Evidence map›Paper›PMID 36166422›Full record

ArticlePloS one2022

Statistical population reconstruction of moose (Alces alces) in northeastern Minnesota using integrated population models.

William J Severud, Sergey S Berg, Connor A Ernst, Glenn D DelGiudice, Seth A Moore, Steve K Windels, Ron A Moen, Edmund J Isaac, Tiffany M Wolf

Abstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

William J SeverudDepartment of Veterinary Population Medicine, University of Minnesota, Saint Paul, Minnesota, United States of America.ORCID 0000-0003-0150-5986
Sergey S BergDepartment of Computer and Information Sciences, University of St. Thomas, Saint Paul, Minnesota, United States of America.ORCID 0000-0002-2707-294X
Connor A ErnstDepartment of Mathematics, University of St. Thomas, Saint Paul, Minnesota, United States of America.
Glenn D DelGiudiceForest Wildlife Populations and Research Group, Minnesota Department of Natural Resources, Forest Lake, Minnesota, United States of America.
Seth A MooreDepartment of Biology and Environment, Grand Portage Band of Lake Superior Chippewa, Grand Portage, Minnesota, United States of America.
Steve K WindelsVoyageurs National Park, International Falls, Minnesota, United States of America.
Ron A MoenCenter for Water and the Environment, University of Minnesota, Duluth, Minnesota, United States of America.
Edmund J IsaacDepartment of Biology and Environment, Grand Portage Band of Lake Superior Chippewa, Grand Portage, Minnesota, United States of America.
Tiffany M WolfDepartment of Veterinary Population Medicine, University of Minnesota, Saint Paul, Minnesota, United States of America.ORCID 0000-0003-1740-4442

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Given recent and abrupt declines in the abundance of moose (Alces alces) throughout parts of Minnesota and elsewhere in North America, accurately estimating statewide population trends and demographic parameters is a high priority for their continued management and conservation. Statistical population reconstruction using integrated population models provides a flexible framework for combining information from multiple studies to produce robust estimates of population abundance, recruitment, and survival. We used this framework to combine aerial survey data and survival data from telemetry studies to recreate trends and demographics of moose in northeastern Minnesota, USA, from 2005 to 2020. Statistical population reconstruction confirmed the sharp decline in abundance from an estimated 7,841 (90% CI = 6,702-8,933) in 2009 to 3,386 (90% CI = 2,681-4,243) animals in 2013, but also indicated that abundance has remained relatively stable since then, except for a slight decline to 3,163 (90% CI = 2,403-3,718) in 2020. Subsequent stochastic projection of the population from 2021 to 2030 suggests that this modest decline will continue for the next 10 years. Both annual adult survival and per-capita recruitment (number of calves that survived to 1 year per adult female alive during the previous year) decreased substantially in years 2005 and 2019, from 0.902 (SE = 0.043) to 0.689 (SE = 0.061) and from 0.386 (SE = 0.030) to 0.303 (SE = 0.051), respectively. Sensitivity analysis revealed that moose abundance was more sensitive to fluctuations in adult survival than recruitment; thus, we conclude that the steep decline in 2013 was driven primarily by decreasing adult survival. Our analysis demonstrates the potential utility of using statistical population reconstruction to monitor moose population trends and to identify population declines more quickly. Future studies should focus on providing better estimates of per-capita recruitment, using pregnancy rates and calf survival, which can then be incorporated into reconstruction models to help improve estimates of population change through time.

Indexed as

DeerAnimalsFemaleMinnesotaNorth AmericaPregnancy

Identifiers

PMID36166422
PMCPMC9514631

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.