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Data · dataset · 2024

Field-validated species distribution model of Canada Warbler (Cardellina canadensis) in Northwestern Ontario

Listed in Teesside University Research Data Repository

The Canada Warbler (CAWA) is a species of conservation concern, but its ecological needs and distribution remain poorly understood.

Description

Additionally, contradictory findings exist regarding the impact of logging on CAWA abundance and habitat use. Furthermore, its habitat needs may be distorted by limitations in current habitat availability compared to historical conditions.

We developed a predictive high-resolution (30 m) field-validated species distribution model (SDM) in Ecoregion 4W of Northwestern Ontario, Canada, where little field-derived information about the species is available. We aimed to assess how time since disturbance mainly due by logging affects CAWA occurrence and distribution and also the accuracy of the model by ground-truth validation. We used a desktop dataset from different sources, and due to limited number of observations (78 after filtered) we enhanced the dataset with field-collected data gathered in 2021 and 2022.

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We ran different models also to test the accuracy of the models using only desktop data and a datasete enhances with field-collected data. The SDM’s environmental covariates included a bare soil index (BASI), a normalized water index (NDWI) as an indicator of deciduos vegetation, an enhanced vegetation index (EVI), a digital elevation model (DEM), years since disturbance (DISTURB [usually by logging] 1-20 years since last disturbance happened, 21 value represent undisturbed or no disturbed more than 20 years ago), distance to mature coniferous forest (D_CONIF), tree canopy height (CAN) and distance to water (WATER) as indicator of riparian zones.

The models that used field-collected data showed a moderate performance for both training and test data (AUC 0.7) while the model that used only desktop dataset showed a poor performance (AUC 0.6); NDWI, WATER, EVI and D_CONIF were the most influential covariates indicating high association of CAWA to deciduous vegetation, riparian areas, shrub cover and importance of coniferous stands. CAWA occurrence probability was high in undisturbed areas, but also it has a high predicted probability (>0.6) in areas within six years since disturbance; CAWA may take advantage of regenerated forest depending on shrub density and retention of old-growth forest structure ( CAWA had a high prediction of occurrence areas with canopies higher than 10m tall).

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Teesside University Research Data Repositoryoai:data.mendeley.com/bmg4f64bdz.26 h agoJSON v1
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concepts[field].local:field:earth-environmentalmapping · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
concepts[field].local:field:life-sciencesmapping · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
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