Relationship of insect biomass and richness with land use along a climate gradient

Abstract

Recently reported insect declines have raised both political and social concern. Although the declines have been attributed to land use and climate change, supporting evidence suffers from low taxonomic resolution, short time series, a focus on local scales, and the collinearity of the identified drivers. In this study, we conducted a systematic assessment of insect populations in southern Germany, which showed that differences in insect biomass and richness are highly context dependent. We found the largest difference in biomass between semi-natural and urban environments (-42%), whereas differences in total richness (-29%) and the richness of threatened species (-56%) were largest from semi-natural to agricultural environments. These results point to urbanization and agriculture as major drivers of decline. We also found that richness and biomass increase monotonously with increasing temperature, independent of habitat. The contrasting patterns of insect biomass and richness question the use of these indicators as mutual surrogates. Our study provides support for the implementation of more comprehensive measures aimed at habitat restoration in order to halt insect declines.

Fig. 1. Overview of the study design and the distribution of the 60 landscapes across the study region.

The 60 quadrants were selected over gradients of elevation and land-use type within the federal state of Bavaria. The colors show the elevation. The insets show examples of a semi-natural and an urban-dominated landscape. The black dots represent the three plots set up in different habitat types.

Fig. 2. Partial effects of season and climate parameters on biomass, total BIN richness and richness of red-listed species.

Partial effects of (a) season, (b) local temperature, (c) humidity (both data logger), (d) long-term mean annual near-surface temperature (1991–2020), and (e) long-term mean annual precipitation (1991–2020) on biomass, total richness of barcode index numbers (BINs), and the richness of red-listed species collected with Malaise traps in 179 plots. Partial effects from generalized additive mixed models (for details, see Table 1) were controlled for elevation, the geographic location of the traps, and land use (for the latter, see Fig. 3). Note that richness was determined for only three of the eight sampling campaigns. (a) partial effect of season, as a smooth term acting multiplicatively on the expected outcome per time unit. Multiplicative effects for local temperature and humidity were estimated using baselines of 10 °C and 40%, respectively. Error envelopes depict standard errors below and above the estimated mean responses.

Fig. 3. Partial effects of land use on insect biomass and diversity (total BIN richness and the richness of red-listed species).

The results of generalized additive mixed models for insect biomass (8 sampling campaigns, n = 1293), richness of barcode index numbers (BINs), and red-listed species (3 sampling campaigns, n = 510) using land-use categories on local and landscape scales. The displayed values are based on comparisons with (a) the local land-use type forest, (b) semi-natural landscapes, and (c) the combined local land-use type forest in semi-natural landscapes. For model parameters, see Table 1. For additional information see annotated code below. Significance was tested by multiple post-hoc comparisons using glht (R package multcomp). Different letters indicate significant differences (p < 0.05) between categories. Note that only the first significant entry for a predictor is shown, subsequent entries between land-use categories, even if significant, were omitted for clarity.

Fig. 4. Taxonomic group and habitat-specific standardized estimates of BIN richness to explain total biomass in a generalized linear mixed model.

The horizontal bars on the right show the total number of BINs per group. Values for BIN richness and total biomass were log-transformed. The vertical gray bar on the left indicates the area outside of which effects are significant.