Estimating abundance of harvested populations at the management unit scale.
Management of harvested populations relies on accurate assessment of abundance within management units to reevaluate and set harvest regulations. Several statistical approaches use readily available age-at-harvest data to estimate populations, but these often rely on auxiliary data which can be cost...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2025-01-01
|
| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0326454 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849329580009062400 |
|---|---|
| author | Allison C Keever James D Kelly Garrett B Clevinger Bradley S Cohen |
| author_facet | Allison C Keever James D Kelly Garrett B Clevinger Bradley S Cohen |
| author_sort | Allison C Keever |
| collection | DOAJ |
| description | Management of harvested populations relies on accurate assessment of abundance within management units to reevaluate and set harvest regulations. Several statistical approaches use readily available age-at-harvest data to estimate populations, but these often rely on auxiliary data which can be costly to collect and may not provide reliable estimates at the management unit scale. We developed a Bayesian integrated population model (IPM) relying solely on available harvest data to estimate abundance of white-tailed deer in Tennessee where estimates of abundance were lacking. We fit the IPM to reported harvest data and estimates of total harvest from hunter surveys to estimate abundance statewide and within deer management units (DMUs). Statewide deer harvest in Tennessee from 2005 to 2023 ranged between 132,256 and 181,477 deer annually (mean = 160,050; SD = 16,178). Although the population fluctuated, median population growth rate was 0.99 (90% CRI 0.978-1.003) during the study. Statewide population abundance was estimated at 890,657 (90% CRI 786,627-1,172,514) deer in 2023. Our IPM provided a comprehensive picture of deer population dynamics and allowed us to estimate abundance and demographic rates using only harvest data and informative priors. This model demonstrates the benefits of using informative priors and regularizing parameters in ecological studies. The IPM is a useful, flexible tool to monitor harvested populations at finer spatial scales thereby allowing decisions on harvest regulations to be based on precise estimates of abundance within specific management units. |
| format | Article |
| id | doaj-art-e52e7109269647899d71ac77c9aaa66a |
| institution | Kabale University |
| issn | 1932-6203 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-e52e7109269647899d71ac77c9aaa66a2025-08-20T03:47:13ZengPublic Library of Science (PLoS)PLoS ONE1932-62032025-01-01206e032645410.1371/journal.pone.0326454Estimating abundance of harvested populations at the management unit scale.Allison C KeeverJames D KellyGarrett B ClevingerBradley S CohenManagement of harvested populations relies on accurate assessment of abundance within management units to reevaluate and set harvest regulations. Several statistical approaches use readily available age-at-harvest data to estimate populations, but these often rely on auxiliary data which can be costly to collect and may not provide reliable estimates at the management unit scale. We developed a Bayesian integrated population model (IPM) relying solely on available harvest data to estimate abundance of white-tailed deer in Tennessee where estimates of abundance were lacking. We fit the IPM to reported harvest data and estimates of total harvest from hunter surveys to estimate abundance statewide and within deer management units (DMUs). Statewide deer harvest in Tennessee from 2005 to 2023 ranged between 132,256 and 181,477 deer annually (mean = 160,050; SD = 16,178). Although the population fluctuated, median population growth rate was 0.99 (90% CRI 0.978-1.003) during the study. Statewide population abundance was estimated at 890,657 (90% CRI 786,627-1,172,514) deer in 2023. Our IPM provided a comprehensive picture of deer population dynamics and allowed us to estimate abundance and demographic rates using only harvest data and informative priors. This model demonstrates the benefits of using informative priors and regularizing parameters in ecological studies. The IPM is a useful, flexible tool to monitor harvested populations at finer spatial scales thereby allowing decisions on harvest regulations to be based on precise estimates of abundance within specific management units.https://doi.org/10.1371/journal.pone.0326454 |
| spellingShingle | Allison C Keever James D Kelly Garrett B Clevinger Bradley S Cohen Estimating abundance of harvested populations at the management unit scale. PLoS ONE |
| title | Estimating abundance of harvested populations at the management unit scale. |
| title_full | Estimating abundance of harvested populations at the management unit scale. |
| title_fullStr | Estimating abundance of harvested populations at the management unit scale. |
| title_full_unstemmed | Estimating abundance of harvested populations at the management unit scale. |
| title_short | Estimating abundance of harvested populations at the management unit scale. |
| title_sort | estimating abundance of harvested populations at the management unit scale |
| url | https://doi.org/10.1371/journal.pone.0326454 |
| work_keys_str_mv | AT allisonckeever estimatingabundanceofharvestedpopulationsatthemanagementunitscale AT jamesdkelly estimatingabundanceofharvestedpopulationsatthemanagementunitscale AT garrettbclevinger estimatingabundanceofharvestedpopulationsatthemanagementunitscale AT bradleyscohen estimatingabundanceofharvestedpopulationsatthemanagementunitscale |