Variation In Density Estimates Research Articles

Distance sampling survey effort to improve density estimates of northern bobwhite

AbstractDistance sampling from aerial platforms can provide researchers with precise and efficient density estimates for wildlife populations, particularly over large areas. The intensity of the distance sampling survey depends on the survey effort. Effort can be referred to as coverage, where transect spacing is determined by the observer's sightability distance of the object or animal. Managers and researchers in Texas often use helicopters to survey and collect data for northern bobwhite (Colinus virginianus) density estimates. For bobwhites, 100% coverage represents transect spacing of 200 m, assuming observers can cover out to 100 m on either side of the transects. Often surveys are conducted at 50% coverage or 400 m spacing to reduce cost. Still, the implications of lowering survey effort on the precision of density estimates are unknown, particularly in coverage prescriptions. We flew 2,641 km of line transects each December from 2014 to 2017 and detected 2,333 bobwhite coveys across 7,648 ha of rangeland on the San Antonio Viejo Ranch in Jim Hogg County, TX, USA. We conducted line‐transect distance sampling from a helicopter platform at 50 and 100% coverage and simulated results at coverage <50% using empirical data. Based on the results of simulated surveys at <100% coverage, surveying for bobwhites using helicopters with less than 50% coverage results in variable density estimates (wide 95% confidence intervals) and low precision (coefficient of variation >20%). Empirical surveys conducted at 50 and 100% coverage show little variation in density estimates between the 2 levels of coverage. However, when broken into substrata (areas less than ~1,000 ha), conducting surveys at 50% coverage resulted in <60 detections, which led to low precision in density estimates (coefficient of variation >20%). Our results are based on surveys conducted at the juncture of the Coastal Sand Sheet and Tamaulipan Thorn Scrub ecoregions in south Texas and need to be evaluated in other arid and semi‐arid rangeland systems.

Spatially explicit capture recapture density estimates: Robustness, accuracy and precision in a long-term study of jaguars (Panthera onca).

Camera trapping is the standard field method of monitoring cryptic, low-density mammal populations. Typically, researchers run camera surveys for 60 to 90 days and estimate density using closed population spatially explicit capture-recapture (SCR) models. The SCR models estimate density, capture probability (g0), and a scale parameter (σ) that reflects ranging behaviour. We used a year of camera data from 20 camera stations to estimate the density of male jaguars (Panthera onca) in the Cockscomb Basin Wildlife Sanctuary in Belize, using closed population SCR models. We subsampled the dataset into 276 90-day sessions and 186 180-day sessions. Estimated density fluctuated from 0.51 to 5.30 male jaguars / 100 km2 between the 90-day sessions, with comparatively robust and precise estimates for the 180-day sessions (0.73 to 3.75 male jaguars / 100 km2). We explain the variation in density estimates from the 90-day sessions in terms of temporal variation in social behaviour, specifically male competition and mating events during the three-month wet season. Density estimates from the 90-day sessions varied with σ, but not with the number of individuals detected, suggesting that variation in density was almost fully attributable to changes in estimated ranging behaviour. We found that the models overestimated σ when compared to the mean ranging distance derived from GPS tracking data from two collared individuals in the camera grid. Overestimation of σ when compared to GPS collar data was more pronounced for the 180-day sessions than the 90-day sessions. We conclude that one-off ('snap-shot') short-term, small-scale camera trap surveys do not sufficiently sample wide-ranging large carnivores. When using SCR models to estimate the density from these data, we caution against the use of poor sampling designs and/or misinterpretation of scope of inference. Although the density estimates from one-off, short-term, small-scale camera trap surveys may be statistically accurate within each short-term sampling period, the variation between density estimates from multiple sessions throughout the year illustrate that the estimates obtained should be carefully interpreted and extrapolated, because different factors, such as temporal stochasticity in behaviour of a few individuals, may have strong repercussions on density estimates. Because of temporal variation in behaviour, reliable density estimates will require larger samples of individuals and spatial recaptures than those presented in this study (mean +/- SD = 14.2 +/- 1.2 individuals, 37.7 +/- 4.7 spatial recaptures, N = 276 sessions), which are representative of, or higher than published sample sizes. To satisfy the need for larger samples, camera surveys will need to be more expansive with a higher density of stations. In the absence of this, we advocate longer sampling periods and subsampling through time as a means of understanding and describing stability or variation between density estimates.

Track surveys do not provide accurate or precise lion density estimates in serengeti

More than 60% of the world's large carnivore species are threatened with extinction. Enumerating species abundance is critical for assessing their conservation status in response to anthropogenic threats and environmental stochasticity. Track surveys are commonly used to estimate abundance and density of large carnivore species, including lions (Panthera leo), but their suitability for estimating species abundance has been challenged. Recently developed regression models for track surveys of African large carnivores offer improvements over previous density estimators but have not been independently validated. We conducted weekly track surveys for lions in southeastern Serengeti National Park during 2015–2016 and applied one of these recent regression models, comparing corresponding lion densities to an independent density estimate in 2015 derived from a repeated call-in survey conducted during the same season. We surveyed 3289 km for tracks in total with overall lion densities of 41.2 (95% confidence limits [CL] = 31.9–57.9)/100 km2 in 2015 and 34.6 (26.8–46.0)/100 km2 in 2016. Within year point estimates of lion density varied up to 56% among weeks, though 95% CLs overlapped. Overall annual CLs from the track survey in 2015 did not overlap with the 95% credible interval from the estimate of lion density using a repeated call-in survey (14.36 lions/100 km2; 95% CrI = 9.04–29.31), suggesting overestimation of lion densities using track surveys in 2015. High between-year and among-week variation in density estimates from track surveys suggests that lion use of roads for movement varied over time and that other factors (e.g., prey distribution, luminosity) influenced lion movements independent of road distributions. We recommend caution when applying current track survey methods for estimating lion density and support application of survey designs that include direct observation of lions (e.g., call-in surveys), account for imperfect detection in a spatially-explicit framework, and incorporate environmental variables (e.g., prey, land cover) that can influence lion space use and movements.

Field Application of Sustained-Yield Harvest Management for Northern Bobwhite in Texas

Sustained-yield harvest (SYH) is considered a potentially viable strategy for managing harvest of northern bobwhites (Colinus virginianus). However, application of SYH has not been evaluated for northern bobwhites. We evaluated the application of using SYH as a harvest management strategy for bobwhite during the 2007 2008 and 2008 2009 hunting seasons in 2 ecoregions of Texas (Rolling Plains, South Texas Plains). We collected field data at 3 study sites/ecoregion (900 1,900 ha each; 2 hunted sites and 1 control) to estimate 4 demographic parameters (fall and spring density, overwinter survival in the absence of hunting, and harvest rate). We used these data to parameterize the additive harvest model for bobwhites and compare predictions of spring abundance of the model with field estimates. The additive harvest model, compared to field estimates, consistently underestimated spring population density (mean 6 SE) by 55.7 6 17.8% (2007 2008) and 34.1 6 4.9% (2008 2009) in the Rolling Plains, and by 26.4 6 25.3% (2007 2008) and 49.1 6 2.1% (2008 2009) in the South Texas Plains. Implementing SYH in the field, despite its potential benefits, will be challenging given the need for reliable estimates of 3 key population parameters (fall and spring density, and natural mortality in the absence of hunting) and the high variation often associated with them. Conservative harvest prescriptions based on the lower 95% CIs of fall density estimates may permit sustainable harvest despite variation in density estimates.

A novel data assimilation technique for the plasmasphere

AbstractWe present a novel technique for imaging and data assimilation of the topside ionosphere and plasmasphere. The methodology is based upon the three‐dimensional variational technique (3DVAR), where an empirical background model is utilized. However, to prevent nonphysical vertical variation in density estimates, we devise statistical methods to enforce a roughness penalty in the traditional 3DVAR optimization. The upward looking total electron content (TEC) observations from the Global Positioning System (GPS) receiver on board Constellation Observing System for Meteorology, Ionosphere and Climate satellites are utilized in the assimilation algorithm. The estimation results show reasonable agreement with in situ density measurements of Defense Meteorological Satellite Program satellites and Van Allen Probes derived densities during geomagnetically quiet and severe storm time conditions, respectively. These preliminary results demonstrate great potential for the use of GPS TEC measurements from low‐Earth orbit satellites in monitoring and studying the morphology and dynamics of large‐scale structures of the electron density in the topside ionosphere and plasmasphere.

The contribution of abiotic and biotic factors to spatial and temporal variation in population density of the least killifish, Heterandria formosa

We report the results of a long-term examination of variation in adult density in the least killifish, Heterandria formosa, and the associations among adult density and a variety of ecological factors. We used data from 11 populations of H. formosa in Northwest Florida, collected between 2000 and 2010, to examine the relationships among temporal and spatial variation in adult density and (1) the composition of the aquatic fauna community among habitats (springs, ponds, and tidal marshes) where H. formosa are found, (2) an index of predation pressure and (3) the sampling season, distance from shore (cm), water depth (cm), and aquatic vegetation cover (%) in throw traps at each sampling event. We found clear evidence that adult densities of H. formosa vary widely but consistently among populations, with greater spatial variation than temporal variation in density estimates. Site identity explained most of the variation in density among populations, and there was no long-term consistent association of variation in density with different habitats; sites of the same habitat type were as likely to have characteristically different densities as were sites of different habitat types. Average adult densities of H. formosa increased as aquatic vegetation cover increased and as the index of predation pressure decreased, however assemblage structure was not a strong predictor of density. These results show that despite marked community, abiotic and biotic distinctions between habitat types, location-specific variation was the predominant signal in these data.

Biases associated with the use of underwater visual census techniques to quantify the density and size-structure of fish populations

Estimates of reef fish densities made by divers visually censusing 5 m wide strip transects were compared with capture–resight estimates calculated independently using data on the resighting frequencies of fish marked with colour-coded tags. The difference in density estimates between methods varied between species but with patterns consistent at the three eastern Tasmanian sites studied. Densities of the two most abundant species, the wrasses Notolabrus tetricus and Notolabrus fucicola, showed good agreement between methods. By contrast, populations of the two monacanthids Meuschenia australis and Meuschenia freycineti were underestimated by an order of magnitude in strip transects relative to capture–resight, while populations of the open-water latrid Latridopsis forsteri were overestimated. For all common fish species observed in strip transects, variation in density estimates between divers was extremely low compared to variation between sites and between months. Variation in density estimates between different days within a week and between 50 m blocks located 50 m apart was also negligible; however, residual error associated with variation by a single diver within a block and day was high. Biases associated with changing detectability of fishes in open versus densely vegetated habitats were assessed by algal removal experiments, and were found to be negligible or non-significantly low for five of the six species examined. The exceptional species— N. tetricus—exhibited a 70% rise in fish sighted by diver following algal clearance despite trapping data indicating no increase in fish numbers. Diver estimates of fish length were on average 7% greater than measured lengths. Divers possessed a clear tendency to make increasingly inaccurate size estimates as fish length deviated in either direction from 300 mm. Lengths of 175-mm animals were underestimated by ≈20% and 400-mm fishes were overestimated by ≈10%. These changes in diver bias with fish size were largely independent of fish species, site and diver. The precision of size estimates, as indicated by the standard deviation of bias, also varied with fish size, with values varying from ≈13% at 200 mm fish length to ≈8% at 400 mm length. The decline in precision at small body size largely reflected size intervals used by divers to bin data. Divers appear capable of making more precise size estimates than the 25-mm interval used at small fish sizes.

Incorporating Landscape Attributes into Models for Migratory Grassland Bird Conservation

Abstract: We evaluated the influence of local and landscape attributes on the occurrence and density of seven passerine species in grasslands (n = 380) throughout eastern South Dakota ( U.S.A.). Landscape composition and land cover were quantified at three spatial scales: 400‐, 800‐, and 1600‐m radii from the transect center. Separate habitat models were generated for mixed‐grass and tallgrass prairie regions to depict the way birds respond to geographic variation in local and landscape structure. Sedge Wrens ( Cistothorus platensis) and Clay‐colored Sparrows ( Spizella pallida) in the mixed‐grass and tallgrass regions used both large and small patches if they were embedded in a landscape with a high proportion of grassland habitat. Occupancy rates for these species were higher in small patches within landscapes with high grassland abundance than in large patches within low grassland landscapes. Grasshopper Sparrows (Ammodramus savannarum) and Dickcissels ( Spiza americana) in the mixed‐grass region and Savannah Sparrows ( Passerculus sandwichensis) in the tallgrass region were area‐sensitive species that used large grassland patches regardless of landscape configuration. The occurrence of Savannah Sparrows in both regions and Sedge Wrens, Grasshopper Sparrows, and Western Meadowlarks ( Sturnella neglecta) in the mixed‐grass region was negatively associated with an increase in patch edges with trees. Explained variation in density estimates was associated only with local patch and vegetation variables. Individual species demonstrated scale‐dependent differences in the way they perceived habitat and in their response to regional landscape structure. These findings provide evidence that results from one region may not be extrapolated to others because they may vary with species distribution, vegetation structure, and landscape composition. Assessments of regional grassland bird habitat must be conducted at multiple scales because some species respond only to local conditions within grasslands, whereas others respond to habitat structure at landscape scales.

TEMPORAL VARIATION IN BIRD COUNTS WITHIN A HAWAIIAN RAINFOREST

We studied monthly and annual variation in density estimates of nine forest bird species along an elevational gradient in an east Maui rainforest. We conducted monthly variable circular-plot counts for 36 consecutive months along transects running downhill from timberline. Density estimates were compared by month, year, and station for all resident bird species with sizeable populations, including four native nectarivores, two native insectivores, a non-native insectivore, and two non-native generalists. We compared densities among three elevational strata and between breeding and nonbreeding seasons. All species showed significant differences in density estimates among months and years. Three native nectarivores had higher density estimates within their breeding season (December–May) and showed decreases during periods of low nectar production following the breeding season. All insectivore and generalist species except one had higher density estimates within their March–August breeding season. Density estimates also varied with elevation for all species, and for four species a seasonal shift in population was indicated. Our data show that the best time to conduct counts for native forest birds on Maui is January–February, when birds are breeding or preparing to breed, counts are typically high, variability in density estimates is low, and the likelihood for fair weather is best. Temporal variations in density estimates documented in our study site emphasize the need for consistent, well-researched survey regimens and for caution when drawing conclusions from, or basing management decisions on, survey data. Variación Temporal en Conteos de Aves en una Selva Lluviosa de Hawai Resumen. Estudiamos la variación mensual y anual en estimaciones de la densidad de nueve especies de aves a lo largo de un gradiente altitudinal en una selva lluviosa del este de Maui. Realizamos conteos mensuales en parcelas circulares por un período de 36 meses consecutivos a lo largo de transectas ubicadas desde la línea del bosque hacia abajo. Las estimaciones de densidad fueron comparadas entre meses, años y estaciones considerando todas las especies de aves residentes con poblaciones considerables, incluyendo cuatro nectarívoros nativos, dos insectívoros nativos, un insectívoro no nativo y dos generalistas no nativos. Comparamos densidades entre tres estratos altitudinales y entre las estaciones reproductivas y no reproductivas. Todas las especies mostraron diferencias significativas en las estimaciones de densidad entre meses y años. Tres nectarívoros nativos presentaron estimaciones de densidad mayores durante sus épocas reproductivas (diciembre–mayo) y mostraron disminuciones durante períodos de baja producción de néctar luego de la estación de cría. Excepto una, todas las especies insectívoras y generalistas presentaron mayores estimaciones de densidad durante sus épocas reproductivas (marzo–agosto). Las estimaciones de densidad de todas las especies también variaron con la altitud, y se encontraron cambios estacionales en las poblaciones de cuatro especies. Nuestros datos muestran que el mejor momento para realizar conteos de aves nativas de selva en Maui es enero–febrero, cuando las aves están criando o preparándose para criar, los conteos son típicamente altos, la variabilidad en las estimaciones de densidad es baja y la probabilidad de buen tiempo es más alta. La variación temporal en las estimaciones de densidad documentadas en nuestro sitio de estudio enfatizan la necesidad de regímenes de muestreo consistentes y bien establecidos, y sugiere cautela a la hora de sacar conclusiones para conservación o tomar decisiones de manejo a partir de datos de muestreos.

Analyst and Observer Variability in Density Estimates from Spot Mapping

We studied variation in density estimates from spot mapping that was attributable to analysts and observers, using expert birders with little or no prior experience with spot mapping. Three observers independently spot mapped one 42-ha plot (Markwood) in mixed-conifer forest, and four others independently spot mapped another (Teakettle). All observers analyzed all maps. Consistency among analysts and observers in estimating the numbers of territories of breeding species on each plot was generally poor. Across all combinations of analysts and maps, 71% of all ANOVAs had significant analyst and/or observer effects. Observer effects were generally greater than analyst effects. When observers analyzed their own species maps, CVs of individual species ranged from 0% to 173% (mean 41%) at Markwood and from 0% to 188% (mean 60%) at Teakettle. As in similar studies, mean CVs from pooled totals of all species were less than those from individual species and were within the range of variation found by other researchers. Based on the range of CVs observed among species in this study, the number of sample plots needed to detect a statistical difference in density of a given species between samples is probably prohibitive for most studies. Instead, practitioners need to design studies to control observer and analyst variability.