Boreal forests play a critical role in the global carbon cycle as they are one of the largest terrestrial carbon sinks globally. In this study, we employ explainable machine learning (ML) techniques to investigate the influence of environmental and vegetation variables on net ecosystem exchange (NEE), focusing specifically on the effects of diffuse radiation. We utilize a sub-hourly resolution data set including satellite and in-situ observations from three boreal or hemiboreal forest research stations across the latitudes 58–68° N to capture latitudinal variability in forest carbon uptake. Using SHAP (Shapley Additive Explanations) values, we identify key drivers influencing NEE and quantify their importance across various ML model architectures. Photosynthetically active radiation (PAR), diffuse radiation, normalized difference vegetation index, and soil temperature were identified as the variables having the largest explanatory power for NEE across the ML models. ML models using only these variables result in $ {R}^2\approx 0.8 $ and RMSE$ \approx 2.3 $ $ \mu \mathrm{mol}\;{\mathrm{m}}^{-2}\hskip0.1em {\mathrm{s}}^{-1} $. Further analysis of SHAP values indicates that higher diffuse radiation (DiffPAR) is associated with more negative NEE (stronger carbon sink). SHAP analysis highlights this effect much more clearly than raw DiffPAR measurements, because it accounts for interactions with other environmental factors. This suggests that the diffuse radiation effect emerges from interactions between DiffPAR and co-varying environmental factors (such as cloudiness and total PAR). Cases identified by SHAP ($ \mathrm{DiffPAR}\ \mathrm{SHAP}<-2 $) have a median NEE $ 1.55\mu \mathrm{mol},{\mathrm{m}}^{-2},{\mathrm{s}}^{-1} $ more negative than cases with raw $ \mathrm{DiffPAR}\ge 400 $. When applied to ML models, SHAP uncovers nonlinear, context-dependent interactions between diffuse radiation and other drivers of NEE without assuming a priori relationships.

Understanding the photosynthetic behaviour, radiation use efficiency (RUE) and water use efficiency (WUE) of potatoes in response to diurnal and seasonal fluctuations in weather, is important for optimizing growth and production. The net ecosystem exchange (NEE) of carbon dioxide (CO2), is a parameter used to measure the balance between gross CO2 assimilation (also referred to as gross primary production (GPP)) and ecosystem respiration (Reco). The objectives of this study were (i) to quantify the NEE of potato grown in two contrasting agro-ecologies and partition NEE into Reco and GPP; (ii) to describe seasonal patterns in daily photosynthesis, RUE and WUE in potato; and (iii) to analyse the variability in photosynthesis rate, RUE and WUE as affected by weather and crop growth stage. We measured CO2 and water vapour fluxes using eddy covariance techniques in potato fields in two production regions of South Africa. The winter crop had higher mean RUE and WUE values, whereas the summer crop absorbed more CO2. RUE had a negative relationship with incident radiation. To optimize dry matter production, WUE and RUE, potato crops must be well established and develop a full canopy early during the season. Maintaining the crop for a longer period in the field has yield benefits, although they appear to decline over time due to reduced efficiencies as the crop matures. The RUE observed over the growing period in the present study was high, relative to findings by other field studies, despite relatively warm growing conditions that were likely sub-optimal for potato.

Measurements were conducted within a fence-exclosure between February 2008 and July 2009 to investigate the influence of soil moisture on ecosystem CO2 fluxes in a Themeda triandra-dominated grassland of a humid Kenyan savanna. Rainout shelters were constructed to reduce ambient rainfall by 0%, 10% and 20% respectively to attain variable soil water content (SWC) during plant growth. SWC within the top 30 cm layer, above-ground biomass, soil and plant nitrogen (N) concentrations were assessed monthly alongside CO2 fluxes. Net ecosystem CO2 exchange (NEE) and ecosystem respiration (Reco) were measured with closed chambers while carbon (C) partitioning during the wet and dry seasons were assessed through pulse 13C labelling. There were significant seasonal and between plot differences in SWC, above-ground biomass, canopy light utilization efficiency (α), CO2 fluxes and C allocation pattern resulting from differences in SWC. The ecosystem was a net C sink during the wet and C neutral during the dry seasons. The study showed strong seasonal fluctuations in ecosystem CO2 fluxes and underscores the significant role of the savanna grasslands in regional C balance due to its expansive nature. The savanna grassland is however vulnerable to low soil moisture, with significant reduction in CO2 uptake during drought.