Divergent long‐term trends and interannual variation in ecosystem resource use efficiencies of a southern boreal old black spruce forest 1999–2017

Long‐term trends in ecosystem resource use efficiencies (RUEs) and their controlling factors are key pieces of information for understanding how an ecosystem responds to climate change. We used continuous eddy covariance and microclimate data over the period 1999–2017 from a 120‐year‐old black spruce stand in central Saskatchewan, Canada, to assess interannual variability, long‐term trends, and key controlling factors of gross ecosystem production (GEP) and the RUEs of carbon (CUE = net primary production [NPP]/GEP), light (LUE = GEP/absorbed photosynthetic radiation [APAR]), and water (WUE = GEP/evapotranspiration [E]). At this site, annual GEP has shown an increasing trend over the 19 years (p < 0.01), which may be attributed to rising atmospheric CO₂ concentration. Interannual variability in GEP, aside from its increasing trend, was most strongly related to spring temperatures. Associated with the significant increase in annual GEP were relatively small changes in NPP, APAR, and E, so that annual CUE showed a decreasing trend and annual LUE and WUE showed increasing trends over the 19 years. The long‐term trends in the RUEs were related to the increasing CO₂ concentration. Further analysis of detrended RUEs showed that their interannual variation was impacted most strongly by air temperature. Two‐factor linear models combining CO₂ concentration and air temperature performed well (R²~0.60) in simulating annual RUEs. LUE and WUE were positively correlated both annually and seasonally, while LUE and CUE were mostly negatively correlated. Our results showed divergent long‐term trends among CUE, LUE, and WUE and highlighted the need to account for the combined effects of climatic controls and the ‘CO₂ fertilization effect’ on long‐term variations in RUEs. Since most RUE‐based models rely primarily on one resource limitation, the observed patterns of relative change among the three RUEs may have important implications for RUE‐based modeling of C fluxes.     

Physiological and environmental regulation of interannual variability in CO2 exchange on rangelands in the western United States

For most ecosystems, net ecosystem exchange of CO₂ (NEE) varies within and among years in response to environmental change. We analyzed measurements of CO₂ exchange from eight native rangeland ecosystems in the western United States (58 site‐years of data) in order to determine the contributions of photosynthetic and respiratory (physiological) components of CO₂ exchange to environmentally caused variation in NEE. Rangelands included Great Plains grasslands, desert shrubland, desert grasslands, and sagebrush steppe. We predicted that (1) week‐to‐week change in NEE and among‐year variation in the response of NEE to temperature, net radiation, and other environmental drivers would be better explained by change in maximum rates of ecosystem photosynthesis (A_max) than by change in apparent light‐use efficiency (α) or ecosystem respiration at 10 °C (R₁₀) and (2) among‐year variation in the responses of NEE, A_max, and α to environmental drivers would be explained by changes in leaf area index (LAI). As predicted, NEE was better correlated with A_max than α or R₁₀ for six of the eight rangelands. Week‐to‐week variation in NEE and physiological parameters correlated mainly with time‐lagged indices of precipitation and water‐related environmental variables, like potential evapotranspiration, for desert sites and with net radiation and temperature for Great Plains grasslands. For most rangelands, the response of NEE to a given change in temperature, net radiation, or evaporative demand differed among years because the response of photosynthetic parameters (A_max, α) to environmental drivers differed among years. Differences in photosynthetic responses were not explained by variation in LAI alone. A better understanding of controls on canopy photosynthesis will be required to predict variation in NEE of rangeland ecosystems.     

Canopy‐scale relationships between stomatal conductance and photosynthesis in irrigated rice

Modeling stomatal behavior is critical in research on land–atmosphere interactions and climate change. The most common model uses an existing relationship between photosynthesis and stomatal conductance. However, its parameters have been determined using infrequent and leaf‐scale gas‐exchange measurements and may not be representative of the whole canopy in time and space. In this study, we used a top‐down approach based on a double‐source canopy model and eddy flux measurements throughout the growing season. Using this approach, we quantified the canopy‐scale relationship between gross photosynthesis and stomatal conductance for 3 years and their relationships with leaf nitrogen content throughout each growing season above a paddy rice canopy in Japan. The canopy‐averaged stomatal conductance (g_sc) increased with increasing gross photosynthesis per unit green leaf area (A_g), as was the case with leaf‐scale measurements, and 41–90% of its variation was explained by variations in A_g adjusted to account for the leaf‐to‐air vapor‐pressure deficit and CO₂ concentration using the Leuning model. The slope (m) in this model (g_sc versus the adjusted A_g) was almost constant within a 15‐day period, but changed seasonally. The m values determined using an ensemble dataset for two mid‐growing‐season 15‐day periods were 30.8 (SE = 0.5), 29.9 (SE = 0.7), and 29.9 (SE = 0.6) in 2004, 2005, and 2006, respectively; the overall mid‐season value was 30.3 and did not greatly differ among the 3 years. However, m appeared to be higher during the early and late growing seasons. The ontogenic changes in leaf nitrogen content strongly affected A_g and thus g_sc. In addition, we have discussed the agronomic impacts of the interactions between leaf nitrogen content and g_sc. Despite limitations in the observations and modeling, our canopy‐scale results emphasize the importance of continuous, season‐long estimates of stomatal model parameters for crops using top‐down approaches.     

The role of changes in environmental quality in multitrait plastic responses to environmental and social change in the model microalga Chlamydomonas reinhardtii

Intraspecific variation plays a key role in species'' responses to environmental change; however, little is known about the role of changes in environmental quality (the population growth rate an environment supports) on intraspecific trait variation. Here, we hypothesize that intraspecific trait variation will be higher in ameliorated environments than in degraded ones. We first measure the range of multitrait phenotypes over a range of environmental qualities for three strains and two evolutionary histories of Chlamydomonas reinhardtii in laboratory conditions. We then explore how environmental quality and trait variation affect the predictability of lineage frequencies when lineage pairs are grown in indirect co‐culture. Our results show that environmental quality has the potential to affect intraspecific variability both in terms of the variation in expressed trait values, and in terms of the genotype composition of rapidly growing populations. We found low phenotypic variability in degraded or same‐quality environments and high phenotypic variability in ameliorated conditions. This variation can affect population composition, as monoculture growth rate is a less reliable predictor of lineage frequencies in ameliorated environments. Our study highlights that understanding whether populations experience environmental change as an increase or a decrease in quality relative to their recent history affects the changes in trait variation during plastic responses, including growth responses to the presence of conspecifics. This points toward a fundamental role for changes in overall environmental quality in driving phenotypic variation within closely related populations, with implications for microevolution.     

环境和生物因子对黄河三角洲滨海湿地净生态系统CO2交换的影响

通过涡度相关和微气象观测技术,对黄河三角洲滨海湿地净生态系统CO₂交换(NEE)以及环境、生物因子进行了观测,探究湿地NEE变化规律及环境和生物因子对NEE的影响. 结果表明: 在日尺度上,生长季NEE呈明显“U”型曲线,非生长季变幅较小;在季节尺度上,NEE生长季波动较大,表现为碳汇,非生长季波动较小,表现为碳源;在年尺度上,滨海湿地生态系统表现为碳汇,总净固碳量为-247 g C·m^-2. 白天NEE主要受控于光合有效辐射(PAR),且生态系统表观量子产量(α)与白天生态系统呼吸(R_eco,d)均于8月达到最大值,最大光合速率(A_max)于7月达到最大值;夜间NEE随气温(T_a)呈指数增加趋势,生态系统的温度敏感系数(Q₁₀)为2.5,且土壤含水量(SWC)越高,Q₁₀值越大.非生长季NEE只与净辐射(R_n)呈显著的线性负相关,与其他环境因子无显著相关关系.生长季NEE与R_n、T_a、土壤10 cm温度(T_{s 10})等环境因子以及叶面积指数(LAI)呈显著的线性负相关,但与地上生物量(AGB)无显著相关关系.多元回归分析表明,R_n和LAI对生长季NEE的协同影响达到52%.