Evidence map›Paper›PMID 41555245›Full record

ArticleBMC ecology and evolution2026

Modelling the spatial and temporal dynamics in the distribution patterns of African White backed vultures Gyps africanus in the Hwange National Park.

Tadiwanashe Zhuwawo, Mark Zvidzai, Ratidzo Blessing Mapfumo

Abstract read
In one paragraph

Article in BMC ecology and evolution, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

3 authors.

Tadiwanashe ZhuwawoDepartment of Geography, Geospatial Sciences and Earth Observation, University of Zimbabwe, Harare, Zimbabwe.
Mark ZvidzaiDepartment of Geography, Geospatial Sciences and Earth Observation, University of Zimbabwe, Harare, Zimbabwe. mark.zvidzai@gmail.com.
Ratidzo Blessing MapfumoDepartment of Geography, Geospatial Sciences and Earth Observation, University of Zimbabwe, Harare, Zimbabwe.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

African White-backed Vultures (AWbV) play a vital ecological role as nature’s scavengers, yet their population is declining due to poisoning, habitat loss, human disturbances, and climate variability. This study investigates the spatial and temporal distribution of AWbV in Hwange National Park, Zimbabwe, using a suite of species distribution modelling algorithms. Four modeling techniques, Random Forest, XGBoost, Generalized Linear Models, and an Ensemble approach were applied to assess how the spatial distribution of the AWbV vary across seasons and compare modelling results from the four algorithms The study also tested the predictive performance of each of the algorithms. The study revealed that AWbV in Hwange National Park consistently preferred northeastern regions year-round, with seasonal use of northwestern areas in the dry season likely due to shifting carrion and water resources. Random Forest outperformed other models with near-perfect accuracy, identifying Mean temperature of driest quarter (Bio9) and distance to park boundary (DTPB) as key dry season drivers, while the Maximum temperature of warmest month (Bio5) and Precipitation of wettest month (Bio13) dominated wet season predictions. Based on these results, conservation managers may need to prioritize the deployment of more conservation resources to protect the northeastern hotspot, while also monitoring climate thresholds to anticipate habitat disturbances. The findings highlight the effectiveness of integrating several algorithms in ecological modeling to inform actionable strategies for vulture conservation amidst environmental and anthropogenic pressures.

Indexed as

Animal DistributionFalconiformesAlgorithmsAnimalsConservation of Natural ResourcesEcosystemModels, BiologicalParks, RecreationalPopulation DynamicsRandom ForestSeasonsZimbabweHwange National ParkSpecies distribution modellingWhite-backed Vulture

Identifiers

PMID41555245
PMCPMC12817523

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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.