scholarly journals Variance Propagation for Density Surface Models

2021 ◽  
Author(s):  
Mark V. Bravington ◽  
David L. Miller ◽  
Sharon L. Hedley
Keyword(s):  
Random Effect ◽  
Distance Sampling ◽  
Line Transect ◽  
Line Transect Survey ◽  
Surface Models ◽  
On Line ◽  
Density Surface ◽  
Two Stages ◽  
Variance Estimates ◽  
Spatially Varying

AbstractSpatially explicit estimates of population density, together with appropriate estimates of uncertainty, are required in many management contexts. Density surface models (DSMs) are a two-stage approach for estimating spatially varying density from distance sampling data. First, detection probabilities—perhaps depending on covariates—are estimated based on details of individual encounters; next, local densities are estimated using a GAM, by fitting local encounter rates to location and/or spatially varying covariates while allowing for the estimated detectabilities. One criticism of DSMs has been that uncertainty from the two stages is not usually propagated correctly into the final variance estimates. We show how to reformulate a DSM so that the uncertainty in detection probability from the distance sampling stage (regardless of its complexity) is captured as an extra random effect in the GAM stage. In effect, we refit an approximation to the detection function model at the same time as fitting the spatial model. This allows straightforward computation of the overall variance via exactly the same software already needed to fit the GAM. A further extension allows for spatial variation in group size, which can be an important covariate for detectability as well as directly affecting abundance. We illustrate these models using point transect survey data of Island Scrub-Jays on Santa Cruz Island, CA, and harbour porpoise from the SCANS-II line transect survey of European waters. Supplementary materials accompanying this paper appear on-line.

scholarly journals Using mark-recapture distance sampling methods on line transect surveys

2014 ◽  
Vol 5 (11) ◽  
pp. 1180-1191 ◽  
Author(s):  
Mary Louise Burt ◽  
David L. Borchers ◽  
Kurt J. Jenkins ◽  
Tiago A. Marques
Keyword(s):  
Sampling Methods ◽  
Distance Sampling ◽  
Line Transect ◽  
Mark Recapture ◽  
On Line

scholarly journals Aerial line transect survey to estimate abundance of marsh deer (Blastocerus dichotomus) (Illiger, 1815)

2005 ◽  
Vol 48 (5) ◽  
pp. 807-814 ◽  
Author(s):  
Artur Andriolo ◽  
Ubiratan Piovezan ◽  
Mateus José Rodrigues Paranhos da Costa ◽  
Jeff Laake ◽  
José Maurício Barbanti Duarte
Keyword(s):  
Population Size ◽  
River Basin ◽  
Distance Sampling ◽  
Aerial Survey ◽  
Line Transect ◽  
Sampling Methodology ◽  
Future Analysis ◽  
Line Transect Survey ◽  
Blastocerus Dichotomus ◽  
The Impact

The objective was to estimate abundance of marsh deer in the Paraná River basin of this work. The results provided information to support further analysis of the impact of the Porto Primavera flooding lake over population. Sixty-nine animals were recorded by aerial survey using distance sampling methodology. Animals were widely distributed throughout the study area. The uncorrected data resulted in a estimate density of 0.0035 ind/ha and a population size of 636 individuals. Correcting the g for the animals that could be missed the calculated abundance was 896 (CV=0.27) individuals. This methodology was applied with success to survey marsh deer. The result was important to evaluate the marsh deer status in the area, and for future analysis of the impact of the flooding dam.

scholarly journals Extending density surface models to include multiple and double-observer survey data

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e12113
Author(s):  
David L. Miller ◽  
David Fifield ◽  
Ewan Wakefield ◽  
Douglas B. Sigourney
Keyword(s):  
Spatial Model ◽  
Distance Sampling ◽  
Additive Model ◽  
Data Sources ◽  
Multiple Sources ◽  
Multiple Data Sources ◽  
Multiple Data ◽  
Surface Models ◽  
Density Surface ◽  
Double Observer

Spatial models of density and abundance are widely used in both ecological research (e.g., to study habitat use) and wildlife management (e.g., for population monitoring and environmental impact assessment). Increasingly, modellers are tasked with integrating data from multiple sources, collected via different observation processes. Distance sampling is an efficient and widely used survey and analysis technique. Within this framework, observation processes are modelled via detection functions. We seek to take multiple data sources and fit them in a single spatial model. Density surface models (DSMs) are a two-stage approach: first accounting for detectability via distance sampling methods, then modelling distribution via a generalized additive model. However, current software and theory does not address the issue of multiple data sources. We extend the DSM approach to accommodate data from multiple surveys, collected via conventional distance sampling, double-observer distance sampling (used to account for incomplete detection at zero distance) and strip transects. Variance propagation ensures that uncertainty is correctly accounted for in final estimates of abundance. Methods described here are implemented in the dsm R package. We briefly analyse two datasets to illustrate these new developments. Our new methodology enables data from multiple distance sampling surveys of different types to be treated in a single spatial model, enabling more robust abundance estimation, potentially over wider geographical or temporal domains.

scholarly journals Developing and assessing a density surface model in a Bayesian hierarchical framework with a focus on uncertainty: insights from simulations and an application to fin whales (Balaenoptera physalus)

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e8226
Author(s):  
Douglas B. Sigourney ◽  
Samuel Chavez-Rosales ◽  
Paul B. Conn ◽  
Lance Garrison ◽  
Elizabeth Josephson ◽  
...  
Keyword(s):  
Distance Sampling ◽  
Habitat Model ◽  
Line Transect ◽  
Surface Model ◽  
Two Stage ◽  
Balaenoptera Physalus ◽  
Density Estimates ◽  
Bayesian Hierarchical ◽  
Density Surface ◽  
Fin Whales

Density surface models (DSMs) are an important tool in the conservation and management of cetaceans. Most previous applications of DSMs have adopted a two-step approach to model fitting (hereafter referred to as the Two-Stage Method), whereby detection probabilities are first estimated using distance sampling detection functions and subsequently used as an offset when fitting a density-habitat model. Although variance propagation techniques have recently become available for the Two-Stage Method, most previous applications have not propagated detection probability uncertainty into final density estimates. In this paper, we describe an alternative approach for fitting DSMs based on Bayesian hierarchical inference (hereafter referred to as the Bayesian Method), which is a natural framework for simultaneously propagating multiple sources of uncertainty into final estimates. Our framework includes (1) a mark-recapture distance sampling observation model that can accommodate two team line transect data, (2) an informed prior for the probability a group of animals is at the surface and available for detection (i.e. surface availability) (3) a density-habitat model incorporating spatial smoothers and (4) a flexible compound Poisson-gamma model for count data that incorporates overdispersion and zero-inflation. We evaluate our method and compare its performance to the Two-Stage Method with simulations and an application to line transect data of fin whales (Balaenoptera physalus) off the east coast of the USA. Simulations showed that both methods had low bias (<1.5%) and confidence interval coverage close to the nominal 95% rate when variance was propagated from the first step. Results from the fin whale analysis showed that density estimates and predicted distribution patterns were largely similar among methods; however, the coefficient of variation of the final abundance estimate more than doubled (0.14 vs 0.31) when detection variance was correctly propagated into final estimates. An analysis of the variance components demonstrated that overall detectability as well as surface availability contributed substantial amounts of variance in the final abundance estimates whereas uncertainty in mean group size contributed a negligible amount. Our method provides a Bayesian alternative to DSMs that incorporates much of the flexibility available in the Two-Stage Method. In addition, these results demonstrate the degree to which uncertainty can be underestimated if certain components of a DSM are assumed fixed.

scholarly journals Techniques for Estimating the Size of Low-Density Gopher Tortoise Populations

2017 ◽  
Vol 8 (2) ◽  
pp. 377-386 ◽  
Author(s):  
Jonathan M. Stober ◽  
Rocio Prieto-Gonzalez ◽  
Lora L. Smith ◽  
Tiago A. Marques ◽  
Len Thomas
Keyword(s):  
Habitat Management ◽  
Distance Sampling ◽  
Probability Of Detection ◽  
Line Transect ◽  
Efficient Design ◽  
Gopher Tortoise ◽  
Gopherus Polyphemus ◽  
Line Transect Survey ◽  
Estimate Population Size ◽  
Survey Designs

Abstract Gopher tortoises (Gopherus polyphemus) are candidates for range-wide listing as threatened under the U.S. Endangered Species Act. Reliable population estimates are important to inform policy and management for recovery of the species. Line transect distance sampling has been adopted as the preferred method to estimate population size. However, when tortoise density is low, it can be challenging to obtain enough tortoise observations to reliably estimate the probability of detection, a vital component of the method. We suggest a modification to the method based on counting usable tortoise burrows (more abundant than tortoises) and separately accounting for the proportion of burrows occupied by tortoises. The increased sample size of burrows can outweigh the additional uncertainty induced by the need to account for the proportion of burrows occupied. We demonstrate the method using surveys conducted within a 13,118-ha portion of the Gopher Tortoise Habitat Management Unit at Fort Gordon Army Installation, Georgia. We used a systematic random design to obtain more precise estimates, using a newly developed systematic variance estimator. Individual transects had a spatially efficient design (pseudocircuits), which greatly improved sampling efficiency on this large site. Estimated burrow density was 0.091 ± 0.011 burrows/ha (CV = 12.6%, 95% CI = 0.071–0.116), with 25% of burrows occupied by a tortoise (CV = 14.4%), yielding a tortoise density of 0.023 ± 0.004 tortoise/ha (CV = 19.0%, 95% CI = 0.016–0.033) and a population estimate of 297 tortoises (95% CI = 210–433). These techniques are applicable to other studies and species. Surveying burrows or nests, rather than animals, can produce more reliable estimates when it leads to a significantly larger sample of detections and when the occupancy status can reliably be ascertained. Systematic line transect survey designs give better precision and are practical to implement and analyze.

PROFIL KERAGAMAN VEGETASI EKOSISTEM MANGROVE DI DESA TAMUKU KABUPATEN LUWU UTARA

2019 ◽  
Vol 5 ◽  
pp. 104
Author(s):  
Suhendra Purnawan ◽  
Subari Yanto ◽  
Ernawati S.Kaseng
Keyword(s):  
Survey Methods ◽  
Mangrove Ecosystem ◽  
Line Transect ◽  
Mangrove Forests ◽  
Vegetation Diversity ◽  
Line Transect Survey ◽  
Analysis Technique ◽  
Mangrove Vegetation ◽  
Data Collection Technique ◽  
The Impact

This study aims to describe the profile of vegetation diversity in the mangrove ecosystem in Tamuku Village, Bone-Bone-Bone District, North Luwu Regency. This research is a qualitative research using survey methods. The data collection technique uses the Quadrant Line Transect Survey technique. The data analysis technique uses the thinking flow which is divided into three stages, namely describing phenomena, classifying them, and seeing how the concepts that emerge are related to each other. The results of this study are the profile of mangrove vegetation in Tamuku Village, which is still found 16 varieties of true mangrove vegetation and 7 varieties of mangrove vegetation joined in the coastal area of Tamuku Village, Bone-Bone District, North Luwu Regency, South Sulawesi. The condition of mangrove vegetation in Tamuku Village is currently very worrying due to human activities that cause damage such as the project of normalization of flow, opening of new farms, disposal of garbage, water pollution due to chemicals, and exploitation of mangrove forests for living needs. The impact is ecosystem damage and reduced vegetation area as a place to grow and develop mangroves.

scholarly journals Getting the Most From Surveys: How Method Selection and Method Modification Impact Butterfly Survey Data

2021 ◽  
Author(s):  
Katherine C Kral-O’Brien ◽  
Adrienne K Antonsen ◽  
Torre J Hovick ◽  
Ryan F Limb ◽  
Jason P Harmon
Keyword(s):  
Species Richness ◽  
New Species ◽  
Count Data ◽  
Distance Sampling ◽  
Line Transect ◽  
Similar Species ◽  
Method Selection ◽  
M 10 ◽  
Sampling Procedures

Abstract Many methods are used to survey butterfly populations, with line transect and area surveys being prominent. Observers are typically limited to search within 5 or 10 m from the line, while observers are unrestricted in larger specified search regions in area surveys. Although methods differ slightly, the selection is often based on producing defendable data for conservation, maximizing data quality, and minimizing effort. To guide method selection, we compared butterfly surveys using 1) line versus area methods and 2) varying width transects (5 m, 10 m, or unrestricted) using count data from surveys in North Dakota from 2015 to 2018. Between line and area surveys, we detected more individuals with area surveys, even when accounting for effort. However, both methods accumulated new species at similar rates. When comparing transect methodology, we detected nearly 60% more individuals and nine more species when transect width increased from 5 m to unrestricted, despite similar effort across methodology. Overall, we found line surveys slightly less efficient at detecting individuals, but they collected similar species richness to area surveys when accounting for effort. Additionally, line surveys allow the use of unrestricted-width transects with distance sampling procedures, which were more effective at detecting species and individuals while providing a means to correct count data over the same transect length. Methods that reduce effort and accurately depict communities are especially important for conservation when long-term datasets are unavailable.

Harbor porpoise (Phocoena phocoena) recovery in the inland waters of Washington: estimates of density and abundance from aerial surveys, 2013–2015

2016 ◽  
Vol 94 (7) ◽  
pp. 505-515 ◽  
Author(s):  
Thomas A. Jefferson ◽  
Mari A. Smultea ◽  
Sarah S. Courbis ◽  
Gregory S. Campbell
Keyword(s):  
Puget Sound ◽  
Distance Sampling ◽  
Line Transect ◽  
Inland Waters ◽  
San Juan ◽  
Phocoena Phocoena ◽  
Harbor Porpoise ◽  
San Juan Islands ◽  
Juan De Fuca ◽  
Harbor Porpoises

The harbor porpoise (Phocoena phocoena (L., 1758)) used to be common in Puget Sound, Washington, but virtually disappeared from these waters by the 1970s. We conducted systematic aerial line-transect surveys (17 237 km total effort) for harbor porpoises, with the goal of estimating density and abundance in the inland waters of Washington State. Surveys in Puget Sound occurred throughout the year from 2013 to 2015, and in the Strait of Juan de Fuca and the San Juan Islands (and some adjacent Canadian waters) in April 2015. We used a high-wing, twin-engine Partenavia airplane and four observers (one on each side of the plane, one looking through a belly port, and one recording data). A total of 1063 harbor porpoise groups were sighted. Density and abundance were estimated using conventional distance sampling methods. Analyses were limited to 447 harbor porpoise groups observed during 5708 km of effort during good sighting conditions suitable for line-transect analysis. Harbor porpoises occurred in all regions of the study area, with highest densities around the San Juan Islands and in northern Puget Sound. Overall, estimated abundance for the Washington Inland Waters stock was 11 233 porpoises (CV = 37%, 95% CI = 9 616 – 13 120). This project clearly demonstrated that harbor porpoises have reoccupied waters of Puget Sound and are present there in all seasons. However, the specific reasons for their initial decline and subsequent recovery remain uncertain.

The importance of survey design in distance sampling: field evaluation using domestic sheep

2011 ◽  
Vol 38 (3) ◽  
pp. 221 ◽  
Author(s):  
Tom A. Porteus ◽  
Suzanne M. Richardson ◽  
Jonathan C. Reynolds
Keyword(s):  
Population Size ◽  
Survey Design ◽  
Distance Sampling ◽  
Field Evaluation ◽  
Stage I ◽  
Stage Ii ◽  
Line Transect ◽  
Domestic Sheep ◽  
Management Decisions ◽  
Mobile Species

Context Sampling methods to estimate animal density require good survey design to ensure assumptions are met and sampling is representative of the survey area. Management decisions are often made based on these estimates. However, without knowledge of true population size it is not possible for wildlife biologists to evaluate how biased the estimates can be if survey design is compromised. Aims Our aims were to use distance sampling to estimate population size for domestic sheep free-ranging within large enclosed areas of hill country and, by comparing estimates against actual numbers, examine how bias and precision are impaired when survey design is compromised. Methods We used both line and point transect sampling to derive estimates of density for sheep on four farms in upland England. In Stage I we used limited effort and different transect types to compromise survey design. In Stage II we increased effort in an attempt to improve on the Stage I estimates. We also examined the influence of a walking observer on sheep behaviour to assess compliance with distance sampling assumptions and to improve the fit of models to the data. Key results Our results show that distance sampling can lead to biased and imprecise density estimates if survey design is poor, particularly when sampling high density and mobile species that respond to observer presence. In Stage I, walked line transects were least biased; point transects were most biased. Increased effort in Stage II reduced the bias in walked line transect estimates. For all estimates, the actual density was within the derived 95% confidence intervals, but some of these spanned a range of over 100 sheep per km2. Conclusions Using a population of known size, we showed that survey design is vitally important in achieving unbiased and precise density estimation using distance sampling. Adequate transect replication reduced the bias considerably within a compromised survey design. Implications Management decisions based on poorly designed surveys must be made with an appropriate understanding of estimate uncertainty. Failure to do this may lead to ineffective management.

scholarly journals The influence of animal mobility on the assumption of uniform distances in aerial line-transect surveys

2008 ◽  
Vol 35 (4) ◽  
pp. 275 ◽  
Author(s):  
Rachel M. Fewster ◽  
Colin Southwell ◽  
David L. Borchers ◽  
Stephen T. Buckland ◽  
Anthony R. Pople
Keyword(s):  
Survey Design ◽  
Distance Sampling ◽  
High Mobility ◽  
Line Transect ◽  
Transect Line ◽  
Aerial Surveys ◽  
Pack Ice ◽  
Capture Recapture ◽  
Distance Data ◽  
Crabeater Seals

Line-transect distance sampling is a widely used method for estimating animal density from aerial surveys. Analysis of line-transect distance data usually relies on a requirement that the statistical distribution of distances of animal groups from the transect line is uniform. We show that this requirement is satisfied by the survey design if all other assumptions of distance sampling hold, but it can be violated by consistent survey problems such as responsive movement of the animals towards or away from the observer. We hypothesise that problems with the uniform requirement are unlikely to be encountered for immobile taxa, but might become substantial for species of high mobility. We test evidence for non-uniformity using double-observer distance data from two aerial surveys of five species with a spectrum of mobility capabilities and tendencies. No clear evidence against uniformity was found for crabeater seals or emperor penguins on the pack-ice in East Antarctica, while minor non-uniformity consistent with responsive movement up to 30 m was found for Adelie penguins. Strong evidence of either non-uniformity or a failure of the capture–recapture validating method was found for eastern grey kangaroos and red kangaroos in Queensland.

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