Literature DB >> 29065232

Sampling scales define occupancy and underlying occupancy-abundance relationships in animals.

Robin Steenweg1, Mark Hebblewhite1, Jesse Whittington2, Paul Lukacs1, Kevin McKelvey3.   

Abstract

Occupancy-abundance (OA) relationships are a foundational ecological phenomenon and field of study, and occupancy models are increasingly used to track population trends and understand ecological interactions. However, these two fields of ecological inquiry remain largely isolated, despite growing appreciation of the importance of integration. For example, using occupancy models to infer trends in abundance is predicated on positive OA relationships. Many occupancy studies collect data that violate geographical closure assumptions due to the choice of sampling scales and application to mobile organisms, which may change how occupancy and abundance are related. Little research, however, has explored how different occupancy sampling designs affect OA relationships. We develop a conceptual framework for understanding how sampling scales affect the definition of occupancy for mobile organisms, which drives OA relationships. We explore how spatial and temporal sampling scales, and the choice of sampling unit (areal vs. point sampling), affect OA relationships. We develop predictions using simulations, and test them using empirical occupancy data from remote cameras on 11 medium-large mammals. Surprisingly, our simulations demonstrate that when using point sampling, OA relationships are unaffected by spatial sampling grain (i.e., cell size). In contrast, when using areal sampling (e.g., species atlas data), OA relationships are affected by spatial grain. Furthermore, OA relationships are also affected by temporal sampling scales, where the curvature of the OA relationship increases with temporal sampling duration. Our empirical results support these predictions, showing that at any given abundance, the spatial grain of point sampling does not affect occupancy estimates, but longer surveys do increase occupancy estimates. For rare species (low occupancy), estimates of occupancy will quickly increase with longer surveys, even while abundance remains constant. Our results also clearly demonstrate that occupancy for mobile species without geographical closure is not true occupancy. The independence of occupancy estimates from spatial sampling grain depends on the sampling unit. Point-sampling surveys can, however, provide unbiased estimates of occupancy for multiple species simultaneously, irrespective of home-range size. The use of occupancy for trend monitoring needs to explicitly articulate how the chosen sampling scales define occupancy and affect the occupancy-abundance relationship.
© 2017 by the Ecological Society of America.

Keywords:  abundance-occupancy; distribution-abundance; large mammals; mobile organisms; occupancy models; sampling; scale

Mesh:

Year:  2017        PMID: 29065232     DOI: 10.1002/ecy.2054

Source DB:  PubMed          Journal:  Ecology        ISSN: 0012-9658            Impact factor:   5.499


  7 in total

1.  Mesocarnivore community structuring in the presence of Africa's apex predator.

Authors:  Gonçalo Curveira-Santos; Chris Sutherland; Simone Tenan; Albert Fernández-Chacón; Gareth K H Mann; Ross T Pitman; Lourens H Swanepoel
Journal:  Proc Biol Sci       Date:  2021-03-10       Impact factor: 5.349

Review 2.  Framing pictures: A conceptual framework to identify and correct for biases in detection probability of camera traps enabling multi-species comparison.

Authors:  Tim R Hofmeester; Joris P G M Cromsigt; John Odden; Henrik Andrén; Jonas Kindberg; John D C Linnell
Journal:  Ecol Evol       Date:  2019-01-23       Impact factor: 2.912

3.  Evidence of region-wide bat population decline from long-term monitoring and Bayesian occupancy models with empirically informed priors.

Authors:  Thomas J Rodhouse; Rogelio M Rodriguez; Katharine M Banner; Patricia C Ormsbee; Jenny Barnett; Kathryn M Irvine
Journal:  Ecol Evol       Date:  2019-09-11       Impact factor: 2.912

4.  Resolving misaligned spatial data with integrated species distribution models.

Authors:  Krishna Pacifici; Brian J Reich; David A W Miller; Brent S Pease
Journal:  Ecology       Date:  2019-05-13       Impact factor: 5.499

5.  Occupancy data improves parameter precision in spatial capture-recapture models.

Authors:  José Jiménez; Francisco Díaz-Ruiz; Pedro Monterroso; Jorge Tobajas; Pablo Ferreras
Journal:  Ecol Evol       Date:  2022-08-26       Impact factor: 3.167

6.  Simulated treatment effects on bird communities inform landscape-scale dry conifer forest management.

Authors:  Quresh S Latif; Jeffery B Cannon; Eric J Chabot; Robert A Sparks
Journal:  Ecol Appl       Date:  2022-04-24       Impact factor: 6.105

7.  Visual encounters on line transect surveys under-detect carnivore species: Implications for assessing distribution and conservation status.

Authors:  Jose M V Fragoso; Fernando Gonçalves; Luiz F B Oliveira; Han Overman; Taal Levi; Kirsten M Silvius
Journal:  PLoS One       Date:  2019-10-30       Impact factor: 3.240

  7 in total

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