Monitoring the abundance of saproxylic red-listed species in a managed beech forest by landsat temporal metrics

  Background  Rapid climate changes lead to an increase in forest disturbance, which in turn lead to growing concerns for biodiversity. While saproxylic beetles are relevant indicators for studying different aspects of biodiversity, most are smaller than 2 ​mm and difficult to sample. This, together with a high number of species and trophic roles, make their study remarkably challenging, time-consuming, and expensive.

  Methods  With this aim, we constructed a Landsat-derived NDVI TS (1984–2020) and we summarised the NDVI trend over time by calculating eight Temporal Metrics (TMs) among which four resulted particularly successful in predicting the amount of saproxylic insects: (i) the slope of the regression line obtained by linear interpolating the NDVI values over time; (ii) the Root Mean Square Error (RMSE) between the regression line and the NDVI TS; (iii) the median, and the (iv) minimum values of the NDVI TS.

  Results  The alpha diversity and species richness analysis indicate dissimilarities across the four monitored sectors (Shannon and Simpson's index ranging between 0.67 to 2.31 and 0.69 to 0.88, respectively), with Landsat TS resulting in effective predictors for estimating saproxylic beetle richness. The strongest correlation was reached between the Monotomidae family and the RMSE temporal metric (R ​= ​0.66). The mean absolute correlation (r) between the NDVI TMs and the saproxylic community was 0.46 for Monotomidae, 0.31 for Cerambycidae, and 0.25 for Curculionidae.

  Conclusions  Our results suggest that Landsat TS has important implications for studying saproxylic beetle distribution and, by helping the selection of monitoring areas, increasing the amount of information acquired while decreasing the effort required for field analysis.