Seasonal hysteresis of net ecosystem exchange in response to temperature change: patterns and causes

Understanding how net ecosystem exchange (NEE) changes with temperature is central to the debate on climate change‐carbon cycle feedbacks, but still remains unclear. Here, we used eddy covariance measurements of NEE from 20 FLUXNET sites (203 site‐years of data) in mid‐ and high‐latitude forests to investigate the temperature response of NEE. Years were divided into two half thermal years (increasing temperature in spring and decreasing temperature in autumn) using the maximum daily mean temperature. We observed a parabolic‐like pattern of NEE in response to temperature change in both the spring and autumn half thermal years. However, at similar temperatures, NEE was considerably depressed during the decreasing temperature season as compared with the increasing temperature season, inducing a counter‐clockwise hysteresis pattern in the NEE–temperature relation at most sites. The magnitude of this hysteresis was attributable mostly (68%) to gross primary production (GPP) differences but little (8%) to ecosystem respiration (ER) differences between the two half thermal years. The main environmental factors contributing to the hysteresis responses of NEE and GPP were daily accumulated radiation. Soil water content (SWC) also contributed to the hysteresis response of GPP but only at some sites. Shorter day length, lower light intensity, lower SWC and reduced photosynthetic capacity may all have contributed to the depressed GPP and net carbon uptake during the decreasing temperature seasons. The resultant hysteresis loop is an important indicator of the existence of limiting factors. As such, the role of radiation, LAI and SWC should be considered when modeling the dynamics of carbon cycling in response to temperature change.     

Spatial variability and controls over biomass stocks,carbon fluxes,and resource-use efficiencies across forest ecosystems

Key message

Stand age, water availability, and the length of the warm period are the most influencing controls of forest structure, functioning, and efficiency.

Abstract

We aimed to discern the distribution and controls of plant biomass, carbon fluxes, and resource-use efficiencies of forest ecosystems ranging from boreal to tropical forests. We analysed a global forest database containing estimates of stand biomass and carbon fluxes (400 and 111 sites, respectively) from which we calculated resource-use efficiencies (biomass production, carbon sequestration, light, and water-use efficiencies). We used the WorldClim climatic database and remote-sensing data derived from the Moderate Resolution Imaging Spectroradiometer to analyse climatic controls of ecosystem functioning. The influences of forest type, stand age, management, and nitrogen deposition were also explored. Tropical forests exhibited the largest gross carbon fluxes (photosynthesis and ecosystem respiration), but rather low net ecosystem production, which peaks in temperate forests. Stand age, water availability, and length of the warm period were the main factors controlling forest structure (biomass) and functionality (carbon fluxes and efficiencies). The interaction between temperature and precipitation was the main climatic driver of gross primary production and ecosystem respiration. The mean resource-use efficiency varied little among biomes. The spatial variability of biomass stocks and their distribution among ecosystem compartments were strongly correlated with the variability in carbon fluxes, and both were strongly controlled by climate (water availability, temperature) and stand characteristics (age, type of leaf). Gross primary production and ecosystem respiration were strongly correlated with mean annual temperature and precipitation only when precipitation and temperature were not limiting factors. Finally, our results suggest a global convergence in mean resource-use efficiencies.     

Variation in above‐ground forest biomass across broad climatic gradients

Aim An understanding of the relationship between forest biomass and climate is needed to predict the impacts of climate change on carbon stores. Biomass patterns have been characterized at geographically or climatically restricted scales, making it unclear if biomass is limited by climate in any general way at continental to global scales. Using a dataset spanning multiple climatic regions we evaluate the generality of published biomass–climate correlations. We also combine metabolic theory and hydraulic limits to plant growth to first derive and then test predictions for how forest biomass should vary with maximum individual tree biomass and the ecosystem water deficit. Location Temperate forests and dry, moist and wet tropical forests across North, Central and South America. Methods A forest biomass model was derived from allometric functions and power‐law size distributions. Biomass and climate were correlated using extensive forest plot (276 0.1‐ha plots), wood density and climate datasets. Climate variables included mean annual temperature, annual precipitation, their ratio, precipitation of the driest quarter, potential and actual evapotranspiration, and the ecosystem water deficit. The water deficit uniquely summarizes water balance by integrating water inputs from precipitation with water losses due to solar energy. Results Climate generally explained little variation in forest biomass, and mixed support was found for published biomass–climate relationships. Our theory indicated that maximum individual biomass governs forest biomass and is constrained by water deficit. Indeed, forest biomass was tightly coupled to maximum individual biomass and the upper bound of maximum individual biomass declined steeply with water deficit. Water deficit similarly constrained the upper bound of forest biomass, with most forests below the constraint. Main conclusions The results suggest that: (1) biomass–climate models developed at restricted geographic/climatic scales may not hold at broader scales; (2) maximum individual biomass is strongly related to forest biomass, suggesting that process‐based models should focus on maximum individual biomass; (3) the ecosystem water deficit constrains biomass, but realized biomass often falls below the constraint; such that (4) biomass is not strongly limited by climate in most forests so that forest biomass may not predictably respond to changes in mean climate.     

Stand Structure and Recent Climate Change Constrain Stand Basal Area Change in European Forests: A Comparison Across Boreal,Temperate, and Mediterranean Biomes

European forests have a prominent role in the global carbon cycle and an increase in carbon storage has been consistently reported during the twentieth century. Any further increase in forest carbon storage, however, could be hampered by increases in aridity and extreme climatic events. Here, we use forest inventory data to identify the relative importance of stand structure (stand basal area and mean d.b.h.), mean climate (water availability), and recent climate change (temperature and precipitation anomalies) on forest basal area change during the late twentieth century in three major European biomes. Using linear mixed-effects models we observed that stand structure, mean climate, and recent climatic change strongly interact to modulate basal area change. Although we observed a net increment in stand basal area during the late twentieth century, we found the highest basal area increments in forests with medium stand basal areas and small to medium-sized trees. Stand basal area increases correlated positively with water availability and were enhanced in warmer areas. Recent climatic warming caused an increase in stand basal area, but this increase was offset by water availability. Based on recent trends in basal area change, we conclude that the potential rate of aboveground carbon accumulation in European forests strongly depends on both stand structure and concomitant climate warming, adding weight to suggestions that European carbon stocks may saturate in the near future.     

Improving predictions of tropical forest response to climate change through integration of field studies and ecosystem modeling

Tropical forests play a critical role in carbon and water cycles at a global scale. Rapid climate change is anticipated in tropical regions over the coming decades and, under a warmer and drier climate, tropical forests are likely to be net sources of carbon rather than sinks. However, our understanding of tropical forest response and feedback to climate change is very limited. Efforts to model climate change impacts on carbon fluxes in tropical forests have not reached a consensus. Here, we use the Ecosystem Demography model (ED2) to predict carbon fluxes of a Puerto Rican tropical forest under realistic climate change scenarios. We parameterized ED2 with species‐specific tree physiological data using the Predictive Ecosystem Analyzer workflow and projected the fate of this ecosystem under five future climate scenarios. The model successfully captured interannual variability in the dynamics of this tropical forest. Model predictions closely followed observed values across a wide range of metrics including aboveground biomass, tree diameter growth, tree size class distributions, and leaf area index. Under a future warming and drying climate scenario, the model predicted reductions in carbon storage and tree growth, together with large shifts in forest community composition and structure. Such rapid changes in climate led the forest to transition from a sink to a source of carbon. Growth respiration and root allocation parameters were responsible for the highest fraction of predictive uncertainty in modeled biomass, highlighting the need to target these processes in future data collection. Our study is the first effort to rely on Bayesian model calibration and synthesis to elucidate the key physiological parameters that drive uncertainty in tropical forests responses to climatic change. We propose a new path forward for model‐data synthesis that can substantially reduce uncertainty in our ability to model tropical forest responses to future climate.     

Biotic and Abiotic Controls Over Canopy Function and Structure in Humid Hawaiian Forests

Foliar nitrogen (N) plays a key role in ecosystem function and dynamics, including processes such as photosynthesis, productivity, and decomposition. Aboveground carbon density (ACD Mg C ha^?1) represents a cumulative functional outcome of these and other ecosystem processes and is an important metric for monitoring current carbon stocks. Despite their importance, multiple interacting controls over landscape-level variation in foliar N and ACD are poorly understood. We assessed the relative importance of individual ecologically important state factors (climate, substrate, age, vegetation, and topography) associated with canopy foliar N and ACD throughout a humid forest landscape. We combined high-resolution remotely sensed data, machine learning, and field data to map and assess canopy foliar N and ACD patterns across a 5016-ha forest reserve in Hawai‘i. Distance to non-native forests had the largest relative influence on canopy foliar N concentration, followed by mean annual temperature (MAT), vegetation type, precipitation, soil, canopy height, and substrate age. In contrast, soil type was the strongest determinant of spatial variability in ACD, followed by precipitation, MAT, and vegetation type. Similar to foliar N, climate and vegetation variables were associated with ACD. However, soil type was found to be much more important in the ACD model (30%) than in the foliar N model (4%). Landscape-scale patterns in canopy foliar N and ACD are the result of shifts in vegetation type and composition, most likely due to species’ responses to past disturbances, current climate conditions, and available nutrients. Degradation of native forests and future climate changes could result in highly altered biogeochemical cycles.     

北京山区3种暖温带森林生态系统未来碳平衡的模拟与分析

 使用LPJ-GUESS植被动态模型, 在北京山区研究了未来100 a以辽东栎(Quercus liaotungensis)为优势种的落叶阔叶林、以白桦(Betula platyphylla)为主的阔叶林和油松(Pinus tabulaeformis)为优势种的针阔混交林的碳变化, 定量分析了生态系统净初级生产力(NPP)、土壤异养呼吸(R_h)、净生态系统碳交换(NEE)和碳生物量(Carbon biomass)对两种未来气候情景(SRES A2和B2)以及相应大气CO₂浓度变化情景的响应特征。结果表明: 1)未来100 a两种气候情景下3种森林生态系统的NPP和R_h均增加, 并且A2情景下增加的程度更大; 2)由于3种生态系统树种组成的不同, 未来气候情景下各自NPP和R_h增加的比例不同, 导致三者NEE的变化也相异: 100 a后辽东栎林由碳汇转变为弱碳源, 白桦林仍保持为碳汇但功能减弱, 油松林成为一个更大的碳汇; 3) 3种森林生态系统的碳生物量在未来气候情景下均增大, 21世纪末与20世纪末相比: 辽东栎林在A2情景下碳生物量增加的比例为27.6%, 大于B2情景下的19.3%; 白桦林和油松林在B2情景下碳生物量增加的比例分别为34.2%和52.2%, 大于A2情景下的30.8%和28.4%。     

Environmental controls over carbon exchange of three forest ecosystems in eastern China

Net ecosystem productivity (NEP) was continuously measured using the eddy covariance (EC) technique from 2003 to 2005 at three forest sites of ChinaFLUX. The forests include Changbaishan temperate mixed forest (CBS), Qianyanzhou subtropical coniferous plantation (QYZ), and Dinghushan subtropical evergreen broad‐leaved forest (DHS). They span wide ranges of temperature and precipitation and are influenced by the eastern Asian monsoon climate to varying extent. In this study, we estimated ecosystem respiration (RE) and gross ecosystem productivity (GEP). Comparison of ecosystem carbon exchange among the three forests shows that RE was mainly determined by temperature, with the forest at CBS exhibiting the highest temperature sensitivity among the three ecosystems. The RE was highly dependent on GEP across the three forests, and the ratio of RE to GEP decreased along the North–South Transect of Eastern China (NSTEC) (i.e. from the CBS to the DHS), with an average of 0.77 ± 0.06. Daily GEP was mainly influenced by temperature at CBS, whereas photosynthetic photon flux density was the dominant factor affecting the daily GEP at both QYZ and DHS. Temperature mainly determined the pattern of the interannual variations of ecosystem carbon exchange at CBS. However, water availability primarily controlled the interannual variations of ecosystem carbon exchange at QYZ. At DHS, NEP attained the highest values at the beginning of the dry seasons (autumn) rather than the rainy seasons (summer), probably because insufficient radiation and frequent fog during the rainy seasons hindered canopy photosynthesis. All the three forest ecosystems acted as a carbon sink from 2003 to 2005. The annual average values of NEP at CBS, QYZ, and DHS were 259 ± 19, 354 ± 34, and 434 ± 66 g C m⁻² yr⁻¹, respectively. The slope of NEP that decreased with increasing latitude along the NSTEC was markedly different from that observed on the forest transect in the European continent. Long‐term flux measurements over more forest ecosystems along the NSTEC will further help verify such a difference between the European forest transect and the NSTEC and provide insights into the responses of ecosystem carbon exchange to climate change in China.     

Measurements of gross and net ecosystem productivity and water vapour exchange of a Pinus ponderosa ecosystem,and an evaluation of two generalized models

Net ecosystem productivity (NEP), net primary productivity (NPP), and water vapour exchange of a mature Pinus ponderosa forest (44°30′ N, 121°37′ W) growing in a region subject to summer drought were investigated along with canopy assimilation and respiratory fluxes. This paper describes seasonal and annual variation in these factors, and the evaluation of two generalized models of carbon and water balance (PnET‐II and 3‐PG) with a combination of traditional measurements of NPP, respiration and water stress, and eddy covariance measurements of above‐and below‐canopy CO₂ and water vapour exchange. The objective was to evaluate the models using two years of traditional and eddy covariance measurements, and to use the models to help interpret the relative importance of processes controlling carbon and water vapour exchange in a water‐limited pine ecosystem throughout the year. PnET‐II is a monthly time‐step model that is driven by nitrogen availability through foliar N concentration, and 3‐PG is a monthly time‐step quantum‐efficiency model constrained by extreme temperatures, drought, and vapour pressure deficits. Both models require few parameters and have the potential to be applied at the watershed to regional scale. There was 2/3 less rainfall in 1997 than in 1996, providing a challenge to modelling the water balance, and consequently the carbon balance, when driving the models with the two years of climate data, sequentially. Soil fertility was not a key factor in modelling processes at this site because other environmental factors limited photosynthesis and restricted projected leaf area index to ～1.6. Seasonally, GEP and LE were overestimated in early summer and underestimated through the rest of the year. The model predictions of annual GEP, NEP and water vapour exchange were within 1–39% of flux measurements, with greater disparity in 1997 because soil water never fully recharged. The results suggest that generalized models can provide insights to constraints on productivity on an annual basis, using a minimum of site data.     

Significant Mean and Extreme Climate Sensitivity of Norway Spruce and Silver Fir at Mid-Elevation Mesic Sites in the Alps

Climate forcing is the major abiotic driver for forest ecosystem functioning and thus significantly affects the role of forests within the global carbon cycle and related ecosystem services. Annual radial increments of trees are probably the most valuable source of information to link tree growth and climate at long-term time scales, and have been used in a wide variety of investigations worldwide. However, especially in mountainous areas, tree-ring studies have focused on extreme environments where the climate sensitivity is perhaps greatest but are necessarily a biased representation of the forests within a region. We used tree-ring analyses to study two of the most important tree species growing in the Alps: Norway spruce (Picea abies) and silver fir (Abies alba). We developed tree-ring chronologies from 13 mesic mid-elevation sites (203 trees) and then compared them to monthly temperature and precipitation data for the period 1846–1995. Correlation functions, principal component analysis and fuzzy C-means clustering were applied to 1) assess the climate/growth relationships and their stationarity and consistency over time, and 2) extract common modes of variability in the species responses to mean and extreme climate variability. Our results highlight a clear, time-stable, and species-specific response to mean climate conditions. However, during the previous-year''s growing season, which shows the strongest correlations, the primary difference between species is in their response to extreme events, not mean conditions. Mesic sites at mid-altitude are commonly underrepresented in tree-ring research; we showed that strong climatic controls of growth may exist even in those areas. Extreme climatic events may play a key role in defining the species-specific responses on climatic sensitivity and, with a global change perspective, specific divergent responses are likely to occur even where current conditions are less limited.