scholarly journals Designing an occupancy framework to monitor an endemic rainforest duck: Methodological and modelling considerations

2020 ◽  
Author(s):  
Shah Nawaz Jelil ◽  
Murchana Parasar ◽  
Laura Cancino ◽  
Kimberly Cook
Keyword(s):  
Detection Probability ◽  
Site Occupancy ◽  
Optimal Number ◽  
Occupancy Models ◽  
Occupancy Detection ◽  
Habitat Factors ◽  
Long Term Ecological Research ◽  
Species Occupancy ◽  
Future Population

AbstractUnderstanding species trend, decline or growth, is vital to further conservation efforts. Species-habitat relationship studies are equally important for conservation as it helps in understanding the habitat a particular species depends upon, i.e. habitat conservation. However, rare and endemic species are inherently difficult to study and occupancy models are especially useful in such cases. We conducted the first detection, non-detection survey for the white winged duck in Dehing Patkai Wildlife Sanctuary, India to assess site occupancy and test habitat factors that explain its occupancy. We found that white winged duck occupancy was low (0.27 ± 0.21 SE) and detection probability was 0.44 ± 0.30 SE. We found that increasing tree richness and decreasing elevation increased species occupancy. Detection probability was influenced by our effort in that detection increased with increasing number of survey hours. Using two standard approaches, we estimated the optimal number of sites and replicate surveys for future occupancy studies. We further present considerations for future surveys. Considering the sporadic and fragmented information available, we recommend long-term ecological research to better understand the present and future population trends of the species.

Factors Associated with Detection Probability and Site Occupancy of the Long-Tailed Skink (Eutropis longicaudata) in the Aluoi Area, Central Vietnam

2021 ◽  
Vol 28 (2) ◽  
pp. 67-72
Author(s):  
Chung D. Ngo ◽  
Hai P. Dang ◽  
Nghiep T. Hoang ◽  
Binh Van Ngo
Keyword(s):  
Detection Probability ◽  
Site Occupancy ◽  
Weather Conditions ◽  
Habitat Model ◽  
Occupancy Models ◽  
Lizard Species ◽  
Disturbed Habitat ◽  
Occupancy Probability ◽  
Central Vietnam ◽  
A Site

Lizard species are rarely detected with perfect accuracy, regardless of the method employed. Nondetection of a species at a site does not necessarily mean the species was absent unless the detection probability was 100%. We assessed the influence of site covariates (less disturbed habitat and disturbed habitat) and sample covariates (temperature, humidity, rainfall) on the occupancy of Eutropis longicaudata in the Aluoi area, central Vietnam. Based on detection/nondetection data over nine visits at 40 less disturbed sites and 39 sites with disturbed habitats, the distribution of E. longicaudata was estimated using site occupancy models. From the best model, we estimated a site occupancy probability of 0.595, a 12.05% increase over the naive occupancy of 0.531 at which E. longicaudata skinks were actually observed. The site covariate of the less disturbed habitat was an important determinant of site occupancy, which was not associated with the variable of disturbance habitats. In the combined AIC model weight, p(precipitation), p(temperature), and p(humidity) have 92%, 36%, and 21% of the total, respectively; providing evidence that environmental conditions (especially precipitation) were important sample covariates in modelling detection probabilities of E. longicaudata. In terms of occupancy probability, the combined weight for the ψ(less disturbed habitat) model and the ψ(disturbed habitat) model were 60% and 32%, respectively. Our results substantiate the importance of incorporating detection and occupancy probabilities into studies of habitat relationships and suggest that the less disturbed habitat associated with weather conditions influence the occupancy of E. longicaudata in central Vietnam.

scholarly journals Utilizing occupancy-detection models with museum specimen data: promise and pitfalls

2021 ◽  
Author(s):  
Vaughn Shirey ◽  
Rassim Khelifa ◽  
Leithen K. M’Gonigle ◽  
Laura Melissa Guzman
Keyword(s):  
Simulated Data ◽  
Data Sets ◽  
Occupancy Models ◽  
Space And Time ◽  
Road Map ◽  
Detection Analysis ◽  
Occupancy Detection ◽  
High Fraction ◽  
The Right ◽  
Species Occupancy

AbstractHistorical museum records provide potentially useful data for identifying drivers of change in species occupancy. However, because museum records are typically obtained via many collection methods, methodological developments are needed in order to enable robust inferences. Occupancy-detection models, a relatively new and powerful suite of methods, are a potentially promising avenue because they can account for changes in collection effort through space and time. Here we present a methodological road-map for using occupancy models to analyze historical museum records. We use simulated data-sets to identify how and when patterns in data and/or modelling decisions can bias inference. We focus primarily on the consequences of contrasting methodological approaches for dealing with species’ ranges and inferring species’ non-detections in both space and time. We find that not all data-sets are suitable for occupancy-detection analysis but, under the right conditions (namely, data-sets that span long durations and contain a high fraction of community-wide collections, or collection events that focus on communities of organisms), models can accurately estimate trends. Finally, we present a case-study on eastern North American odonates where we calculate long-term trends of occupancy by using our most robust workflow.

scholarly journals Connectivity: insights from the U.S. Long Term Ecological Research Network

Ecosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
Author(s):  
David M. Iwaniec ◽  
Michael Gooseff ◽  
Katharine N. Suding ◽  
David Samuel Johnson ◽  
Daniel C. Reed ◽  
...  
Keyword(s):  
Research Network ◽  
Ecological Research ◽  
Long Term Ecological Research ◽  
The U.S

Habitat factors related to wild rabbit population trends after the initial impact of rabbit haemorrhagic disease

2006 ◽  
Vol 33 (6) ◽  
pp. 467 ◽  
Author(s):  
Carlos Calvete ◽  
Enrique Pelayo ◽  
Javier Sampietro
Keyword(s):  
Habitat Quality ◽  
Population Trends ◽  
Wild Rabbit ◽  
Pest Species ◽  
Predator Species ◽  
Rabbit Population ◽  
Habitat Factors ◽  
Rabbit Haemorrhagic Disease ◽  
Haemorrhagic Disease

The European wild rabbit (Oryctolagus cuniculus) is an introduced pest species in Australia and New Zealand. Rabbits have a devastating negative impact on agricultural production and biodiversity in these countries, and Rabbit Haemorrhagic Disease (RHD) is currently included in control strategies for rabbit populations. On the other hand, the European wild rabbit is a key native prey species in the Iberian Peninsula. Since the arrival of RHD, however, rabbit populations have undergone dramatic decreases and several predator species at risk of extinction are currently dependent on the rabbit population density. Therefore, from the point of view of biodiversity conservation, evaluating habitat correlates and trends of rabbit populations after the first RHD epizootic is of great interest to improve the long-term control or promotion of wild rabbit populations. We estimated the relationship between habitat factors and long-term population trends as well as the relationships between habitat factors and rabbit abundance 2 and 14 years after the arrival of RHD in several Iberian rabbit populations. We observed that only 26% of surveyed populations seemed to experience an increase in rabbit abundance over the last 12 years and that this increase was higher in the low-rabbit-abundance areas of l992, leading to high rabbit abundance in 2004. Our results suggested that short- and long-term impacts of RHD were related to habitat quality. The initial impact of RHD was higher in more suitable habitats, but increasing long-term population trends were positively related to good habitat quality.

scholarly journals Using areas of known occupancy to identify sources of variation in detection probability of raptors: taking time lowers replication effort for surveys

2016 ◽  
Vol 3 (10) ◽  
pp. 160368 ◽  
Author(s):  
Campbell Murn ◽  
Graham J. Holloway
Keyword(s):  
Detection Probability ◽  
Spatial Scales ◽  
Survey Methods ◽  
A Priori ◽  
Low Density ◽  
Occupancy Models ◽  
Imperfect Detection ◽  
Factors Affecting ◽  
Sources Of Variation ◽  
Time Of Year

Species occurring at low density can be difficult to detect and if not properly accounted for, imperfect detection will lead to inaccurate estimates of occupancy. Understanding sources of variation in detection probability and how they can be managed is a key part of monitoring. We used sightings data of a low-density and elusive raptor (white-headed vulture Trigonoceps occipitalis ) in areas of known occupancy (breeding territories) in a likelihood-based modelling approach to calculate detection probability and the factors affecting it. Because occupancy was known a priori to be 100%, we fixed the model occupancy parameter to 1.0 and focused on identifying sources of variation in detection probability. Using detection histories from 359 territory visits, we assessed nine covariates in 29 candidate models. The model with the highest support indicated that observer speed during a survey, combined with temporal covariates such as time of year and length of time within a territory, had the highest influence on the detection probability. Averaged detection probability was 0.207 (s.e. 0.033) and based on this the mean number of visits required to determine within 95% confidence that white-headed vultures are absent from a breeding area is 13 (95% CI: 9–20). Topographical and habitat covariates contributed little to the best models and had little effect on detection probability. We highlight that low detection probabilities of some species means that emphasizing habitat covariates could lead to spurious results in occupancy models that do not also incorporate temporal components. While variation in detection probability is complex and influenced by effects at both temporal and spatial scales, temporal covariates can and should be controlled as part of robust survey methods. Our results emphasize the importance of accounting for detection probability in occupancy studies, particularly during presence/absence studies for species such as raptors that are widespread and occur at low densities.

scholarly journals Patterns and trends of organic matter processing and transport: Insights from the US Long-Term Ecological Research network

2021 ◽  
pp. 100025
Author(s):  
Tamara K. Harms ◽  
Peter M. Groffman ◽  
Lihini Aluwihare ◽  
Chris Craft ◽  
William R Wieder ◽  
...  
Keyword(s):  
Organic Matter ◽  
Research Network ◽  
Ecological Research ◽  
The Us ◽  
Long Term Ecological Research ◽  
Organic Matter Processing
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