Staying Grounded: Using Vegetation Indices to Inform Carabid Beetle Conservation

Large parts of China are covered by steppes: more than 40% of the country’s terrestrial surface exhibit different types of grassland. In these ecosystems, carabids constitute one of the most abundant beetles. These carabid or ground beetle communities do not only depend on the biotic and abiotic characteristics of their local habitat but are also influenced by habitat structures at the landscape level. A recently published study by Tsafack et al. (2020) examines the relationships between land cover and carabid abundance at different spatial scales to inform conservation actions.

There are more than 40,000 ground beetle species worldwide.

Strong anthropogenic pressures in the form of climate change and intensive land use modify grasslands all over the world. In the study area in northern China, related processes like desertification and habitat degradation directly influence the local fauna. In the case of the carabid beetles, it is known that their response to landscape features is highly scale-sensitive. This means that their abundance is driven by different factors at different spatial scales, rendering conservation actions complex.

In order to understand differences in carabid abundance in several types of grasslands, Tsafack et al. (2020) explored the influences of landscape features at different spatial scales. To that end, they used several vegetation indices measuring water availability, productivity and other factors. The grassland in the study area was divided into three types: desert steppes with a high proportion of drought-tolerant species, typical steppes exhibiting natural patches of grass, and meadow steppes where species like Festuca brachyphylla and Stipa bungeana dominate the vegetation structure. With the help of pitfall traps, a total of 6873 ground beetles belonging to 25 species were collected. The observed variance in carabid abundance was then related to the vegetation indices to find out which indices predict carabid abundance the most accurately at which spatial scale.

The study area in Ningxia region in northern China. (Modified from Tsafack et al. (2020), p. 3)

The findings by Tsafack et al. (2020) show that the relationship between landscape characteristics and carabid abundance is shaped by the type of grassland, the vegetation index, and the scale considered. Overall, the modified normalized difference water index (MNDWI) was the index with the most significant correlations. Thus, Tsafack et al. (2020) conclude that the MNDWI is the most appropriate index to investigate carabid abundance spatial patterns in the three different types of steppes.

The study further indicates that the influence of landscape features on carabid abundance varies with the type of grassland considered. In general, stronger relationships between landscape characteristics and the number of ground beetle were observed in the meadow steppes than in the desert or typical steppes. The authors assume that the dispersal of carabids is constrained by vegetation in desert steppes due to high vegetation patchiness, while carabids species of the meadow steppe are more mobile and can exploit larger habitats.

Finally, Tsafack et al. (2020) describe how the scale at which the maximum influence of different indices was recorded varied across steppe types and the considered vegetation index: in desert steppes, carabid abundance was correlated with productivity and water availability at a short distance (25 m). Meanwhile, in meadow steppes, ground beetle abundance was correlated with the same two factors at a much larger scale (1250–1500 m). Finally, in typical steppes, different aspects of water occurrence were correlated with carabid abundance at small, intermediate and larger spatial scales.

Given the complex relationship between carabid abundance, vegetation indices and spatial scales, Tsafack et al. (2020) conclude that landscape ecology studies based on remotely sensed data need to systematically take the different indices available at different spatial scales into consideration to comprehensively understand species patterns.

To read the full paper follow this link.

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