Camera traps enable the estimation of herbaceous aboveground net primary production (ANPP) in an African savanna at high temporal resolution

Abstract

Determining the drivers of aboveground net primary production (ANPP), a key ecosystem process, is an important goal of ecosystem ecology. However, accurate estimation of ANPP across larger areas remains challenging, especially for savanna ecosystems that are characterized by large spatiotemporal heterogeneity in ANPP. Satellite remote sensing methods are frequently used to estimate productivity at the landscape scale but generally lack the spatial and temporal resolution to capture the determinants of productivity variation. Here, we developed and tested methods for estimating herbaceous productivity as an alternative to labour-intensive repeated biomass clipping and caging of small plots. We compared measures of three spectral greenness indices, normalized difference vegetation index derived from Sentinel-2 (NDVIs) and a handheld radiometer (NDVIg), and green chromatic coordinate derived from digital repeat cameras (GCC) and tested their relationship to biweekly field-measured herbaceous ANPP using movable exclosures. We found that a satellite-based model including average NDVIs and its rate of change (ΔNDVIs) over the biweekly productivity measurement interval predicted herbaceous ANPP reasonably well (Jackknife R 2 = 0.26). However, the predictive accuracy doubled (Jackknife R 2 = 0.52) when including the sum of day to day increases in camera trap-derived vegetation greenness (tGCC). This result can be considered promising, given the current lack of productivity estimation methods at comparable spatiotemporal resolution. We furthermore found that the fine (daily) temporal resolution of GCC time series captured fast vegetation responses to rainfall events that were missed when using a coarser temporal resolution (>2 days). These findings demonstrate the importance of measuring at a fine temporal resolution for predicting herbaceous ANPP in savanna ecosystems. We conclude that camera traps are promising in offering a reliable and costeffective method to estimate productivity in savannas and contribute to a better understanding of ecosystem functioning and its drivers.

Inter‐population variability in movement parameters: practical implications for population density estimation

“…Motion‐sensitive cameras have a passive infrared sensor, which is activated when an animal passes in front of it, and the camera records pictures, videos, or both (Welbourne et al 2016). The use of motion‐sensitive cameras is usually described as a non‐invasive tool with the potential to monitor wildlife in a broad sense, but it also has the potential to monitor vegetation phenology and climatic parameters (Hofmeester et al 2020, Sun et al 2021, Jonge et al 2022). Thus, a wide range of applications have been described for the use of cameras (Caravaggi et al 2017, Niedballa et al 2019, Gilbert et al 2021, Palencia et al 2021, Wevers et al 2021).…”