Habitat suitability modelling to improve conservation status of two critically endangered endemic Afromontane forest bird species in Taita Hills, Kenya

• DOI: 10.1016/j.jnc.2021.126111
• Publication Date: 2021-12-07T01:12:20Z
• Authors: Gilbay Obunga; Mika Siljander; Marianne Maghenda; P.K.E. Pellikka
• Keywords: 0106 biological sciences; PREDICTION; IMPACT; Wildlife Ecology and Conservation Biology; Conservation status; Taita Apalis; DIVERSITY; Taita Thrush; APALIS APALIS-FUSCIGULARIS; 01 natural sciences; Endangered species; Biodiversity Conservation and Ecosystem Management; Habitat destruction; Critically endangered bird species; MANAGEMENT; DISTRIBUTIONS; LOCATION; Species distribution models; MaxEnt; Biology; Nature and Landscape Conservation; ARABUKO-SOKOKE FOREST; Species Distribution Modeling and Climate Change Impacts; Ecology; Habitat Suitability; Geography; Ecological Modeling; Critically endangered; 15. Life on land; IUCN Red List; Threatened species; Environmental sciences; THRESHOLDS; Habitat; Habitat Selection; 13. Climate action; Habitat suitability; FOS: Biological sciences; Environmental Science; Physical Sciences; BIODIVERSITY; Habitat Fragmentation

Tropical montane forests are known to support many endemic species with restricted geographic ranges. Many of these however, faced numerous threats, most notably from habitat loss and degradation, invasive alien species, climate change. Examples include Taita Apalis Thrush. (Apalis fuscigularis) Thrush (Turdus helleri) birds listed as Critically Endangered by the Government Kenya International Union for Conservation Nature (IUCN). They Hills' cloud in southeastern protected under Wildlife Management Act. As they face high risk extinction, exploring their suitability is imperative protection. To determine current spatial distribution key ecogeographical explanatory factors conditions affecting indirect effects on survival reproduction, we employed Maximum Entropy (MaxEnt) modelling. This study was conducted Ngangao Vuria June July 2019 2020. forest gazetted reserve managed Forest Service whereas non-gazetted thus remains without official protection status. Ecogeographical variables; climatic, remote sensing-, LIDAR-, topography- landscape-based variables were used modelling separate models produced. 23 occurrence records 30 21 According models, less than 7% total area predicted suitable shows that two more vulnerable extinction demographic stochasticity. Consequently, managing habitats critical long-term persistence. LIDAR-based canopy height range elevation greatly influenced forest, areas (1620–1750 m a.s.l.) having open middle-storey preferred. Elevation, slope topographic wetness index (twi) major determinants Ngangao, where gentle sloping moderately dry surfaces within (1620–1730 favoured. Mean annual temperature, Euclidean distance edge, land cover type Vuria, interior made up indigenous vegetation proposes reforesting degraded sites next highly species; establishment agroforestry belts based trees boundaries reduce grazing firewood collection pressure enhance resilience edge effects; enhancing through Participatory Management.