting and lake-basin characteristics (proportion of littoral area). We use Bayesian techniques to fit our model to the data and explore how uncertainty in the estimated parameters leads to uncertainty in population estimates. Our analysis suggests that lake size, temperature and the proportion of littoral area can be used to predict population size using this index netting method. In addition to providing density estimates, our results help to better understand how fish ecology and behavior influences gillnet catches.

Sea turtle population estimates incorporating uncertainty: a new approach applied to western North Atlantic loggerheads Caretta caretta

Loggerhead sea turtles Caretta caretta have been listed as threatened under the US Endangered Species Act since 1978, and a change in their listing status to endangered was recently under consideration. Estimates of adult population size are needed to evaluate population status, but include a number of uncertainties. A point estimate of loggerhead population size based on a nest count fails to convey the range of our uncertainty in the estimated number of indi- viduals in a population. We developed distributions of adult female loggerhead subpopulation sizes for 5 subpopulations of the western North Atlantic, and for the western North Atlantic popu- lation as a whole. Distributions were derived by re-sampling from available nest counts (2001�2010) and data on breeding interval, survival and clutch frequency, each affecting the extrapolation of nest numbers to adult females. Our best estimate for the western North Atlantic adult female loggerhead population was 38 334 (SD = 2287) adult females. Confidence limits on estimates for the individual subpopulations ranged from a high of 45 058 adult females for Penin- sular Florida to a low of 258 adult females in the Dry Tortugas. To reduce uncertainty in population estimates, research needs to focus on quantifying breeding interval and clutch frequency, espe- cially in the less-studied subpopulations.