MétaCan
Menu
Back to cohort
Record W2962683187 · doi:10.1002/wmon.1041

Dynamics, Persistence, and Genetic Management of the Endangered Florida Panther Population

2019· article· en· W2962683187 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueWildlife Monographs · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and phenotypic traits in livestock
Canadian institutionsMcMaster University
FundersDivision of Graduate EducationNational Park ServiceUniversity of FloridaFlorida Fish and Wildlife Conservation CommissionU.S. Fish and Wildlife ServiceTexas Tech UniversityNational Science Foundation
KeywordsBiologyPopulationInbreedingInbreeding depressionGenetic diversityEndangered speciesDemographyZoologyEcology

Abstract

fetched live from OpenAlex

ABSTRACT Abundant evidence supports the benefits accrued to the Florida panther ( Puma concolor coryi ) population via the genetic introgression project implemented in South Florida, USA, in 1995. Since then, genetic diversity has improved, the frequency of morphological and biomedical correlates of inbreeding depression have declined, and the population size has increased. Nevertheless, the panther population remains small and isolated and faces substantial challenges due to deterministic and stochastic forces. Our goals were 1) to comprehensively assess the demographics of the Florida panther population using long‐term (1981–2015) field data and modeling to gauge the persistence of benefits accrued via genetic introgression and 2) to evaluate the effectiveness of various potential genetic management strategies. Translocation and introduction of female pumas ( Puma concolor stanleyana ) from Texas, USA, substantially improved genetic diversity. The average individual heterozygosity of canonical (non‐introgressed) panthers was 0.386 ± 0.012 (SE); for admixed panthers, it was 0.615 ± 0.007. Survival rates were strongly age‐dependent (kittens had the lowest survival rates), were positively affected by individual heterozygosity, and decreased with increasing population abundance. Overall annual kitten survival was 0.32 ± 0.09; sex did not have a clear effect on kitten survival. Annual survival of subadult and adult panthers differed by sex; regardless of age, females exhibited higher survival than males. Annual survival rates of subadult, prime adult, and old adult females were 0.97 ± 0.02, 0.86 ± 0.03, and 0.78 ± 0.09, respectively. Survival rates of subadult, prime adult, and old adult males were 0.66 ± 0.06, 0.77 ± 0.05, and 0.65 ± 0.10, respectively. For panthers of all ages, genetic ancestry strongly affected survival rate, where first filial generation (F1) admixed panthers of all ages exhibited the highest rates and canonical (mostly pre‐introgression panthers and their post‐introgression descendants) individuals exhibited the lowest rates. The most frequently observed causes of death of radio‐collared panthers were intraspecific aggression and vehicle collision. Cause‐specific mortality analyses revealed that mortality rates from vehicle collision, intraspecific aggression, other causes, and unknown causes were generally similar for males and females, although males were more likely to die from intraspecific aggression than females. The probability of reproduction and the annual number of kittens produced varied by age; evidence that ancestry or abundance influenced these parameters was weak. Predicted annual probabilities of reproduction were 0.35 ± 0.08, 0.50 ± 0.05, and 0.25 ± 0.06 for subadult, prime adult, and old adult females, respectively. The number of kittens predicted to be produced annually by subadult, prime adult, and old adult females were 2.80 ± 0.75, 2.67 ± 0.43, and 2.28 ± 0.83, respectively. The stochastic annual population growth rate estimated using a matrix population model was 1.04 (95% CI = 0.72–1.41). An individual‐based population model predicted that the probability that the population would fall below 10 panthers within 100 years (quasi‐extinction) was 1.4% (0–0.8%) if the adverse effects of genetic erosion were ignored. However, when the effect of genetic erosion was considered, the probability of quasi‐extinction within 100 years increased to 17% (0–100%). Mean times to quasi‐extinction, conditioned on going quasi‐extinct within 100 years, was 22 (0–75) years when the effect of genetic erosion was considered. Sensitivity analyses revealed that the probability of quasi‐extinction and expected time until quasi‐extinction were most sensitive to changes in kitten survival parameters. Without genetic management intervention, the Florida panther population would face a substantially increased risk of quasi‐extinction. The question, therefore, is not whether genetic management of the Florida panther population is needed but when and how it should be implemented. Thus, we evaluated genetic and population consequences of alternative genetic introgression strategies to identify optimal management actions using individual‐based simulation models. Releasing 5 pumas every 20 years would cost much less ($200,000 over 100 years) than releasing 15 pumas every 10 years ($1,200,000 over 100 years) yet would reduce the risk of quasi‐extinction by comparable amount (44–59% vs. 40–58%). Generally, releasing more females per introgression attempt provided little added benefit. The positive effects of the genetic introgression project persist in the panther population after 20 years. We suggest that managers contemplate repeating genetic introgression by releasing 5–10 individuals from other puma populations every 20–40 years. We also recommend that managers continue to collect data that will permit estimation and monitoring of kitten, adult, and subadult survival. We identified these parameters via sensitivity analyses as most critical in terms of their impact on the probability of and expected times to quasi‐extinction. The continuation of long‐term monitoring should permit the adaptation of genetic management strategies as necessary while collecting data that have proved essential in assessing the genetic and demographic health of the population. The prospects for recovery of the panther will certainly be improved by following these guidelines. © 2019 The Authors. Wildlife Monographs published by Wiley Periodicals, Inc. on behalf of The Wildlife Society.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.330

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.200
Teacher spread0.193 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it