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Data from: Two-species occupancy modeling accounting for species misidentification and nondetection
负责人:
关键词:
DOI:
doi:10.5061/dryad.88ks4g5
摘要:
of forest habitats among years. 5.Given the extent of species misidentification issues in occupancy studies, this modelling approach should help improve
Data from: Distinguishing distribution dynamics from temporary emigration using dynamic occupancy models
负责人:
Valente, Jonathon J.
关键词:
closure assumption colonization detection probability dynamic occupancy models extinction metapopulation Pollock's robust design temporary emigration
DOI:
doi:10.5061/dryad.5d8s7
摘要:
. 4. Concern for violating the occupancy modeling closure assumption has led to widespread recommendations that samples within primary period
Data from: Inferential biases linked to unobservable states in complex occupancy models
负责人:
关键词:
parameter redundancy;chytridiomycosis;unobservable state
DOI:
doi:10.5061/dryad.g62f6
摘要:
’ natural history or sampling technology. When multistate occupancy models are used and an unobservable state is present, parameter estimation can be influenc
Data from: Effects of mountaintop removal mining and valley filling on the occupancy and abundance of stream salamanders
负责人:
关键词:
coal mining;hurdle model;Gyrinophilus;Desmognathus;salamander;mountaintop removal mining;valley filling;land use;Water quality;Appalachia;Pseudotriton;Eurycea;reclamation;Amphibians
DOI:
doi:10.5061/dryad.5m8f6
摘要:
(Ecology, 94, 2013 and 1472), where occupancy is modelled separately from abundance while accounting for differences in per-individual detection probabili
Data from: Should scientists be required to use a model-based solution to adjust for possible distance-based detectability bias?
负责人:
关键词:
point count;n\/a;Black-backed Woodpecker;distance;Inference;occupancy;detectability;index;Picoides arcticus
DOI:
doi:10.5061/dryad.46tp6
摘要:
the effects of distance on detectability or occupancy. I challenge the idea that modeling is the best approach to account for distance-based effects
Combining hierarchical distance sampling with occupancy modeling to measure population density from indirect signs
负责人:
Martin, Scott A.;;Bolt, M. Rebecca;;Seigel, Richard A.;;Parkinson, Christopher L.
关键词:
Ecology Conservation Conservation Management Animal Ecology Wildlife Management Methodology Population Density
DOI:
doi:10.17632/4s97scjk3g
摘要:
Gopher Tortoise density is included. Table S1. Covariates used in modelling and their predicted effects. Check marks for each location correspond to wheth
Combining hierarchical distance sampling with occupancy modeling to measure population density from indirect signs
负责人:
Martin, Scott A.;;Bolt, M. Rebecca;;Seigel, Richard A.;;Parkinson, Christopher L.
关键词:
Ecology Conservation Conservation Management Animal Ecology Wildlife Management Methodology Population Density
DOI:
doi:10.17632/4s97scjk3g.1
摘要:
Gopher Tortoise density is included. Table S1. Covariates used in modelling and their predicted effects. Check marks for each location correspond to wheth
Data from: Adding fossil occupancy trajectories to the assessment of modern extinction risk
负责人:
关键词:
Marine invertebrates;Geographic occupancy;Palaeobiology;Cenozoic;Extinction risk
DOI:
doi:10.5061/dryad.h5b45
摘要:
and its temporal trajectory are significant determinants of risk. Based on extinct species we develop a model on the additive and interacting effects of occupancy
Data from: Mapping and explaining wolf recolonization in France using dynamic occupancy models and opportunistic data
负责人:
关键词:
occupancy model;large carnivores;opportunistic data;1994 - 2016;Canis lupus
DOI:
doi:10.5061/dryad.g9s1d
摘要:
to 2016, while accounting for species imperfect detection and time- and space-varying sampling effort using dynamic site-occupancy models. Ignoring
Data from: Assessing spatio-temporal priorities for species’ recovery in broad-scale dynamic landscapes
负责人:
关键词:
spatio priorities;recovery planning;koala;multiple threats;dynamic occupancy model;Land-use change;dynamic threats;climate change
DOI:
doi:10.5061/dryad.4nh84
摘要:
. 2. We combined a dynamic occupancy model with a decision analysis framework to spatially allocate multiple recovery actions to maximize species’ probabili

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