Abstract
Field-based thermal infrared cameras provide surface temperature information at very high spatial and temporal resolution and could complement existing phenological camera and spectral sensor networks. Since temperature is one of the main drivers of ecosystem respiration (ER), field-based thermal cameras offer a new opportunity to model and upscale ER in unprecedented detail. We present such an approach based on manual chamber CO2 flux measurements and thermal imagery from a tower-based camera and from Unmanned Aerial Vehicle (UAV) flights. Data were collected over two growing seasons, including the hot drought of 2018, for the two main vegetation microforms (hummock and hollow) of a hemi-boreal peatland in Sweden. Thermal imagery proved suitable for modelling ER in this ecosystem: ER model accuracies were similar when air, soil or surface temperature measurements were used as input. Our findings allowed us to upscale ER using UAV-derived thermal images and we present maps of ER at sub-decimeter resolution (<7 cm). The significantly different ER measured for each microform highlighted the importance of modelling their ER separately. Not accounting for these differences and the microforms' spatial distribution across the peatland led to a bias in upscaled ER of up to 18%. As a result of the severity and timing of the hot drought in 2018, we observed reductions in the ER of both microforms, but more so for hummocks (-48%) than for hollows (-15%), and modelled ER leveled off at high temperatures. These findings indicate that peatland carbon loss during hot droughts may be lower than expected and strongly relates to vegetation composition. The presented upscaling approach offers a new method to analyse how ER varies across a peatland or within a flux-tower footprint, and to interpret biases that occur when using coarse resolution satellite data to upscale chamber or tower-based flux measurements.
Highlights
Respiration is the production of carbon dioxide (CO2) by living or ganisms as they grow, live and decompose and ecosystem respiration (ER) is the sum of respiration from all vegetation and soil fauna within a specific ecosystem
This study investigates, at a hemi-boreal peatland, what improve ments high resolution surface temperature data from tower- and UAVmounted thermal cameras could bring to ER modelling compared to using sparse air and soil temperature data
We present a novel approach for upscaling ecosystem respiration (ER) at a hemi-boreal peatland in Sweden
Summary
Respiration is the production of carbon dioxide (CO2) by living or ganisms as they grow, live and decompose and ecosystem respiration (ER) is the sum of respiration from all vegetation and soil fauna within a specific ecosystem. Since ER is the sum of multiple above- and below-ground processes, there are ongoing discussions of what temperature metric (air, soil or surface temperature) is most appropriate to use in ER modelling (Las slop et al, 2012; Wohlfahrt and Galvagno, 2017). One of the major limitations of temperature measurements is their coarse spatial resolu tion, with air and soil temperature sensors usually limited to one or a handful of locations around a study site. Recent studies have highlighted this limitation, by showing that microclimate can vary widely within an ecosystem, leading to large deviations from standardized air and soil temperature measurements at a single location (Lembrechts and Lenoir, 2020; Zellweger et al, 2019). Leaf surface tem peratures may differ by >40◦C from air temperature (Still et al, 2019) whilst maximum air temperature can vary by 20◦C over a few hectares (Maclean, 2020)
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