Gross primary productivity and water use efficiency are increasing in a high rainfall tropical savanna

Eddy covariance measurements reveal a decreased carbon sequestration strength 2010-2022 in an African semiarid savanna

Monitoring the changes of ecosystem functioning is pivotal for understanding the global carbon cycle. Despite its size and contribution to the global carbon cycle, Africa is largely understudied in regard to ongoing changes of its ecosystem functioning and their responses to climate change. One of the reasons is the lack of long-term in situ data. Here, we use eddy covariance to quantify the net ecosystem exchange (NEE) and its components-gross primary production (GPP) and ecosystem respiration (Reco) for years 2010-2022 for a Sahelian semiarid savanna to study trends in the fluxes. Significant negative trends were found for NEE (12.7 ± 2.8 g C m2 year-1), GPP (39.6 ± 7.9 g C m2 year-1), and Reco (32.2 ± 8.9 g C m2 year-1). We found that NEE decreased by 60% over the study period, and this decrease was mainly caused by stronger negative trends in rainy season GPP than in Reco. Additionally, we observed strong increasing trends in vapor pressure deficit, but no trends in rainfall or soil water content. Thus, a proposed explanation for the decrease in carbon sink strength is increasing atmospheric dryness. The warming climate in the Sahel, coupled with increasing evaporative demand, may thus lead to decreased GPP levels across this biome, and lowering its CO2 sequestration.

Rain use efficiency gradients across Australian ecosystems

Rain use efficiency (RUE) quantifies the ecosystem's capacity to use precipitation water to assimilate atmospheric CO2. The spatial distribution of RUE and its drivers across the Australian continent is largely unknown. This knowledge gap limits our understanding of the possible contribution of Australian ecosystems to global carbon assimilation. This study investigates the spatial distribution of RUE across diverse terrestrial ecosystems in Australia. The results show that RUE ranges from 0.43 (1st percentile) to 3.10 (99th percentile) g C m-2 mm-1 with a continental mean of 1.19 g C m-2 mm-1. About 68 % of the spatiotemporal variability of RUE can be explained by a multiple linear regression model primarily contributed by climatic predictors. Benchmarked by the model estimation, drainage-diverging/converging landscapes tend to have reduced/increased RUE. The model also revealed the impact of increasing atmospheric CO2 concentration on RUE. The continental mean RUE would increase by between 29.3 and 64.8 % by the end of this century under the SSP5-8.5 scenario in which the CO2 concentration is projected to double from the present level. This increase in projected RUE is attributed to the assumed greening effect of increasing CO2 concentration, which does not consider the saturation of CO2 fertilisation effect and the warming effect on increasing wildfire occurrence. Under the SSP1-2.6 scenario, RUE would decrease by about 7 %. This study provides baseline RUEs of various ecosystems in Australia for investigating the impacts of human interferences and climate change on the capacity of Australian vegetation to assimilate atmospheric CO2 under given precipitation.

Wetness severity increases abrupt shifts in ecosystem functioning in arid savannas

The accelerating pace of climate change has led to unprecedented shifts in surface temperature and precipitation patterns worldwide, with African savannas being among the most vulnerable regions. Understanding the impacts of these extreme changes on ecosystem health, functioning and stability is crucial. This paper focuses on the detection of breakpoints, indicative of shifts in ecosystem functioning, while also determining relevant ecosystem characteristics and climatic drivers that increase susceptibility to these shifts within the semi-arid to arid savanna biome. Utilising a remote sensing change detection approach and rain use efficiency (RaUE) as a proxy for ecosystem functioning, spatial and temporal patterns of breakpoints in the savanna biome were identified. We then employed a novel combination of survival analysis and remote sensing time series analysis to compare ecosystem characteristics and climatic drivers in areas experiencing breakpoints versus areas with stable ecosystem functioning. Key ecosystem factors increasing savanna breakpoint susceptibility were identified, namely higher soil sand content, flatter terrain and a cooler long-term mean temperature during the wet summer season. Moreover, the primary driver of changes in ecosystem functioning in arid savannas, as opposed to wetter tropical savannas, was found to be the increased frequency and severity of rainfall events, rather than drought pressures. This research highlights the importance of incorporating wetness severity metrics alongside drought metrics to comprehensively understand climate-ecosystem interactions leading to abrupt shifts in ecosystem functioning in arid biomes. The findings also emphasise the need to consider the underlying ecosystem characteristics, including soil, topography and vegetation composition, in assessing ecosystem responses to climate change. While this research primarily concentrated on the southern African savanna as a case study, the methodological robustness of this approach enables its application to diverse arid and semi-arid biomes for the assessment of climate-ecosystem interactions that contribute to abrupt shifts.

A Beginner's Guide to Eddy Covariance: Methodology and Its Applications to Photosynthesis

The eddy covariance technique, commonly applied using flux towers, enables the investigation of greenhouse gas (e.g., carbon dioxide, methane, nitrous oxide) and energy (latent and sensible heat) fluxes between the biosphere and the atmosphere. Through measuring carbon fluxes in particular, eddy covariance flux towers can give insight into how ecosystem scale photosynthesis (i.e., gross primary productivity) changes over time in response to climate and management. This chapter is designed to be a beginner's guide to understanding the eddy covariance method and how it can be applied in photosynthesis research. It introduces key concepts and assumptions that apply to the method, what materials are required to set up a flux tower, as well as practical advice for site installation, maintenance, data management, and postprocessing considerations. This chapter also includes examples of what can go wrong, with advice on how to correct these errors if they arise. This chapter has been crafted to help new users design, install, and manage the best towers to suit their research needs and includes additional resources throughout to further guide successful eddy covariance research activities.

Aerodynamic effects cause higher forest evapotranspiration and water yield reductions after wildfires in tall forests

Wildfires are increasing in frequency, intensity, and extent globally due to climate change and they can alter forest composition, structure, and function. The destruction and subsequent regrowth of young vegetation can modify the ecosystem evapotranspiration and downstream water availability. However, the response of forest recovery on hydrology is not well known with even the sign of evapotranspiration and water yield changes following forest fires being uncertain across the globe. Here, we quantify the effects of forest regrowth after catastrophic wildfires on evapotranspiration and runoff in the world's tallest angiosperm forest (Eucalyptus regnans) in Australia. We combine eddy covariance measurements including pre- and post-fire periods, mechanistic ecohydrological modeling and then extend the analysis spatially to multiple fires in eucalypt-dominated forests in south-eastern Australia by utilizing remote sensing. We find a fast recovery of evapotranspiration which reaches and exceeds pre-fire values within 2 years after the bushfire, a result confirmed by eddy covariance data, remote sensing, and modeling. Such a fast evapotranspiration recovery is likely generalizable to tall eucalypt forests in south-eastern Australia as shown by remote sensing. Once climate variability is discounted, ecohydrological modeling shows evapotranspiration rates from the recovering forest which reach peak values of +20% evapotranspiration 3 years post-fire. As a result, modeled runoff decreases substantially. Contrary to previous research, we find that the increase in modeled evapotranspiration is largely caused by the aerodynamic effects of a much shorter forest height leading to higher surface temperature, higher humidity gradients and therefore increased transpiration. However, increases in evapotranspiration as well as decreases in runoff caused by the young forest are constrained by energy and water limitations. Our result of an increase in evapotranspiration due to aerodynamic warming in a shorter forest after wildfires could occur in many parts of the world experiencing forest disturbances.

Climate warming negatively affects plant water-use efficiency in a seasonal hydroperiod wetland

Climate warming has substantial influences on plant water-use efficiency (PWUE), which is defined as the ratio of plant CO2 uptake to water loss and is central to the cycles of carbon and water in ecosystems. However, it remains uncertain how does climate warming affect PWUE in wetland ecosystems, especially those with seasonally alternating water availability during the growing season. In this study, we used a continuous 10-year (2011-2020) eddy covariance (EC) dataset from a seasonal hydroperiod wetland coupled with a 15-year (2003-2017) satellite-based dataset (called PML-V2) and an in situ warming experiment to examine the climate warming impacts on wetland PWUE. The 10-year EC observational results revealed that rising temperatures had significant negative impacts on the interannual variations in wetland PWUE, and increased transpiration (Et) rather than changes in gross primary productivity (GPP) dominated these negative impacts. Furthermore, the 15-year satellite-based evidence confirmed that, in the study region, climate warming had significant negative consequences for the interannual variations in wetland PWUE by enhancing wetland Et. Lastly, at the leaf-scale, the light response curves of leaf photosynthesis, leaf Et, and leaf-scale PWUE indicated that wetland plants need to consume more water during the photosynthesis process under warmer conditions. These findings provide a fresh perspective on how climate warming influences carbon and water cycles in wetland ecosystems.

Ecohydrological insight: Solar farms facilitate carbon sink enhancement in drylands

Solar farms are critical to tackling climate change and achieving carbon neutrality. Besides producing renewable energy, a solar farm modifies microclimates and changes water distribution, consequently affecting local carbon sequestration capacity (CSC). Yet, how the CSC of an ecosystem responds to these changes after solar farm construction remains inadequately understood. Herein, the SOFAR model was adopted to reveal the effects of large-scale solar farms (LSFs) on CSC in arid northern China, with a series of numeric experiments along a climate gradient (with precipitation ranging from 70 to 500 mm yr^-1). The results show that relative to pristine vegetation background, CSC was non-linearly increased by averages of 3.49-6.68%, 4.43-10.25%, 5.07-9.71% and 5.6% each year after the installation of LSFs in hyper-arid climates (with aridity index or AI = 0.04-0.05), arid climates (AI = 0.14-0.16), semi-arid climates (AI = 0.21-0.3) and semi-humid climates (AI = 0.55), respectively. The increase in available water for plants growing under the drip lines of photovoltaic panels (PVs) in LSFs is confirmed to be the overwhelming factor responsible for CSC enhancement. Although biases remain in the estimation of increased CSC in hyper- and semi-humid regions due to the high variability of climate (e.g., extreme drought events) and serious radiation reduction beneath PVs, it is certain that solar farms facilitate CSC without increasing external land use. These results will deepen our understanding of the feedback between solar farms and ambient environments and be meaningful for vegetation management in solar farms, especially in the context of climate change and carbon neutrality aims.

Inherent Water-Use Efficiency of Different Forest Ecosystems and Its Relations to Climatic Variables

Inherent water-use efficiency (IWUE) is a vital parameter connecting the carbon and water cycles. However, the factors influencing the IWUE in different forest ecosystems are still a subject of debate. In this work, FLUXNET platform measurements of 67 forest sites were used to detect trends of the IWUE of four forest ecosystems, namely deciduous broadleaf forests (DBF), evergreen broadleaf forests (EBF), needle-leaf forests (ENF), and mixed forests (MF). The IWUE differed significantly among different forest ecosystems and positively correlated with temperature and solar radiation. The IWUE of EBF was the highest at 32.02 g·C·Kg·H2O−1. The values of DBF and MF were similar and higher than that of ENF. With increasing latitude, the IWUE increased first and then decreased, with a maximum of 35° N. The IWUE of EBF was negatively correlated with precipitation and leaf area index. Temperature and solar radiation were the main factors controlling the IWUE of forest ecosystems, whereas precipitation was the major factor controlling the inter-annual variation in the ΔIWUE of forest ecosystems. Our results provide a scientific basis for the study of forest carbon sinks, forest eco-hydrological processes, and forest ecosystem responses to global climatic changes.