Using Eddy Covariance Sensors to Quantify Carbon Metabolism of Peatlands: A Case Study in Turkey

Abstract

Net ecosystem exchange (NEE) of carbon dioxide (CO2) was measured in a cool temperate peatland in northwestern Turkey on a continuous basis using eddy covariance (EC) sensors and multiple (non-)linear regression-M(N)LR-models. Our results showed that hourly NEE varied between −1.26 and 1.06 mg CO2 m−2 s−1, with a mean value of 0.11 mg CO2 m−2 s−1. Nighttime ecosystem respiration (RE) was on average measured as 0.23 ± 0.09 mg CO2 m−2 s−1. Two best-fit M(N)LR models estimated daytime RE as 0.64 ± 0.31 and 0.24 ± 0.05 mg CO2 m−2 s−1. Total RE as the sum of nighttime and daytime RE ranged from 0.47 to 0.87 mg CO2 m−2 s−1, thus yielding estimates of gross primary productivity (GPP) at −0.35 ± 0.18 and −0.74 ± 0.43 mg CO2 m−2 s−1. Use of EC sensors and M(N)LR models is one of the most direct ways to quantify turbulent CO2 exchanges among the soil, vegetation and atmosphere within the atmospheric boundary layer, as well as source and sink behaviors of ecosystems.

Spatiotemporal Variability of Gross Primary Productivity in Türkiye: A Multi-Source and Multi-Method Assessment

“…Here, we compare multiple satellite-based GPP estimates and multiple approaches for time series analysis to interpret decadal-scale GPP trends, using the diverse geography and vegetation of the Republic of Türkiye as a case study. Türkiye has relatively sparse observations from the eddy covariance of surface-atmosphere carbon dioxide exchange from which GPP can be inferred [34][35][36], emphasizing the importance of satellite remote sensing in interpreting carbon cycling dynamics [37]. It also has a relatively large and growing population and a changing climate with increases in temperature and atmospheric heat content [38].…”

Compositing climate change vulnerability of a Mediterranean region using spatiotemporally dynamic proxies for ecological and socioeconomic impacts and stabilities

“…The concept of climate change vulnerability and its three determinants (exposure, sensitivity, and adaptive capacity) for the selection of assessment indicators were first proposed by the Intergovernmental Panel on Climate Change (IPCC) Third Assessment Report (IPCC 2001) and implemented by the IPCC Fourth Assessment Report (IPCC 2007). Climate change vulnerability can be defined as the degree to which a coupled ecologicalsocioeconomic system can secure its stability against (its resilience and resistance to) negative interaction effects of climate change (Williamson et al 2008;Evrendilek et al 2011;Young et al 2015). Climate change vulnerability is a dynamic ecosystem state that spatiotemporally changes in response not only to the regime (nature, magnitude, frequency, and severity) of climate change impacts but also to the degree of ecological and socioeconomic stabilities (Evrendilek et al 2011;Birkmann et al 2013).…”

“…Climate change vulnerability can be defined as the degree to which a coupled ecologicalsocioeconomic system can secure its stability against (its resilience and resistance to) negative interaction effects of climate change (Williamson et al 2008;Evrendilek et al 2011;Young et al 2015). Climate change vulnerability is a dynamic ecosystem state that spatiotemporally changes in response not only to the regime (nature, magnitude, frequency, and severity) of climate change impacts but also to the degree of ecological and socioeconomic stabilities (Evrendilek et al 2011;Birkmann et al 2013). Ecological and socioeconomic stabilities are used here to refer to the coupled ecological and socioeconomic capacity to cope with and mitigate climate change impacts.…”