Finding the perfect mismatch: Evaluating misspecification of population structure within spatially explicit integrated population models

2021 ◽  
Author(s):  
Katelyn M. Bosley ◽  
Amy M. Schueller ◽  
Daniel R. Goethel ◽  
Dana H. Hanselman ◽  
Kari H. Fenske ◽  
...  
Keyword(s):  
Population Structure ◽  
Population Models ◽  
Spatially Explicit

Uncertainty in spatially explicit population models

2008 ◽  
Vol 141 (4) ◽  
pp. 956-970 ◽  
Author(s):  
E.S. Minor ◽  
R.I. McDonald ◽  
E.A. Treml ◽  
D.L. Urban
Keyword(s):  
Population Models ◽  
Spatially Explicit

scholarly journals Incoherent dimensionality in fisheries management: consequences of misaligned stock assessment and population boundaries

2020 ◽  
Author(s):  
Aaron M Berger ◽  
Jonathan J Deroba ◽  
Katelyn M Bosley ◽  
Daniel R Goethel ◽  
Brian J Langseth ◽  
...  
Keyword(s):  
Population Structure ◽  
Stock Assessment ◽  
Spatially Explicit ◽  
Spatial Simulation ◽  
Management Options ◽  
Spatially Explicit Models ◽  
Fisheries Policy ◽  
Simulation Estimation ◽  
Definition Of ◽  
Dynamic Population

Abstract Fisheries policy inherently relies on an explicit definition of management boundaries that delineate the spatial extent over which stocks are assessed and regulations are implemented. However, management boundaries tend to be static and determined by politically negotiated or historically identified population (or multi-species) units, which create a potential disconnect with underlying, dynamic population structure. The consequences of incoherent management and population or stock boundaries were explored through the application of a two-area spatial simulation–estimation framework. Results highlight the importance of aligning management assessment areas with underlying population structure and processes, especially when fishing mortality is disproportionate to vulnerable biomass among management areas, demographic parameters (growth and maturity) are not homogenous within management areas, and connectivity (via recruitment or movement) unknowingly exists among management areas. Bias and risk were greater for assessments that incorrectly span multiple population segments (PSs) compared to assessments that cover a subset of a PS, and these results were exacerbated when there was connectivity between PSs. Directed studies and due consideration of critical PSs, spatially explicit models, and dynamic management options that help align management and population boundaries would likely reduce estimation biases and management risk, as would closely coordinated management that functions across population boundaries.

Incorporating citizen science data in spatially explicit integrated population models

Ecology ◽  
2019 ◽  
Vol 100 (9) ◽  
Author(s):  
Catherine C. Sun ◽  
J. Andrew Royle ◽  
Angela K. Fuller
Keyword(s):  
Citizen Science ◽  
Population Models ◽  
Spatially Explicit ◽  
Science Data

Spatially Explicit Population Models: Current Forms and Future Uses

1995 ◽  
Vol 5 (1) ◽  
pp. 3-11 ◽  
Author(s):  
John B. Dunning ◽  
David J. Stewart ◽  
Brent J. Danielson ◽  
Barry R. Noon ◽  
Terry L. Root ◽  
...  
Keyword(s):  
Population Models ◽  
Spatially Explicit

Incorporating behavior-based indices of connectivity into spatially explicit population models

2012 ◽  
Vol 90 (2) ◽  
pp. 222-236 ◽  
Author(s):  
C.E. Rizkalla ◽  
R.K. Swihart
Keyword(s):  
Population Models ◽  
Spatially Explicit ◽  
Patch Occupancy ◽  
Ecological Processes ◽  
Forest Patch ◽  
Fragmented Landscapes ◽  
Direct Observations ◽  
Behavior Based ◽  
Potential Methods ◽  
Parameter Values

Measuring connectivity in fragmented landscapes remains a central problem in ecology. Connectivity metrics range from descriptors of landscape structure to direct observations of a species’ ability to move to and colonize a forest patch. We constructed individual-based spatially explicit population models for a guild of forest rodents in Indiana to test the ability of structural and actual, or behavioral, measures of connectivity to predict patch and landscape occupancy and abundance. Model accuracy was assessed using comparisons with data from trapping studies. Predicted abundances within patches correlated with empirical data for five out of six species, but predicted patterns of patch occupancy corresponded with observations for only one species. Discrepancies may be due to inaccurate parameter values or the absence from the models of ecological processes such as conspecific attraction and competition. Nonetheless, the models demonstrated the utility of patch immigration as a measure of connectivity in explaining population abundance in fragmented landscapes. We discuss potential methods of collecting these behavior-based data.

Spatially Explicit Population Models

1995 ◽  
Vol 5 (1) ◽  
pp. 2-2 ◽  
Author(s):  
H. Ronald Pulliam ◽  
John B. Dunning
Keyword(s):  
Population Models ◽  
Spatially Explicit
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