Line transect sampling of Karner blue butterflies ( Lycaeides melissa samuelis)

Line transect sampling is an effective survey method for estimating butterfly densities because it provides unbiased estimates of site-density (provided key assumptions are met), and estimates are comparable among sites. For monitoring Karner blue butterflies in Wisconsin, USA, comparable estimates are required because each year a different selection of sites will be monitored. Annual state-wide indices of species abundance can be derived from the site-surveys and compared to previous year's indices to monitor trends. We advocate that line transect sampling is preferable to Pollard-Yates transects as a survey technique for monitoring Karner blue butter- flies. The Pollard-Yates surveys do not adjust for diferences in site detectability. As a consequence, estimates of among-site from Pollard-Yates surveys can be biased. © Rapid Science 1998     

Chilean Blue Whales as a Case Study to Illustrate Methods to Estimate Abundance and Evaluate Conservation Status of Rare Species

Abstract: Often abundance of rare species cannot be estimated with conventional design‐based methods, so we illustrate with a population of blue whales (Balaenoptera musculus) a spatial model‐based method to estimate abundance. We analyzed data from line‐transect surveys of blue whales off the coast of Chile, where the population was hunted to low levels. Field protocols allowed deviation from planned track lines to collect identification photographs and tissue samples for genetic analyses, which resulted in an ad hoc sampling design with increased effort in areas of higher densities. Thus, we used spatial modeling methods to estimate abundance. Spatial models are increasingly being used to analyze data from surveys of marine, aquatic, and terrestrial species, but estimation of uncertainty from such models is often problematic. We developed a new, broadly applicable variance estimator that showed there were likely 303 whales (95% CI 176–625) in the study area. The survey did not span the whales' entire range, so this is a minimum estimate. We estimated current minimum abundance relative to pre‐exploitation abundance (i.e., status) with a population dynamics model that incorporated our minimum abundance estimate, likely population growth rates from a meta‐analysis of rates of increase in large baleen whales, and two alternative assumptions about historic catches. From this model, we estimated that the population was at a minimum of 9.5% (95% CI 4.9–18.0%) of pre‐exploitation levels in 1998 under one catch assumption and 7.2% (CI 3.7–13.7%) of pre‐exploitation levels under the other. Thus, although Chilean blue whales are probably still at a small fraction of pre‐exploitation abundance, even these minimum abundance estimates demonstrate that their status is better than that of Antarctic blue whales, which are still <1% of pre‐exploitation population size. We anticipate our methods will be broadly applicable in aquatic and terrestrial surveys for rarely encountered species, especially when the surveys are intended to maximize encounter rates and estimate abundance.     

The Importance of Analysis Method for Breeding Bird Survey Population Trend Estimates

Population trends from the Breeding Bird Survey are widely used to focus conservation efforts on species thought to be in decline and to test preliminary hypotheses regarding the causes of these declines. A number of statistical methods have been used to estimate population trends, but there is no consensus as to which is the most reliable. We quantified differences in trend estimates or different analysis methods applied to the same subset of Breeding Bird Survey data. We estimated trends for 115 species in British Columbia using three analysis methods: U.S. National Biological Service route regression, Canadian Wildlife Service route regression, and nonparametric rank-trends analysis. Overall, the number of species estimated to be declining was similar among the three methods, but the number of statistically significant declines was not similar (15, 8, and 29 respectively). In addition, many differences existed among methods in the trend estimates assigned to individual species. Comparing the two route regression methods, Canadian Wildlife Service estimates had a greater absolute magnitude on average than those of the U.S. National Biological Service method. U.S. National Biological Service estimates were on average more positive than the Canadian Wildlife Service estimates when the respective agency's data selection criteria were applied separately. These results imply that our ability to detect population declines and to prioritize species of conservation concern depend strongly upon the analysis method used. This highlights the need for further research to determine how best to accurately estimate trends from the data. We suggest a method for evaluating the performance of the analysis methods by using simulated Breeding Bird Survey data.     

Latitudinal variation in abundance of herbivorous fishes: a comparison of temperate and tropical reefs

The aim of the study was to provide comparable estimates of abundance of herbivorous reef fishes at temperate and tropical localities using a standardized methodology. Faunas of herbivorous fish were sampled on the rocky reefs of temperate northern New Zealand and on the coral reefs of the northern Great Barrier Reef (GBR), Australia, and the San Blas Archipelago in the Caribbean. A pilot study established the most appropriate habitat setting and the scale and magnitude of replication for the sampling program in temperate waters. Herbivorous fishes, including members of families endemic to the southern hemisphere (Odacidae and Aplodactylidae), were most abundant in turbulent, shallow water (0 to 6 m) and had patchy distributions within this habitat. A hierarchical sampling program using 10-min transect counts within the 0 to 6 m depth stratum examined abundance patterns at a range of spatial scales including mainland and island coasts, localities separated by up to 100 km and sites separated by up to 10 km. This program identified a characteristic fauna of seven species of herbivorous fishes with mean total abundances ranging from 23 to 30 individuals per 10-min transect. Species composition of the fauna varied between islands and coasts. A similar methodology was used to sample the major families of herbivorous fish in a number of sites in each of the tropical regions. These sampling programs revealed a fauna dominated by acanthurids and scarids in both the GBR and Caribbean localities. Estimates of abundance from these regions were similar, with a mean of 108 individuals recorded on the GBR and 129 per 10-min transect in the Caribbean. Species richness varied between each region, with 44 taxa recorded from the GBR and 11 from the Caribbean. Abundances of temperate water herbivores in New Zealand were found to be 75 to 80% lower than those recorded from shallow water habitats sampled on coral reefs. This was not related to species richness, since both New Zealand and the Caribbean locality had patterns of low richness. We suggest that the differences in abundance found by our study between temperate and tropical regions are not restricted to herbivorous fishes, but are representative of general latitudinal trends in reef fish faunas. Received: 4 November 1996 / Accepted: 15 December 1996     

Evaluating the performance of methods for estimating the abundance of rapidly declining coastal shark populations

Accurately surveying shark populations is critical to monitoring precipitous ongoing declines in shark abundance and interpreting the effects that these reductions are having on ecosystems. To evaluate the effectiveness of existing survey tools, we used field trials and computer simulations to critically examine the operation of four common methods for counting coastal sharks: stationary point counts, belt transects, video surveys, and mark and recapture abundance estimators. Empirical and theoretical results suggest that (1) survey method selection has a strong impact on the estimates of shark density that are produced, (2) standardizations by survey duration are needed to properly interpret and compare survey outputs, (3) increasing survey size does not necessarily increase survey precision, and (4) methods that yield the highest density estimates are not always the most accurate. These findings challenge some of the assumptions traditionally associated with surveying mobile marine animals. Of the methods we trialed, 8 x 50 m belt transects and a 20 m radius point count produced the most accurate estimates of shark density. These findings can help to improve the ways we monitor, manage, and understand the ecology of globally imperiled coastal shark populations.     

Use of Approximate Inference in an Index of Completeness of Biological Inventories

Abstract:  To assess the completeness of a floristic or faunal inventory, one may use the ratio of the observed number of species to the "true number" of species ( C ). If the inventory is complete , C = 1. The estimate of the true number can be obtained from accumulation curves, nonparametric methods, or other techniques. We devised a simple method for computing confidence intervals (CI) for C and for evaluating the null hypothesis that the inventory is complete. The method is based on the assumptions that an estimate of the variance of the true number of species is known and that the distribution of the estimator of the true number of species is approximately normal. We applied our method to bird inventories in the Balsas Basin of Mexico. The completeness index for subtransects were lower (84.0, 85.4, and 89.9%) than for the whole transect (91.6%) (all significantly different from 100%). Thus, these particular inventories were incomplete at 2 spatial resolutions. Our method of estimating CI for C can be used to estimate species richness obtained from databases of different sites or to test the null hypothesis that an inventory derived from a database is complete.     

Determining Optimal Population Monitoring for Rare Butterflies

Abstract: Determining population viability of rare insects depends on precise, unbiased estimates of population size and other demographic parameters. We used data on the endangered St. Francis' satyr butterfly (Neonympha mitchellii francisci) to evaluate 2 approaches (mark–recapture and transect counts) for population analysis of rare butterflies. Mark–recapture analysis provided by far the greatest amount of demographic information, including estimates (and standard errors) of population size, detection, survival, and recruitment probabilities. Mark–recapture analysis can also be used to estimate dispersal and temporal variation in rates, although we did not do this here. Models of seasonal flight phenologies derived from transect counts (Insect Count Analyzer) provided an index of population size and estimates of survival and statistical uncertainty. Pollard–Yates population indices derived from transect counts did not provide estimates of demographic parameters. This index may be highly biased if detection and survival probabilities vary spatially and temporally. In terms of statistical performance, mark–recapture and Pollard–Yates indices were least variable. Mark–recapture estimates were less likely to fail than Insect Count Analyzer, but mark–recapture estimates became less precise as sampling intensity decreased. In general, count‐based approaches are less costly and less likely to cause harm to rare insects than mark–recapture. The optimal monitoring approach must reconcile these trade‐offs. Thus, mark–recapture should be favored when demographic estimates are needed, when financial resources enable frequent sampling, and when marking does not harm the insect populations. The optimal sampling strategy may use 2 sampling methods together in 1 overall sampling plan: limited mark–recapture sampling to estimate survival and detection probabilities and frequent but less expensive transect counts.     

A Possible Method for the Rapid Assessment of Biodiversity

Inventories of vertebrate and flowering plants are frequently used as surrogates for estimates of total biodiversity. This is in part because the inclusion of invertebrates and nonflowering plants is perceived as being too time-consuming, costly, and difficult because of the shortage of specialists. Estimates of the species richness of field samples of spiders, ants, polychaetes, and mosses made by a biodiversity technician and by specialist taxonomists were compared. The biodiversity technician received a few hours training in the taxonomy of each group and separated specimens into recognizable taxonomic units (RTUs). The specialists sorted to species. For the three animal groups the biodiversity technician recorded 165 taxa and the specialists 147, with the error for the ants and spiders being 13% or less. A small amount of splitting and lumping of species was detected. The concordance of estimates remained very similar when small subsamples were used. The procedure was repeated by 13 undergraduates using a subsample of spiders. Their average error was 14.4%. The greatest similarity in estimates was for the mosses, but with high levels of splitting and lumping this result was entirely fortuitous. The results suggest that RTU estimates made by biodiversity technicians may be sufficiently close to formal taxonomic estimates of species richness to be useful for the rapid assessment of biodiversity. They also show, however, that the procedures outlined here should be used on invertebrate and nonflowering plant groups before they can be confidently included in biodiversity surveys.     

两栖动物监测方法和国外监测计划研究

两栖动物是生物多样性的重要组成部分,对环境变化非常敏感,可被用作环境监测的指示物种.介绍了两栖动物监测的指标、时间、频次以及监测的主要方法,包括目视遇测法、样线（带）法、繁殖区调查法、鸣叫调查法、围栏陷阱法、人工庇护所法、人工隐蔽物法和标志重捕法,分析了各种方法的适用性和局限性;还详细介绍了国外比较成熟的2个两栖动物监测计划——美国两栖动物监测计划和英国两栖爬行动物监测计划.     

Multimethod,multistate Bayesian hierarchical modeling approach for use in regional monitoring of wolves

In many cases, the first step in large‐carnivore management is to obtain objective, reliable, and cost‐effective estimates of population parameters through procedures that are reproducible over time. However, monitoring predators over large areas is difficult, and the data have a high level of uncertainty. We devised a practical multimethod and multistate modeling approach based on Bayesian hierarchical‐site‐occupancy models that combined multiple survey methods to estimate different population states for use in monitoring large predators at a regional scale. We used wolves (Canis lupus) as our model species and generated reliable estimates of the number of sites with wolf reproduction (presence of pups). We used 2 wolf data sets from Spain (Western Galicia in 2013 and Asturias in 2004) to test the approach. Based on howling surveys, the naïve estimation (i.e., estimate based only on observations) of the number of sites with reproduction was 9 and 25 sites in Western Galicia and Asturias, respectively. Our model showed 33.4 (SD 9.6) and 34.4 (3.9) sites with wolf reproduction, respectively. The number of occupied sites with wolf reproduction was 0.67 (SD 0.19) and 0.76 (0.11), respectively. This approach can be used to design more cost‐effective monitoring programs (i.e., to define the sampling effort needed per site). Our approach should inspire well‐coordinated surveys across multiple administrative borders and populations and lead to improved decision making for management of large carnivores on a landscape level. The use of this Bayesian framework provides a simple way to visualize the degree of uncertainty around population‐parameter estimates and thus provides managers and stakeholders an intuitive approach to interpreting monitoring results. Our approach can be widely applied to large spatial scales in wildlife monitoring where detection probabilities differ between population states and where several methods are being used to estimate different population parameters.     

Simultaneous-count models to estimate abundance from counts of unmarked individuals with imperfect detection

We developed a method to estimate population abundance from simultaneous counts of unmarked individuals over multiple sites. We considered that at each sampling occasion, individuals in a population could be detected at 1 of the survey sites or remain undetected and used either multinomial or binomial simultaneous-count models to estimate abundance, the latter being equivalent to an N-mixture model with one site. We tested model performance with simulations over a range of detection probabilities, population sizes, growth rates, number of years, sampling occasions, and sites. We then applied our method to 3 critically endangered vulture species in Cambodia to demonstrate the real-world applicability of the model and to provide the first abundance estimates for these species in Cambodia. Our new approach works best when existing methods are expected to perform poorly (i.e., few sites and large variation in abundance among sites) and if individuals may move among sites between sampling occasions. The approach performed better when there were >8 sampling occasions and net probability of detection was high (>0.5). We believe our approach will be useful in particular for simultaneous surveys at aggregation sites, such as roosts. The method complements existing approaches for estimating abundance of unmarked individuals and is the first method designed specifically for simultaneous counts.     

A robust nonparametric method for quantifying undetected extinctions

How many species have gone extinct in modern times before being described by science? To answer this question, and thereby get a full assessment of humanity's impact on biodiversity, statistical methods that quantify undetected extinctions are required. Such methods have been developed recently, but they are limited by their reliance on parametric assumptions; specifically, they assume the pools of extant and undetected species decay exponentially, whereas real detection rates vary temporally with survey effort and real extinction rates vary with the waxing and waning of threatening processes. We devised a new, nonparametric method for estimating undetected extinctions. As inputs, the method requires only the first and last date at which each species in an ensemble was recorded. As outputs, the method provides estimates of the proportion of species that have gone extinct, detected, or undetected and, in the special case where the number of undetected extant species in the present day is assumed close to zero, of the absolute number of undetected extinct species. The main assumption of the method is that the per‐species extinction rate is independent of whether a species has been detected or not. We applied the method to the resident native bird fauna of Singapore. Of 195 recorded species, 58 (29.7%) have gone extinct in the last 200 years. Our method projected that an additional 9.6 species (95% CI 3.4, 19.8) have gone extinct without first being recorded, implying a true extinction rate of 33.0% (95% CI 31.0%, 36.2%). We provide R code for implementing our method. Because our method does not depend on strong assumptions, we expect it to be broadly useful for quantifying undetected extinctions.     

Multi-scale marine biodiversity patterns inferred efficiently from habitat image processing

Cost-effective proxies of biodiversity and species abundance, applicable across a range of spatial scales, are needed for setting conservation priorities and planning action. We outline a rapid, efficient, and low-cost measure of spectral signal from digital habitat images that, being an effective proxy for habitat complexity, correlates with species diversity and requires little image processing or interpretation. We validated this method for coral reefs of the Great Barrier Reef (GBR), Australia, across a range of spatial scales (1 m to 10 km), using digital photographs of benthic communities at the transect scale and high-resolution Landsat satellite images at the reef scale. We calculated an index of image-derived spatial heterogeneity, the mean information gain (MIG), for each scale and related it to univariate (species richness and total abundance summed across species) and multivariate (species abundance matrix) measures of fish community structure, using two techniques that account for the hierarchical structure of the data: hierarchical (mixed-effect) linear models and distance-based partial redundancy analysis. Over the length and breadth of the GBR, MIG alone explained up to 29% of deviance in fish species richness, 33% in total fish abundance, and 25% in fish community structure at multiple scales, thus demonstrating the possibility of easily and rapidly exploiting spatial information contained in digital images to complement existing methods for inferring diversity and abundance patterns among fish communities. Thus, the spectral signal of unprocessed remotely sensed images provides an efficient and low-cost way to optimize the design of surveys used in conservation planning. In data-sparse situations, this simple approach also offers a viable method for rapid assessment of potential local biodiversity, particularly where there is little local capacity in terms of skills or resources for mounting in-depth biodiversity surveys.     

A combination line transect and capture-recapture sampling model for multiple observers in aerial surveys

We present a robust sampling methodology to estimate population size using line transect and capture-recapture procedures for aerial surveys. Aerial surveys usually underestimate population density due to animals being missed. A combination of capture-recapture and line transect sampling methods with multiple observers allows violation of the assumption that all animals on the centreline are sighted from the air. We illustrate our method with an example of inanimate objects which shows evidence of failure of the assumption that all objects on the centreline have probability 1 of being detected. A simulation study is implemented to evaluate the performance of three variations of the Lincoln-Petersen estimator: the overall estimator, the stratified estimator, and the general stratified estimator based on the combined likelihood proposed in this paper. The stratified Lincoln-Petersen estimator based on the combined likelihood is found to be generally superior to the other estimators.     

Animal abundance estimation in independent observer line transect surveys

The theory of conventional line transect surveys is based on an essential assumption that 100% detection of animals right on the transect lines can be achieved. When this assumption fails, independent observer line transect surveys are used. This paper proposes a general approach, based on a conditional likelihood, which can be carried out either parametrically or nonparametrically, to estimate the abundance of non-clustered biological populations using data collected from independent observer line transect surveys. A nonparametric estimator is specifically proposed which combines the conditional likelihood and the kernel smoothing method. It has the advantage that it allows the data themselves to dictate the form of the detection function, free of any subjective choice. The bias and the variance of the nonparametric estimator are given. Its asymptotic normality is established which enables construction of confidence intervals. A simulation study shows that the proposed estimator has good empirical performance, and the confidence intervals have good coverage accuracy.     

Estimating nonlinear interaction strengths: an observation-based method for species-rich food webs

Efforts to estimate the strength of species interactions in species-rich, reticulate food webs have been hampered by the multitude of direct and indirect interactions such systems exhibit and have been limited by an assumption that pairwise interactions display linear functional forms. Here we present a new method for directly measuring, on a per capita basis, the nonlinear strength of trophic species interactions within such food webs. This is an observation-based method, requiring three pieces of information: (1) species abundances, (2) predator and prey-specific handling times, and (3) data from predator-specific feeding surveys in which the number of individuals observed feeding on each of the predator's prey species has been tallied. The method offers a straightforward way to assess the completeness of one's sampling effort in accurately estimating interaction strengths through the construction of predator-specific prey accumulation curves. The method should be applicable to a variety of systems in which empirical estimates of direct interaction strengths have thus far remained elusive.     

Extinction and Colonization of Birds on Habitat Islands

Abstract: We used point-count and transect surveys to estimate the distribution and abundance of eight scrub-breeding bird species in 34 habitat fragments and the urban matrix in southern California. We then calculated local extinction and colonization rates by comparing our data with surveys conducted in 1987. We classified factors that influence extinction and colonization rates into two types: (1) extrinsic factors, which are characteristics of the habitat fragments such as area, age, and isolation and (2) intrinsic factors, which are characteristics of the species that inhabit fragments, such as body size and population density. Over the past decade, at least one species went locally extinct in over 50% of the fragments, and local extinctions were almost twice as common as colonizations. Fragment size and, to a lesser extent, fragment age were the most important extrinsic factors determining extinction and colonization. Density indices of scrub birds were the most important intrinsic factors determining extinction rates, predicting the number of sites occupied, the probability of local extinction, relative area requirements, and time to local extinction.     

Effects of Recent Environmental Change on Accuracy of Inferences of Extinction Status

Correctly classifying a species as extinct or extant is of critical importance if current rates of biodiversity loss are to be accurately quantified. Observing an extinction event is rare, so in many cases extinction status is inferred using methods based on the analysis of records of historic sighting events. The accuracy of such methods is difficult to test. However, results of recent experiments with microcosm communities suggest that the rate at which a population declines to extinction, potentially driven by varying environmental conditions, may alter one's ability accurately to infer extinction status. We tested how the rate of population decline, driven by historic environmental change, alters the accuracy of 6 commonly applied sighting‐based methods used to infer extinction. We used data from small‐scale experimental communities and recorded wild population extirpations. We assessed how accuracy of the different methods was affected by rate of population decline, search effort, and number of sighting events recorded. Rate of population decline and historic population size of the species affected the accuracy of inferred extinction dates; however, faster declines produced more accurate inferred dates of extinction, but only when population sizes were higher. Optimal linear estimation (OLE) offered the most reliable and robust estimates, though no single method performed best in all situations, and it may be appropriate to use a different method if information regarding historic search efforts is available. OLE provided the most accurate estimates of extinction when the number of sighting events used was >10, and future use of this method should take this into account. Data from experimental populations provide added insight into testing techniques to discern wild extirpation events. Care should be taken designing such experiments so that they mirror closely the abundance dynamics of populations affected by real‐world extirpation events. Efectos del Cambio Ambiental Reciente sobre la Precisión de las Inferencias sobre el Estado de Extinción     

Estimation of population density by spatially explicit capture-recapture analysis of data from area searches

The recent development of capture-recapture methods for estimating animal population density has focused on passive detection using devices such as traps or automatic cameras. Some species lend themselves more to active searching: a polygonal plot may be searched repeatedly and the locations of detected individuals recorded, or a plot may be searched just once and multiple cues (feces or other sign) identified as belonging to particular individuals. This report presents new likelihood-based spatially explicit capture-recapture (SECR) methods for such data. The methods are shown to be at least as robust in simulations as an equivalent Bayesian analysis, and to have negligible bias and near-nominal confidence interval coverage with parameter values from a lizard data set. It is recommended on the basis of simulation that plots for SECR should be at least as large as the home range of the target species. The R package "secr" may be used to fit the models. The likelihood-based implementation extends the spatially explicit analyses available for search data to include binary data (animal detected or not detected on each occasion) or count data (multiple detections per occasion) from multiple irregular polygons, with or without dependence among polygons. It is also shown how the method may be adapted for detections along a linear transect.     

Spatial variability in habitat associations of pre- and post-settlement stages of coral reef fishes at Ishigaki Island,Japan

Successful settlement of pelagic fish larvae into benthic juvenile habitats may be enhanced by a shortened settlement period, since it limits larval exposure to predation in the new habitat. Because the spatial distribution of marine fish larvae immediately prior to settlement versus during settlement was unknown, field experiments were conducted at Ishigaki Island (Japan) using light trap sampling and underwater visual belt transect surveys to investigate the spatial distribution patterns of selected pre- and post-settlement fishes (Acanthuridae, Pomacentridae, Chaetodonidae and Lethrinidae) among four habitats (seagrass bed, coral rubble, branching coral and tabular coral). The results highlighted two patterns: patterns 1, pre- and post-settlement individuals showing a ubiquitous distribution among the four habitats (Acanthuridae) and pattern 2, pre-settlement individuals distributed in all habitats, but post-settlement individuals restricted to coral (most species of Pomacentridae and Chaetodontidae) or seagrass habitats (Lethrinidae). The first pattern minimizes the transition time between the larval pelagic stage and acquisition of a benthic reef habitat, the latter leading immediately to a juvenile lifestyle. In contrast, the second pattern is characterized by high settlement habitat selectivity by larvae and/or differential mortality immediately after settlement.