Effectiveness of scat-detection dogs in determining species presence in a tropical savanna landscape.

Most protected areas are too small to sustain populations of wide-ranging mammals; thus, identification and conservation of high-quality habitat for those animals outside parks is often a high priority, particularly for regions where extensive land conversion is occurring. This is the case in the vicinity of Emas National Park, a small protected area in the Brazilian Cerrado. Over the last 40 years the native vegetation surrounding the park has been converted to agriculture, but the region still supports virtually all of the animals native to the area. We determined the effectiveness of scat-detection dogs in detecting presence of five species of mammals threatened with extinction by habitat loss: maned wolf (Chrysocyon brachyurus), puma (Puma concolor), jaguar (Panthera onca), giant anteater (Myrmecophaga tridactyla), and giant armadillo (Priodontes maximus). The probability of scat detection varied among the five species and among survey quadrats of different size, but was consistent across team, season, and year. The probability of occurrence, determined from the presence of scat, in a randomly selected site within the study area ranged from 0.14 for jaguars, which occur primarily in the forested areas of the park, to 0.91 for maned wolves, the most widely distributed species in our study area. Most occurrences of giant armadillos in the park were in open grasslands, but in the agricultural matrix they tended to occur in riparian woodlands. At least one target species occurred in every survey quadrat, and giant armadillos, jaguars, and maned wolves were more likely to be present in quadrats located inside than outside the park. The effort required for detection of scats was highest for the two felids. We were able to detect the presence for each of five wide-ranging species inside and outside the park and to assign occurrence probabilities to specific survey sites. Thus, scat dogs provide an effective survey tool for rare species even when accurate detection likelihoods are required. We believe the way we used scat-detection dogs to determine the presence of species can be applied to the detection of other mammalian species in other ecosystems.

Correction: A statistical test and sample size recommendations for comparing community composition following PCA.

[This corrects the article DOI: 10.1371/journal.pone.0206033.].

A statistical test and sample size recommendations for comparing community composition following PCA.

Many investigations of anthropogenic and natural impacts in ecological systems attempt to detect differences in ecological variables or community composition. Frequently, ordination procedures such as principal components analysis (PCA) or canonical correspondence analysis (CCA) are used to simplify such complex data sets into a set of primary factors that express the variation across the original variables. Scatterplots of the first and second principal components are then used to visually inspect for differences in community composition between treatment groups. We present a multidimensional extension of analysis of variance based on an analysis of distance (ANODIS) that can be used to formally test for differences in community composition using 1, 2, or more dimensions of a PCA or CCA of the original sample observations. The statistical tests of significance are based on F-statistics adapted for the analysis of this multidimensional data. Because the analysis is parametric, power and sample size calculations useful in the design of field studies can be readily computed. The use of ANODIS is illustrated using bivariate PCA scatterplots from three published studies. Statistical power calculations using the noncentral F-distribution are illustrated.

Three-dimensional migration behavior of juvenile salmonids in reservoirs and near dams.

To acquire 3-D tracking data on juvenile salmonids, Juvenile Salmon Acoustic Telemetry System (JSATS) cabled hydrophone arrays were deployed in the forebays of two dams on the Snake River and at a mid-reach reservoir between the dams. The depth distributions of fish were estimated by statistical analyses performed on large 3-D tracking data sets from ~33,500 individual acoustic tagged yearling and subyearling Chinook salmon and juvenile steelhead at the two dams in 2012 and subyearling Chinook salmon at the two dams and the mid-reach reservoir in 2013. This research investigated the correlation between vertical migration behavior and passage routes. The depth distributions of fish within the forebays of the dams were significantly different from fish passing the mid-reach reservoir. Fish residing deeper in the forebay tended to pass the dam using deeper powerhouse routes. This difference in depth distributions indicated that the depth distribution of fish at the mid-reach reservoir was not related to behaviors of fish passing through certain routes of the adjacent dams. For fish that were detected deeper than 17.5 m in the forebays, the probability of powerhouse passage (i.e., turbine) increased significantly. Another important finding was the variation in depth distributions during dam passage associated with the diel period, especially the crepuscular periods.

Migration depth and residence time of juvenile salmonids in the forebays of hydropower dams prior to passage through turbines or juvenile bypass systems: implications for turbine-passage survival.

Little is known about the three-dimensional depth distributions in rivers of individually marked fish that are in close proximity to hydropower facilities. Knowledge of the depth distributions of fish approaching dams can be used to understand how vulnerable fish are to injuries such as barotrauma as they pass through dams. To predict the possibility of barotrauma injury caused by pressure changes during turbine passage, it is necessary to understand fish behaviour relative to acclimation depth in dam forebays as they approach turbines. A guiding study was conducted using high-resolution three-dimensional tracking results of salmonids implanted with Juvenile Salmon Acoustic Telemetry System transmitters to investigate the depth distributions of subyearling and yearling Chinook salmon (Oncorhynchus tshawytscha) and juvenile steelhead (Oncorhynchus mykiss) passing two dams on the Snake River in Washington State. Multiple approaches were evaluated to describe the depth at which fish were acclimated, and statistical analyses were performed on large data sets extracted from ∼28 000 individually tagged fish during 2012 and 2013. Our study identified patterns of depth distributions of juvenile salmonids in forebays prior to passage through turbines or juvenile bypass systems. This research indicates that the median depth at which juvenile salmonids approached turbines ranged from 2.8 to 12.2 m, with the depths varying by species/life history, year, location (which dam) and diel period (between day and night). One of the most enlightening findings was the difference in dam passage associated with the diel period. The amount of time that turbine-passed fish spent in the immediate forebay prior to entering the powerhouse was much lower during the night than during the day. This research will allow scientists to understand turbine-passage survival better and enable them to assess more accurately the effects of dam passage on juvenile salmon survival.

Dynamics of a transferrin polymorphism in a population of Sylvilagus nuttallii.

Frequencies of three codominant alleles at the transferrin (Tf) locus and four of the six possible genotypes in a population of Nuttall's cottontails Sylvilagus nuttallii on an 87-ha study area in central Oregon were determined for parental stocks, trappable offspring, and over-winter survivors in 1974 and 1975. One rare allele disappeared during winter 1974-75 and did not reappear during the study. The Tf genotype frequency shifted in favor of Tf-BB between parents and offspring in 1974, remained stable over winter, shifted in favor of Tf-BC (to near the original frequency) between parents and offspring in 1975 and remained stable over winter. Allele and genotype frequencies were significantly different between 1974 and 1975 offspring; differences in frequencies between other samples were not significant because of the small number of cottontails that survived to spring each year. We were unable to discount the possibility of non-random breeding being responsible for observed differences, but, because survival of juveniles was related to moisture available for plant growth (and presumably to the moisture content in forage) during the cottontail breeding season and because frequencies of Tf genotypes of the four litters produced each year seemed related to available moisture, we postulated that precipitation was the selective force responsible for shifts in allele and genotype frequencies. Although we were unable to ascertain the probability that the polymorphism was balanced, the stochastic precipitation pattern seemed adequate to prevent fixation of an allele by selection if the selective mechanism was as postulated.

Random effects models and multistage estimation procedures for statistical population reconstruction of small game populations.

Recently, statistical population models using age-at-harvest data have seen increasing use for monitoring of harvested wildlife populations. Even more recently, detailed evaluation of model performance for long-lived, large game animals indicated that the use of random effects to incorporate unmeasured environmental variation, as well as second-stage Horvitz-Thompson-type estimators of abundance, provided more reliable estimates of total abundance than previous models. We adapt this new modeling framework to small game, age-at-harvest models with only young-of-the-year and adult age classes. Our Monte Carlo simulation results indicate superior model performance for the new modeling framework, evidenced by lower bias and proper confidence interval coverage. We apply this method to male wild turkey harvest in the East Ozarks turkey productivity region, Missouri, USA, where statistical population reconstruction indicates a relatively stationary population for 1996-2010.

Comparison of statistical population reconstruction using full and pooled adult age-class data.

BACKGROUND: Age-at-harvest data are among the most commonly collected, yet neglected, demographic data gathered by wildlife agencies. Statistical population construction techniques can use this information to estimate the abundance of wild populations over wide geographic areas and concurrently estimate recruitment, harvest, and natural survival rates. Although current reconstruction techniques use full age-class data (0.5, 1.5, 2.5, 3.5, … years), it is not always possible to determine an animal's age due to inaccuracy of the methods, expense, and logistics of sample collection. The ability to inventory wild populations would be greatly expanded if pooled adult age-class data (e.g., 0.5, 1.5, 2.5+ years) could be successfully used in statistical population reconstruction. METHODOLOGY/PRINCIPAL FINDINGS: We investigated the performance of statistical population reconstruction models developed to analyze full age-class and pooled adult age-class data. We performed Monte Carlo simulations using a stochastic version of a Leslie matrix model, which generated data over a wide range of abundance levels, harvest rates, and natural survival probabilities, representing medium-to-big game species. Results of full age-class and pooled adult age-class population reconstructions were compared for accuracy and precision. No discernible difference in accuracy was detected, but precision was slightly reduced when using the pooled adult age-class reconstruction. On average, the coefficient of variation (i.e., SE(θ)/θ) increased by 0.059 when the adult age-class data were pooled prior to analyses. The analyses and maximum likelihood model for pooled adult age-class reconstruction are illustrated for a black-tailed deer (Odocoileus hemionus) population in Washington State. CONCLUSIONS/SIGNIFICANCE: Inventorying wild populations is one of the greatest challenges of wildlife agencies. These new statistical population reconstruction models should expand the demographic capabilities of wildlife agencies that have already collected pooled adult age-class data or are seeking a cost-effective method for monitoring the status and trends of our wild resources.