TY - JOUR
T1 - Camera traps enable the estimation of herbaceous aboveground net primary production (ANPP) in an African savanna at high temporal resolution
AU - de Jonge, Inger K.
AU - Veldhuis, Michiel P.
AU - Vrieling, A.
AU - Olff, Han
N1 - Funding Information:
We thank the management and research staff at Serengeti Wildlife Research Center, Tanzanian Wildlife Research Institute, Tanzanian National Park Authority and Tanzanian Commission for Science and Technology for their help and support while undertaking this study. Second, we thank Emilian Mayemba, Robbert van Gool, James Fredrickson, Toni Hoenders and Neha Mohan Babu for much appreciated help in the field. This study was part of the AfricanBioServices project and funded by the EU Horizon 2020 grant number 641918.
Funding Information:
This study was part of the AfricanBioServices project and funded by the EU Horizon 2020 grant number 641918. Funding Information
Publisher Copyright:
© 2022 The Authors. Remote Sensing in Ecology and Conservation published by John Wiley & Sons Ltd on behalf of Zoological Society of London.
PY - 2022/10
Y1 - 2022/10
N2 - 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 R2 = 0.26). However, the predictive accuracy doubled (Jackknife R2 = 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 cost-effective method to estimate productivity in savannas and contribute to a better understanding of ecosystem functioning and its drivers.
AB - 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 R2 = 0.26). However, the predictive accuracy doubled (Jackknife R2 = 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 cost-effective method to estimate productivity in savannas and contribute to a better understanding of ecosystem functioning and its drivers.
KW - ITC-ISI-JOURNAL-ARTICLE
KW - ITC-GOLD
UR - https://ezproxy2.utwente.nl/login?url=https://library.itc.utwente.nl/login/2022/isi/vrieling_cam.pdf
U2 - 10.1002/rse2.263
DO - 10.1002/rse2.263
M3 - Article
VL - 8
SP - 583
EP - 600
JO - Remote sensing in ecology and conservation
JF - Remote sensing in ecology and conservation
SN - 2056-3485
IS - 5
ER -