Fragmentation of natural habitats can be detrimental for species if individuals fail to cross habitat boundaries to reach new locations, thereby reducing functional connectivity. Connectivity is crucial for species shifting their ranges under climate change, making it important to understand factors that might prevent movement through human-modified landscapes. In tropical regions, rain forests are being fragmented by agricultural expansion, potentially isolating populations of highly diverse forest-dependent species. The likelihood of crossing habitat boundaries is an important determinant of species dispersal through fragmented landscapes, and so we examined movement across rain forest-oil palm plantation boundaries on Borneo by using relatively mobile nymphalid butterflies as our model study taxon. We marked 1666 individuals from 65 species, and 19 percent (100/527) of recaptured individuals crossed the boundary. Boundary crossing was relatively frequent in some species, and net movement of individuals was from forest into plantation. However, boundary crossing from forest into plantation was detected in less than 50 percent (12/28) of recaptured species and was dominated by small-sized butterfly species whose larval host plants occurred within plantations. Thus, while oil palm plantations may be relatively permeable to some species, they may act as barriers to the movement of forest-dependent species (i.e., species that require rain forest habitat to breed), highlighting the importance of maintaining forest connectivity for conserving rain forest species.
Raw butterfly capture data
Raw data on the capture/recapture events of each individual butterfly marked and captured in the field during the study. See ReadMe file for description of column headings.
RawButterflyCaptureData.csv
R script for summary statistics and chi-squared
R script file containing code to calculate summary statistics (e.g. the number of individuals captured/recaptured/crossing the boundary etc.) and chi-squared tests presented in the study. Calculations for Figure 3 are also included.
SummaryStatisticsChi2_Script.R
Distances moved (n=20 species)
File containing total distances (m) moved by forest and plantation individuals (individuals marked in forest and plantations, respectively) that were recaptured during the study. All species (n=20) that were recaptured in a different trap are included in the dataset.
Column headings:
UniqueIDF: Unique number given to every forest individual to study its movement.
TotDistF: Total distance moved (m) by each forest individual that moved to a different trap.
UniqueIDP: Unique number given to every plantation individual to study its movement.
TotDistP: Total distance moved (m) by each plantation individual that moved to a different trap.
TotalDistances20Species.csv
Distances moved (n=12 species)
File containing total distances (m) moved by forest and plantation individuals (individuals marked in forest and plantations, respectively) that were recaptured during the study. Only species that were recaptured in both habitats and moved to a different trap are included in the dataset (n=12 species).
Column headings:
UniqueIDF: Unique number given to every forest individual to study its movement.
TotDistF: Total distance moved (m) by each forest individual that moved to a different trap.
UniqueIDP: Unique number given to every plantation individual to study its movement.
TotDistP: Total distance moved (m) by each plantation individual that moved to a different trap.
TotalDistances12Species.csv
R script for analysis of distances moved
R script file containing code to calculate total distances moved by forest and plantation individuals and analyse differences in these distances using Mann-Whitney U tests.
DistancesMoved_Script.R
GLMM input variables
Input variables used in Generalized Linear Mixed Models (GLMMs) that examine whether the proportion of individuals per species crossing the habitat boundary was influenced by species' traits, abundance and habitat of first capture. See ReadMe file for description of column headings.
GLMMInputVariables.csv
GLMM input variables with site identity
Input variables used in Generalized Linear Mixed Models (GLMMs) that examine whether the proportion of individuals per species crossing the habitat boundary was influenced by species' traits, abundance and habitat of first capture. Site identity was included as a random effect in this analysis. See ReadMe file for description of column headings.
GLMMInputVariablesSite.csv
R script for GLMM analysis
R script file containing code to perform Generalized Linear Mixed Models (GLMMs) that examine the influence of species traits, abundance and habitat of first capture on boundary crossing. This also includes code for calculating logit probabilities and confidence intervals used in Figure 4, as well as the supplementary analysis whereby site identity was included as a random effect (Appendix S2 and Table S2).
GLMMAnalysis_Script.R
Forest habitat measurements
Data from the 13 environmental characteristics measured in forest habitats in order to assess the similarity of sample sites. See ReadMe file for description of column headings.
ForestHabitatMeasurements.csv
Plantation habitat measurements
Data from the five environmental characteristics measured in plantation habitats in order to assess the similarity of sample sites. See ReadMe file for description of column headings.
PlantationHabitatMeasurements.csv