Butterfly community composition within a tropical urban landscape is influenced by habitat type and temperature
Abstract
The specific factors that influence spatial community or population dynamics are often elusive, and even less known is the impact of tropical urban landscapes on diverse species community assemblages. To address this knowledge gap, we used a survey data set with 510 fruit‐feeding butterflies comprising 20 species across two heterogeneous habitats within a city in Nigeria. Next, we constructed generalised linear mixed models to understand the differential responses of the butterfly community to changes in environmental conditions across habitats. Butterfly species community assemblages significantly differed between the two urban habitats, with butterfly species significantly higher in the savannah woodland compared with the gallery forest due to the optimal daily temperatures of the savannah woodland. However, butterfly richness was lower in the gallery forest due to extreme environmental conditions. This study highlights that butterfly community changes in tropical urban landscapes are possibly responding to local microclimates and spatial heterogeneity across habitats. For evidence‐based conservation management of tropical butterfly biodiversity, there would be a need for a long‐term, extensive and systematic insect monitoring programme for butterflies across disturbed and undisturbed fragmented habitats harbouring diverse insect species.
https://doi.org/10.5061/dryad.dv41ns25c
The dataset data consists of raw occurrence records of butterflies, and other variables collected to evaluate factors influencing the community of butterflies in urban areas in Nigeria. This includes over 500 butterfly species observations from different two habitats.
Description of the data and file structure
Week: Consists of raw data of the week butterflies were collected from different locations.
Date: The variables represent the date butterflies were collected from different locations.
Poin_ID: Are the exact occurrence points where butterflies were collected from habitats.
Lon: Longitudinal coordinates (°E or °W) of the source locations where butterflies were samples
Lat: Latitudinal coordinates (°N or °S) of the source locations where butterflies were samples
habitat: Classification of the habitats where butterflies were found during sampling
habitat_area: Computed size of habitats where butterflies were found during sampling
**Species: **Species of butterflies collected and identified in the laboratory
**Flower: ** Number of plants with flowers found to be utilized by butterflies during sampling
**Fruits: ** Number of plants with fruits found to be utilized by butterflies during sampling
**Family: **Family of species of butterflies collected and identified in the laboratory
**Subfamily: **Subfamilies of species of butterflies collected and identified in the laboratory
Count: Number of butterflies counted at each occurrence points during sampling.
**Weather: **Categories of weather condition during sampling for statistical analyses
temp: Daily mean temperature (°C) of the source locations where butterflies were samples
maxtemp: Daily maximum temperature (°C) of the source locations where butterflies were samples
mintemp: Daily minimum temperature (°C) of the source locations where butterflies were samples
humidity: Mean humid value (g/kg) of the source locations where butterflies were samples
ws: Mean wind speed value (m/s) of the source locations where butterflies were samples
maxws: Maximum wind speed value (m/s) of the source locations where butterflies were samples
minws: Minimum wind speed value (m/s) of the source locations where butterflies were samples
we used a survey dataset with 510 fruit-feeding butterflies comprising 20 species across two heterogeneous habitats within a city in Nigeria. Next, we constructed generalised linear mixed models to understand the differential responses of the butterfly community to changes in environmental conditions across habitats.