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Record W3017946359 · doi:10.1002/ecs2.3082

Estimating arthropod survival probability from field counts: a case study with monarch butterflies

2020· article· en· W3017946359 on OpenAlexaffabout
Tyler J. Grant, D. T. Tyler Flockhart, Teresa Rose Blader, Richard L. Hellmich, Grace M. Pitman, Sam Tyner, D. Ryan Norris, Steven P. Bradbury

Bibliographic record

VenueEcosphere · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsUniversity of GuelphNature Conservancy of Canada
FundersNational Institute of Food and Agriculture
KeywordsMonarch butterflyPupaStatisticsDanausPopulationBayesian probabilityEcologyMark and recaptureBiologyGeographyLarvaDemographyMathematics

Abstract

fetched live from OpenAlex

Abstract Survival probability is fundamental for understanding population dynamics. Methods for estimating survival probability from field data typically require marking individuals, but marking methods are not possible for arthropod species that molt their exoskeleton between life stages. We developed a novel Bayesian state‐space model to estimate arthropod larval survival probability from stage‐structured count data. We performed simulation studies to evaluate estimation bias due to detection probability, individual variation in stage duration, and study design (sampling frequency and sample size). Estimation of cumulative survival probability from oviposition to pupation was robust to potential sources of bias. Our simulations also provide guidance for designing field studies with minimal bias. We applied the model to the monarch butterfly ( Danaus plexippus ), a declining species in North America for which conservation programs are being implemented. We estimated cumulative survival from egg to pupation from monarch counts conducted at 18 field sites in three landcover types in Iowa, USA, and Ontario, Canada: road right‐of‐ways, natural habitats (gardens and restored meadows), and agricultural field borders. Mean predicted survival probability across all landcover types was 0.014 (95% CI: 0.004–0.024), four times lower than previously published estimates using an ad hoc estimator. Estimated survival probability ranged from 0.002 (95% CI: 7.0E−7 to 0.034) to 0.058 (95% CI: 0.013–0.113) at individual sites. Among landcover types, agricultural field borders in Ontario had the highest estimated survival probability (0.025 with 95% CI: 0.008–0.043) and natural areas had the lowest estimated survival probability (0.008 with 95% CI: 0.009–0.024). Monarch production was estimated as adults produced per milkweed stem by multiplying survival probabilities by eggs per milkweed at these sites. Monarch production ranged from 1.0 (standard deviation [SD] = 0.68) adult in Ontario natural areas in 2016 to 29.0 (SD = 10.42) adults in Ontario agricultural borders in 2015 per 6809 milkweed stems. Survival estimates are critical to monarch population modeling and habitat restoration efforts. Our model is a significant advance in estimating survival probability for monarch butterflies and can be readily adapted to other arthropod species with stage‐structured life histories.

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How this classification was reachedexpand

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.213
Threshold uncertainty score0.997

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)0.0040.001

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 head0.018
GPT teacher head0.246
Teacher spread0.227 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations22
Published2020
Admission routes2
Has abstractyes

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