Abstract. Estimates of abundance of threatened and endangered species are crucial for monitoring population status and recovery progress. For most wildlife species, multiple abundance estimation methods are available and the choice of method should depend on cost and efficacy. We fieldtested the cost and efficacy of line transect, total count, sample count, and double observer methods for estimating abundance of gopher tortoise (Gopherus polyphemus) burrows in two habitats that differed in vegetation density (sparse and dense) at the Ordway-Swisher Biological Station in northcentral Florida. In the dense vegetation stratum, density of burrows estimated using the line transect method (8.58 ± 0.94 burrows ha −1 ) was lower than that obtained from the total count method (11.33 burrows ha −1 ). In the sparse vegetation stratum, estimated burrow density using the line transect method (11.32 ± 1.19 burrows ha −1 ) was closer to the burrow density obtained from the total count method (13.00 burrows ha −1 ). Density of burrows estimated using the double observer method was identical to that obtained from the total count method in dense vegetation stratum, but slightly greater than that obtained from the total count method in sparse vegetation stratum. Density of burrows estimated using the sample count method varied widely depending on the proportion of plots sampled. The cost of sampling as well as estimates of burrow density varied with habitat type. The line transect method was the least costly of the methods, and we were able to sample a larger effective area with the same effort. Using burrow cameras and patch occupancy modeling approach, we also estimated the probability of burrow occupancy by gopher tortoises (active: 0.50 ± 0.09; inactive: 0.04 ± 0.04), and used these values to estimate abundance of gopher tortoises. Using estimates of burrow abundance based on the line transect method, density of gopher tortoises was 2.75 ± 0.74 ha −1 in the sparse vegetation stratum. We recommend that gopher tortoise monitoring programs use rigorous methods for estimating burrow abundance (e.g., line transect methods) and the probability of burrow occupancy by gopher tortoises (e.g., patch occupancy modeling approach).
Abstract:The line transect distance sampling method provides unbiased estimates of abundance when organisms are distributed randomly or line transects are laid out randomly, sample sizes are large and other assumptions of the method are met; such, however, is rarely the case in real life. We conducted a simulation study to investigate how spatial distribution and density of objects, and total length, layout and number of transects influence bias, precision, and accuracy of estimates of abundance obtained by distance sampling along line transects. Overall, density estimated using the distance sampling method was within 4.9% of the true density, but it varied substantially depending upon spatial distribution of objects. Of the three spatial distribution patterns considered, estimates of density were least biased, and most precise and accurate when objects were distributed randomly; they were most biased, and least precise and accurate when objects followed a clumped distribution. The estimated bias (% difference between true density and estimated density) for clumped, random and uniform distribution was 13.1%, -0.4%, and 2.1%, respectively; precision (% coefficient of variation, CV( D )) was 13.7%, 9.1%, and 9.2%; and accuracy (root mean-squared error, RMSE) was 27.9%, 7.4%, and 11.7% for clumped, random, and uniform distribution, respectively. Increasing total transect length and using several short transects (as opposed to few long transects) generally reduced bias, and increased accuracy and precision of estimates of abundance. A systematic layout of transects worked as well as, or better than, random layout, except when objects were distributed uniformly in space. This study advances the utility of the line transect method by providing information both on how study design affects accuracy and precision of abundance estimates, and how it can be improved when assumptions of the method are not strictly met based on a priori knowledge of the spatial distribution and presumed density of the target organism through appropriate changes in the study design.
Line-transect distance sampling (LTDS) is increasingly used to estimate gopher tortoise (Gopherus polyphemus) densities. The process requires detecting tortoise burrows, and then determining occupancy. We compared 3 LTDS approaches that differ in how burrow detection and occupancy data are integrated, and 2 search strategies. Surveys were conducted at Avon Park Air Force Range in South-central Florida, USA, from April through October 2009. These include 1) LTDS using data from occupied burrows only; 2) LTDS with burrows treated as "clusters" of size 1 or 0 depending on occupancy; 3) LTDS to estimate burrow densities, with occupancy modeling to estimate occupancy rates; and 4) 2 search strategies: standard versus expanded searches. The LTDS method produced reliable burrow density estimates, and tortoise densities were estimated most precisely and with least effort using data from occupied burrows only. However, any method could be biased if burrow occupancy is uncertain. Indeed, in the Florida scrub and pine flatwoods habitats, video-camera scoping was hindered by groundwater or obstructions, resulting in undetermined occupancy for 45% of burrows. Improving scope technologies and surveying during the dry season has improved subsequent results for xeric habitats; however, research is needed to improve detectability of tortoises in mesic habitats with flooded burrows. If occupancy is uncertain, we recommend collecting data on all burrows, irrespective of occupancy, so that burrow densities can be estimated even if occupancy cannot. We do not recommend expanding the search area with sigmoid search paths adjacent to transects owing to potential violations of assumptions, nor use of occupancy modeling, because model requirements may lead to unacceptable exclusion of data. Ó 2015 The Wildlife Society.
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