Phylogenetic analysis links Nigerian mammal extinction risk to brain mass, range and generation time

A phylogenetic analysis of 314 mammal species occurring in Nigeria found that estimated extinction risk was associated with brain mass, present-day geographic range and generation time, with the relevant traits differing among specific threats. In the overall model, species with smaller current ranges and larger brains had higher estimated risk, longer generation times were positively associated with risk, and body mass was negatively associated with it.

The observational study examined whether biological traits were associated with species’ IUCN conservation status and their exposure to threats recorded in the International Union for Conservation of Nature’s Threats Classification Scheme, version 3.3. Its scope was limited to mammals occurring in Nigeria. Eight threat-specific models covered residential and commercial development, agriculture and aquaculture, energy production and mining, transportation and service corridors, biological resource use, human intrusions and disturbance, pollution, and climate change and severe weather.

The researchers compiled species records and spatial data from the IUCN Red List and matched scientific names against PHYLACINE 1.2 and phylogenetic trees from Upham and colleagues, producing a harmonised list of 314 taxa. Body-mass data came from PHYLACINE, while brain-mass and generation-time data came from the COMBINE database. Geographic range was calculated from IUCN spatial polygons, producing measures of total area, current area and extinct area. Range could not be calculated for 17 primarily aquatic or semi-aquatic species because polygon data were missing.

Five predictors were included in the analysis: absolute current geographic area, the ratio of current to total historical area, body mass, brain mass and generation time. The current-to-total-area ratio was used as a measure of historical range contraction: lower values indicate a greater proportional loss of historically occupied area. This ratio was distinct from the absolute current-range predictor. Threat exposure was coded manually from individual IUCN species profiles, with a value of 1 assigned whenever a threat was listed at any severity or scope and 0 when it was absent.

The researchers used phylogenetic logistic regression to account for shared evolutionary history when estimating trait–risk relationships. They tested combinations of the five predictors, applied variance-inflation-factor diagnostics and excluded combinations with values above 2. Four threat categories with fewer than 25 affected species were omitted because the authors said such samples could produce unstable or overfitted estimates. Nine models were retained: one overall model based on Red List status and the eight threat-specific models.

Brain mass was the most consistent and influential predictor across the models. Larger brain mass was positively associated with estimated extinction risk in the overall analysis and under agriculture and aquaculture, biological resource use, residential and commercial development, and climate change and severe weather. Its largest standardised effects occurred in the climate, development and biological-resource-use models. The authors linked this pattern to characteristics often associated with large-brained mammals, including behavioural specialisation, extended development, delayed reproduction and higher energy demands, as well as possible exposure to hunting and wildlife trade.

Absolute current geographic range was another recurring association. Its effect was negative, indicating higher estimated risk among species with smaller present-day ranges. That relationship was statistically significant under agriculture and aquaculture, biological resource use, human intrusions and disturbance, and in the overall model. By contrast, historical range contraction had limited predictive value. It was significant only in the human-intrusions model, where greater proportional range loss was associated with higher risk, and it was not significant in the overall model or the other threat-specific models.

Generation time also varied by threat. Longer generation times were associated with higher risk under agriculture and aquaculture, energy production and mining, and transportation and service corridors. Under climate change and severe weather, the relationship reversed, with shorter generation times associated with greater risk. The authors proposed that this contrast may reflect differences in sensitivity to environmental variability, although the climate-related effect was weaker than those seen under direct human pressures. Body mass generally had weak effects but was significantly and negatively associated with risk in the agriculture and aquaculture model.

These results indicate that extinction-risk patterns among Nigerian mammals are biologically structured rather than uniform, but the analysis does not establish that the measured traits cause extinction. Its precision is constrained by the resolution and attribution accuracy of IUCN threat records, especially for gradual or indirect threats such as pollution and climate change. Some trait values also required inference or imputation: body mass was directly available for 312 of 314 species, while brain mass and generation time were directly available for 295 species. The estimates also depend on the completeness and accuracy of the phylogenetic tree and taxonomy used. The authors conclude that trait-based, phylogenetically informed evidence could help prioritise large-brained, range-restricted and slow-reproducing mammals and support responses tailored to particular threats.

Subject of Research: Trait-based analysis of extinction risk among 314 mammal species in Nigeria

Article Title: Assessing patterns of extinction risk amongst mammal species in Nigeria: A comparative analysis of human impact

Article References: Asanbe, B. (2026). Assessing patterns of extinction risk amongst mammal species in Nigeria: A comparative analysis of human impact. Biodiversity Data Journal, 14, Article e191439. https://doi.org/10.3897/bdj.14.e191439

Image Credits: AI Generated

DOI: 10.3897/BDJ.14.e191439

Keywords: Nigeria, mammals, extinction risk, phylogenetic regression, brain mass, geographic range, generation time, threat exposure, biodiversity conservation, Assessing, patterns, extinction