Aim Butterflies are considered important indicators representing the state of biodiversity and key ecosystem functions, but their use as bioindicators requires better understanding of how their observed response link to environmental factors. Moreover, better understanding how butterfly faunas vary with climate and land cover may be useful to estimate the potential impacts of various drivers, including climate change, botanical succession, grazing, and afforestation. It is particularly important to establish which species of butterflies are sensitive to each environmental driver. Location Israel, including the West Bank and Golan Heights. Methods To develop a robust and systematic approach for identifying how butterfly faunas vary with the environment, we analysed the occurrence of 73 species and the abundance of 24 species from Israeli Butterfly Monitoring Scheme (BMS-IL) data. We used Regional Generalised Additive Models to quantify butterfly abundance, and generalised linear latent variable models and generalised linear models to quantify the impact of temperature, rainfall, soil type, and habitat on individual species and on the species community. Results Species richness was higher along cooler transects, and also for hilly and mountainous transects in the Mediterranean region (rendzina and Terra Rossa soils) compared with the coastal plain (Hamra soil) and semi-arid northern Jordan Vale (loessial serozem soil). Species occurrence was better explained by temperature (negative correlation) than precipitation, while for abundance the opposite pattern was found. Soil type and habitat were insignificant drivers of occurrence and abundance. Conclusions Butterfly faunas responded very strongly to temperature, even when accounting for other environmental factors. We expect that some butterfly species will disappear from marginal sites with global warming, and a large proportion will become rarer as the region becomes increasingly arid.

These are summary data from Pollard (1977) transects of the Israeli Butterfly Monitoring Scheme (BMS-IL). The species occurrence data are taken from transects surveyed for at least 5 years (taking only the first five years for transects surveyed for longer). The species abundance data are sums of actual and imputed (modeled) counts of 24 easy to identify species for 2019. Imputed counts were calculated using Regional Generalized Additive Models (Regional GAM; Schmucki et al., 2016) through the package rbms version 1.0.0 (Schmucki et al., 2019). For more details, see the full text (Comay et al, 2021).

References

Comay, O., Ben-Yehuda, O., Schwartz-Tzachor, R., Benyamini, D., Pe'er, I., Ktalav, I. and Pe'er G. 2021. Environmental controls on butterfly occurrence and species richness in Israel: The importance of temperature over rainfall. Ecology and Evolution.

Pollard, E. (1977). A method for assessing changes in the abundance of butterflies. Biological Conservation, 12, 115-134.

Schmucki, R., Pe’er, G., Roy, D. B., Stefanescu, C., Van Swaay, C. A. M., Oliver, T. H. … Julliard, R. (2016). Regionally informed abundance index for supporting integrative analyses across butterfly monitoring schemes. Journal of Applied Ecology, 53, 501-510. https://doi.org/10.1111/1365-2664.12561

Schmucki R., Harrower C.A., Dennis E.B. (2019) rbms: Computing generalised abundance indices for butterfly monitoring count data. R package version 1.0.0. https://github.com/RetoSchmucki/rbms

Table columns:
transectCode - a unique identifier for the transect. Each transect is divided into 50 meter sections. Note that some (but not all) of the transects appear in both tables.
Site.Name.Heb - The Hebrew name of the transect (in Hebrew alphabet).
Site.Name.Eng - Latin transcription og the Hebrew Name of the transect. Sometimes with English translations, when appropriate (e.g. south, west, botanical garden etc.).
first.monitoring.date - The first date of monitoring at the transect, during the relevant period: first 5 years for occurrence data, 2019 for abundance data.
last.monitoring,date - The last date of monitoring at the transect, during the relevant period: first 5 years for occurrence data, 2019 for abundance data.
no.of.visits - Number of monitoring visits at the transects, during the relevant period: first 5 years for occurrence data, 2019 for abundance data.
Grassland, Scrubland, Forest and Garden are given as fraction of the entire transect, calculated based on the no. of sections of each habitat type (summed up to 1).
Habitat - the dominant habitat(s) type(s) at the transect.
Community.Heb - The Hebrew name of the volunteer community into which the transect belongs (in Hebrew alphabet).
Community - Latin transcription of the Hebrew name of the volunteer community into which the transect belongs. "Independs" are transects monitored by volunteers who are not a part of a volunteer community.
Longitude and Latitude are given in decimal degrees, in the WGS84 coordinate reference system, and relate to the transects' starting point.
mean.annual.temp - Mean annual temperature, in degrees Celsius.
rainfall - Mean annual rainfall, in mm.
no.of.sections - Number of 50-meter-sections.
Soil.English - English name of the soil type at the transect. Nomenclature follows Singer (2007).
Soil.group - Higher (coarser) grouping of soil types.
scaled.temp - Mean annual temperature, scaled and centered.
scaled.rain - Mean annual rainfall, scaled and centered.

The species abundance data are sums of actual and imputed (modeled) counts of 24 easy to identify species for 2019. Imputed counts were calculated using Regional
Generalized Additive Models (Regional GAM; Schmucki et al., 2016) through the package rbms version 1.0.0 (Schmucki et al., 2019).
Table columns unique to the abundance table:
total.abundance - Sum of all species' abundances.
abund.wo.V.cardui - Sum of all species' abundances, save Vanessa cardui (the most abundant species at 2019).

The species occurrence columns are binary (0 or 1), and indicate whether the species was observed in the transect at least once in its first 5 years of monitoring.
Transects monitored for less then 5 years were excluded.
Table columns unique to the occurrence table:
species.richness - Species richness, i.e. the number of species observed at the transect during its first 5 years of monitoring

Rdata files can be read with R and its package gllvm (Niku et al., 2019; 2020).

Niku, J., Brooks, W., Herliansyah, R., Hui, F. K. C., Taskinen, S. & Warton, D. I. (2020). gllvm: Generalized Linear Latent Variable Models. R package version 1.2.0.  https://CRAN.R-project.org/package=gllvm

Niku, J., Hui, F. K. C., Taskinen, S. & Warton, D. I. (2019). gllvm: Fast analysis of multivariate abundance data with generalized linear latent variable models in R. Methods in Ecology and Evolution, 10, 2173-2181. https://doi.org/10.1111/2041-210X.13303

Singer, A. (2007). The soils of Israel. Springer-Verlag Berlin Heidelberg. https://doi.org/10.1007/978-3-540-71734-8