Primary Productivity Ecosystem Research Articles

Comprehensive assessment of the climatic and vegetation impacts of wind farms on grasslands: A case study in inner Mongolia, China

Although wind power contributes to the reduction of greenhouse gas emissions, it also has significant impacts on the local climate and vegetation. Exploring these impacts is important for the sustainable development of wind power. Therefore, based on moderate-resolution imaging spectroradiometer (MODIS) data and other remote sensing data from 2003 to 2022, this paper investigated the impacts of 101 grassland wind farms (WFs) in Inner Mongolia on land-atmosphere water and heat exchange, vegetation growth, ecosystem primary productivity, and vegetation structural characteristics during the growing season and revealed the spatial distribution patterns of the impacts of WFs as well as differences between different types of grasslands. The results indicated that WFs increased the nighttime land surface temperature (LST), decreased evapotranspiration (ET), inhibited vegetation growth, decreased gross primary productivity (GPP), and reduced the leaf area index (LAI) in growing season grasslands. This effect varied across different types of grasslands and showed significant complexity. In terms of land-atmosphere water and heat exchange, nighttime LST increases and ET decreases were significant in the typical steppe but not in the meadow steppe. In terms of vegetation change, meadow steppe had the most inhibited vegetation growth and the greatest reduction in GPP. In terms of the impact range, WFs on typical steppe and meadow steppe have opposite effects on vegetation growth and ecosystem primary productivity inside and outside of them, i.e., they inhibit vegetation growth and reduce GPP inside the WF areas but promote vegetation growth and increase GPP outside the WF areas. Compared with previous studies, this study analyzed multiple climate and vegetation indicators based on many WF samples, which reduced the uncertainty associated with a single sample and provided more comprehensive and comparable observations of different types of grasslands. These findings can help to balance the relationship between wind power development and ecological protection.

Assessing two decades of landscape greenness in relation to temperature and precipitation in a tropical dry forest of Northwestern Mexico

Canopy greenness is an indicator of ecosystem primary productivity, which is often limited by temperature and precipitation. Changes in vegetation greening have been reported mostly at global scales. However, we still have a poor understanding of vegetation greening patterns and drivers for major vegetation types, such as the tropical dry forest, one of the most extensive vegetation types in Mexico. Here, we analyze two decades of interannual variation in greenness and its relationship to temperature and precipitation in the northmost neotropical dry forest occurring in Northwestern Mexico. We constructed time-series linear regression models using standardized anomalies with z-scores (i.e., standard deviations away from the long-term mean) for the Normalized Difference Vegetation Index (NDVI) and the climate data from 2001 to 2021. Our best models indicate both temperature and precipitation exert positive effects on vegetation greenness, particularly from a lagged effect perspective, as retained predictors were the accumulated precipitation of two monsoon (summer) seasons and previous year mean temperature. The lowest levels of landscape greenness seem connected to prolonged droughts and extreme frost events. In fact, a switch from negative to positive NDVI anomalies was observed in the years following the February 2011 extreme frost that affected much of North America, including northern Mexico. Notable, under the stricter statistical criterion of −1.7 ≥ z score ≥ 1.7, only climatic variables presented very-extreme anomalies and these were not necessarily linked to a very-extreme response in landscape greenness. However, considering the criterion of −1.3 ≥ z score ≥ 1.3, we identified several extreme NDVI anomalies and their corresponding climatic anomaly. Therefore, more flexible statistical criteria might reveal climate extremes of ecological and social relevance. Our overall findings have implications for forest and climate risk management, particularly as extreme climatic anomalies are expected to continue increasing in light of climate change.

Effects of diffuse light on the gross ecosystem primary productivity of a winter wheat (Triticum aestivum L.) cropland in northern China

Diffuse light is produced by clouds and aerosols in the atmosphere. Exploring the effects of diffuse light on ecosystem productivity is important for understanding the terrestrial carbon (CO2) cycle. Here, 2 years of gross ecosystem primary productivity (GEP) from a (winter) wheat cropland in China was assessed using eddy covariance technology to explore the effects of diffuse photosynthetic active radiance (PAR) on wheat GEP. Wheat GEP increased significantly and positively along with diffuse PAR. In addition, wheat GEP was significantly affected by total PAR, air temperature, and vapor press deficit in different diffuse PAR fraction (fDIF) change stages. Because significant autocorrelations existed among the controlling factors, a path analysis was used to quantify the effects of diffuse light on GEP. Diffuse PAR was the primary and secondary importance factors affecting GEP with direct path coefficients of 0.54 and 0.48, respectively, in different fDIF change stages. A multilayer canopy model revealed that the middle and lower canopy levels intercepted more light when diffuse PAR increased. This resulted in the photosynthetic enhancement of middle and lower canopy levels, which contributed approximately 65% and 35%, respectively, to the increase in photosynthesis for the entire canopy (~ 30.5%). Overall, our study provided new evidence regarding the importance of diffuse light for CO2 uptake in agroecosystems, which is important for predicting the responses of ecosystem CO2 budgets to future climate-related light changes.

Power-law productivity of highly biodiverse agroecosystems supports land recovery and climate resilience

Transformative change in primary food production is urgently needed in the face of climate change and biodiversity loss. Although there are a growing number of studies aimed at global policymaking, actual implementations require on-site analyses of social feasibility anchored by ecological rationale. This article reports the in-depth characterizations of low-input mixed polyculture of highly diverse crops managed on the self-organization of ecosystems, which performed better compared to conventional monoculture methods in Japan and Burkina Faso. Analyses on crop productivity and diversity showed that the primary production of ecosystems followed a power law, and through the underlying mechanisms excelled in (1) promoting diversity and total quantity of products along with the rapid increase of in-field biodiversity, especially useful for the recovery of local regime shift in a semi-arid environment; (2) a fundamental reduction of inputs and environmental load; and (3) ecosystem-based autonomous adaptation of the crop portfolio to climatic variability. The overall benefits imply substantial possibilities of a new typology of sustainable farming for smallholders sensitive to climate change, which could overcome the historical trade-off between productivity and biodiversity based on the human-guided augmentation of ecosystems.

Enhanced ecosystem carbon sink in shrub-grassland ecotone under grazing exclusion on Tibetan plateau

Grassland degradation is a prevalent issue at the interface of shrubland and grassland ecosystems, particularly susceptible to environmental changes. To counteract the degradation, grazing exclusion has been proposed as a dominant restoration strategy on the Tibetan plateau, the world's largest and highest plateau. However, the impact of degradation and subsequent restoration on the carbon dynamics consist of carbon sink / source capacity of shrub-grassland ecotones remain unclear. Therefore, in this study, using a transparent chamber (0.8 m in length × 0.8 m in width × 0.6 m in height) attached to an infrared gas analyzer, the in situ field investigation was performed to measure the gross ecosystem primary productivity (GEP), ecosystem respiration (Re), net ecosystem CO2 exchange (NEE), and environmental factors over a four-year continuous period in lightly and heavily degraded shrub-grassland ecotones during recover process on the Tibetan Plateau. Our result showed that: 1). Shrub-grassland ecotone acts as a net CO2 sink, with the maximum NEE occurring in July during the growing season. 2). Ecotone degradation diminishes the carbon sequestration capacity. Specifically, the annual GEP, Re, and NEE rates decrease by 14.1 %, 7.3 %, and 27.2 %, respectively, in the heavily degraded ecotone compared to the lightly degraded counterpart. 3). Grazing exclusion positively influenced the carbon sequestration capacity, particularly in heavily degraded ecotone, which leads to a substantial increase in the annual GEP, Re, and NEE rates of 15.4 % and 33.4 %, 12.3 % and 20.9 %, 22.25 % and 64.9 % for lightly and heavily degraded ecotones, respectively. 4). A piecewise structural equation model reveals that soil moisture and soil temperature are pivotal drivers influencing NEE. 5) Correlation analysis shows that NEE was negatively correlated with soil temperature during April to June and September to October but was positively correlated with soil temperature during July to August. In contrast, NEE displays a consistent negative correlation with soil moisture throughout the growing season. This research provides new insights on grassland degradation and restoration for carbon sequestration in alpine shrub-grassland ecotones and highlights their implications for sustainable management of alpine ecosystems.

2016–2017年小浪底栓皮栎人工林碳水通量观测数据集

The concern about global change has brought more attention to the role of plantations in the regional carbon and water cycle recently. Quercus variabilis is one of the most widely distributed natural tree species in China. The southern foot of Taihang Mountain is one of the key areas of forestry engineering in China. The study on the observation of water and carbon fluxes in a Quercus variabilis plantation in this area is of great significance to the development of forestry ecological engineering and the evaluation of plantation carbon sink function in China. Henan Xiaolangdi Earth Critical Zone National Research Station on the Middle Yellow River (i.e. XLD) has carried out long-term observation of and research on the carbon and water fluxes in a Quercus variabilis plantation using the eddy covariance technique since 2005. This dataset contains carbon and water flux observations and meteorological data collected from XLD from 2016 to 2017, which have been processed in accordance with the standard quality control system of ChinaFLUX. It covers the data of gross ecosystem primary productivity, ecosystem respiration, net ecosystem carbon exchange, latent heat flux, sensible heat flux and other related meteorological factors, such as air temperature, air relative humidity, vapor pressure, wind speed, wind direction, radiation, soil temperature, soil moisture, precipitation, etc. The dataset is composed of the data collected at the scales of half-hourly, daily, monthly, and yearly intervals. This dataset can provide data support for the management of plantation ecosystems and the assessment of regional carbon budgets. Moreover, it plays a crucial role in promoting data sharing and standardization management of field stations in China.

Drought conditions, aridity and forest structure control the responses of Iberian holm oak woodlands to extreme droughts: A large-scale remote-sensing exploration in eastern Spain

Understanding how Mediterranean forests respond to the increasing frequency of extreme droughts and forest densification is crucial for effective land management in the present context of climate change and land abandonment. We study the responses of Iberian holm oak (Quercus ilex L.) woodlands to recent extreme droughts during 2000–2019 along broad gradients of climate aridity and forest structure. To this purpose, we apply large-scale remote-sensing using MODIS EVI as a primary production proxy in 5274 Q. ilex sites distributed within a 100,000 km2 region in eastern Spain. These woodlands were extensively affected by two extreme drought events in 2005 and 2012. Resistance, assessed as the capacity of the ecosystems to maintain primary production during drought, was significantly lower for semi-arid than for sub-humid and dry-transition conditions. Holm oak woodlands located in semi-arid areas of the region showed also poorer resilience to drought, characterized by low capacity to fully recover to their pre-drought production levels. Further, drought intensity and both pre- and post-drought hydric conditions controlled the variations of resistance, recovery and resilience between the two analyzed extreme drought events. Drought effects were particularly negative for dense Q. ilex stands under semi-arid climate conditions, where strong competition for scarce water resources reduced drought resistance. The observed drought vulnerability of semi-arid holm oak woodlands may affect the long-term stability of these dry forests. Adaptive management strategies, such as selective forest thinning, may be useful for improving drought responses in these more vulnerable semi-arid woodlands. Conversely, natural rewilding may more appropriately guide management actions for more humid areas, where densely developed Q. ilex woodlands show in general a high ability to maintain ecosystem primary production during drought.

Integrating multiple plant functional traits to predict ecosystem productivity

Quantifying and predicting variation in gross primary productivity (GPP) is important for accurate assessment of the ecosystem carbon budget under global change. Scaling traits to community scales for predicting ecosystem functions (i.e., GPP) remain challenging, while it is promising and well appreciated with the rapid development of trait-based ecology. In this study, we aim to integrate multiple plant traits with the recently developed trait-based productivity (TBP) theory, verify it via Bayesian structural equation modeling (SEM) and complementary independent effect analysis. We further distinguish the relative importance of different traits in explaining the variation in GPP. We apply the TBP theory based on plant community traits to a multi-trait dataset containing more than 13,000 measurements of approximately 2,500 species in Chinese forest and grassland systems. Remarkably, our SEM accurately predicts variation in annual and monthly GPP across China (R2 values of 0.87 and 0.73, respectively). Plant community traits play a key role. This study shows that integrating multiple plant functional traits into the TBP theory strengthens the quantification of ecosystem primary productivity variability and further advances understanding of the trait-productivity relationship. Our findings facilitate integration of the growing plant trait data into future ecological models.

Response of cyanobacterial mats to ambient phosphate fluctuations: phosphorus cycling, polyphosphate accumulation and stoichiometric flexibility

Cyanobacterial mats inhabit a variety of aquatic habitats, including the most extreme environments on Earth. They can thrive in a wide range of phosphorus (P) levels and are thus important players for ecosystem primary production and P cycling at the sediment-water interface. Polyphosphate (polyP), the major microbial P storage molecule, is assigned a critical role in compensating for phosphate fluctuations in planktonic cyanobacteria, but little is known about potentially analogous mechanisms of mat-forming cyanobacteria. To investigate acclimation strategies of cyanobacterial mats to fluctuating phosphate concentrations, laboratory batch experiments were conducted, in which the cosmopolitan mat-forming, marine cyanobacterium Sodalinema stali was exposed to low dissolved P concentrations, followed by a P pulse. Our results show that the cyanobacteria dynamically adjusted cellular P content to ambient phosphate concentrations and that they had accumulated polyP during periods of high phosphate availability, which was subsequently recycled to sustain growth during phosphate scarcity. However, following the depletion of dispensable cellular P sources, including polyP, we observed a reallocation of P contained in DNA into polyP, accompanied by increasing alkaline phosphatase activity. This suggests a change of the metabolic focus from growth towards maintenance and the attempt to acquire organic P, which would be naturally contained in the sediment. P overplus uptake following a simulated P pulse further suggests that Sodalinema-dominated mats exhibit elaborated mechanisms to cope with severe P fluctuations to overcome unfavourable environmental conditions, and potentially modulate critical P fluxes in the aquatic cycle.

Predicting ecosystem productivity based on plant community traits.

With the rapid accumulation of plant trait data, major opportunities have arisen for the integration of these data into predicting ecosystem primary productivity across a range of spatial extents. Traditionally, traits have been used to explain physiological productivity at cell, organ, or plant scales, but scaling up to the ecosystem scale has remained challenging. Here, we show the need to combine measures of community-level traits and environmental factors to predict ecosystem productivity at landscape or biogeographic scales. We show how theory can extend the production ecology equation to enormous potential for integrating traits into ecological models that estimate productivity-related ecosystem functions across ecological scales and to anticipate the response of terrestrial ecosystems to global change.

Decoupling of greenness and gross primary productivity as aridity decreases

Ecosystem primary productivity is a key ecological process influencing many ecosystem services, including carbon storage. Thus, clarifying how primary productivity in terrestrial ecosystems responds to climatic variability can reveal key mechanisms that will drive future changes in the global carbon budget. Satellite products of canopy greenness are widely used as proxies for vegetation productivity to evaluate how ecosystems respond to climate variability. However, to what degree inter-annual variations in productivity are consistent with greenness and how this relationship varies spatially remains unclear. Here we investigated the strength of the coupling between inter-annual variations in leaf area index (LAI, a measure of greenness) and ecosystem gross primary productivity (GPP) derived from eddy covariance towers, i.e., the r2 of the LAI-GPP relationship. Overall, inter-annual GPP and LAI were highly coupled (i.e., high r2) in arid grasslands, but were fully decoupled in mesic evergreen broadleaf forests, indicating that this relationship varies strongly along aridity gradients. A possible mechanism of the spatial variation in the LAI-GPP relationship is that the tradeoff between ecosystem structure (LAI) and physiology (photosynthesis per unit leaf area) becomes stronger in more humid climates. Land models overestimated the r2 of LAI-GPP correlation for most ecosystem types and failed to capture the spatial pattern along aridity gradients. We conclude that relying on greenness products for evaluating inter-annual changes in vegetation productivity may bias assessments, especially in tropical rainforest ecosystems. Our findings may also reconcile observed disparities between responses in greenness and GPP during drought in Amazon forests.

The ecological functions and risks of expansive bivalve-macroalgae polyculture: A case study in Sansha Bay, China

Bivalve-macroalgae polyculture (BMP) is one of the most important aquacultural means and can maintain a nutrient balance and prevent eutrophication in aquaculture waters. Sansha Bay is a typical mariculture bay on the coasts of southeastern China. The quantity of BMP has expanded in recent decades, while the ecological functions and risks of intensive BMP remain unknown. This study compared the food web structure and ecosystem characteristics between 2010 and 2019 using Ecopath and simulated individual and combined effects of BMP on the ecosystem to detect the ecological functions of polyculture using Ecosim. The results showed that with the expansion of aquaculture in Sansha Bay during the last decade (2010–2019), the total biomass (492.82 g/m2/a) and total flow (19,553.75 g/m2/a) of the ecosystem in 2019 were higher, while the contribution of phytoplankton to primary production accounted for only 13.5%. In Sansha Bay, the total transfer efficiencies were lower than in other aquaculture ecosystems, 4.16% and 4.27% in 2010 and 2019, respectively. The maturity declined slightly, and the ecosystem's primary productivity was still redundant in Sansha Bay based on the analysis of ecological characteristics. The biomass of phytoplankton increased more than two times to remove BMP, which indicated the positive control of eutrophication and harmful algae blooms. However, each culture species should be scientifically evaluated to reduce the redundancy of the ecosystem, improve the system's maturity, and make the aquaculture ecosystem more resilient and stable.

A New Classification Tool and a Systematic Review of Macroalgal Studies Disentangle the Complex Interactive Effects of Warming and Nutrient Enrichment on Primary Production

In order to understand how global warming effects on ecosystem primary production may change depending on nutrient enrichment, a new classification is proposed to disentangle and recognize the combination of interactions among several factors, based on the effect direction (positive, negative, or neutral) and its changes induced in it by the other factor (synergizing, antagonizing, inducing no change, or changing it in some other way). Marine macroalgae were chosen (as primary producers for which there is the most experimental information available) to review the relevant studies on which this new classification can be tested. It was observed the positive effects of elevated temperature and nutrient enrichment often synergized each other within the temperature range between relatively low and optimal growth levels. However, the negative effect of further temperature elevation from optimal to higher levels was antagonized by nutrient enrichment in some studies but was synergized in others, depending on the range of temperature elevation. The positive effect of nutrient enrichment was antagonized (but still positive) by temperature increase above the optimum in many cases, although the effect sometimes switched to a negative effect depending on the magnitude of nutrient enrichment. These results predict that global warming will enhance bottom-up effects on primary production in cold seasons and areas, and there will be a negative warming effect on production in hot seasons and areas, but it may be possible to mitigate this effect by appropriate levels of nutrient enrichment.

Effects of Habitat-Specific Primary Production on Fish Size, Biomass, and Production in Northern Oligotrophic Lakes

Ecological theory predicts that the relative distribution of primary production across habitats influence fish size structure and biomass production. In this study, we assessed individual, population, and community-level consequences for brown trout (Salmo trutta) and Arctic char (Salvelinus alpinus) of variation in estimated habitat specific (benthic and pelagic) and total whole lake (GPPwhole) gross primary production in 27 northern oligotrophic lakes. We found that higher contribution of benthic primary production to GPPwhole was associated with higher community biomass and larger maximum and mean sizes of fish. At the population level, species-specific responses differed. Increased benthic primary production (GPPBenthic) correlated to higher population biomass of brown trout regardless of being alone or in sympatry, while Arctic char responded positively to pelagic primary production (GPPPelagic) in sympatric populations. In sympatric lakes, the maximum size of both species was positively related to both GPPBenthic and the benthic contribution to GPPWhole. In allopatric lakes, brown trout mean and maximum size and Arctic char mean size were positively related to the benthic proportion of GPPWhole. Our results highlight the importance of light-controlled benthic primary production for fish biomass production in oligotrophic northern lakes. Our results further suggest that consequences of ontogenetic asymmetry and niche shifts may cause the distribution of primary production across habitats to be more important than the total ecosystem primary production for fish size, population biomass, and production. Awareness of the relationships between light availability and asymmetric resource production favoring large fish and fish production may allow for cost-efficient and more informed management actions in northern oligotrophic lakes.

Environmental hormesis of non-specific and specific adaptive mechanisms in plants

Adaptive responses of plants are important not only for local processes in populations and communities but also for global processes in the biosphere through the primary production of ecosystems. In recent years, the concept of environmental hormesis has been increasingly used to explain the adaptive responses of living organisms, including plants, to low doses of natural factors, both abiotic and biotic, as well as various anthropogenic impacts. However, the issues of whether plant hormesis is similar/different when it is induced by mild stressors having different specific effects and what is the contribution of hormetic stimulation of non-specific and specific adaptive mechanisms in plant resilience to strong stressors (i.e., preconditioning) remains unclear. This paper analyses hormetic stimulation of non-specific and specific adaptive mechanisms in plants and its significance for preconditioning, the phenomenon of the hormetic trade-off for these mechanisms, and the position of hormetic stimulation of non-specific and specific adaptive mechanisms in the system of plant adaptations to environmental challenges. The analysis has shown that both non-specific and specific adaptive mechanisms of plants can be stimulated hormetically by mild stressors and are important for plant preconditioning. Due to limited plant resources, non-specific and specific adaptive mechanisms have hormetic trades-offs 1 (hormesis accompanied by the deterioration of some plant traits) and 2 (hormesis of some plant traits with the invariability of others). At the same time, hormetic trade-off 2 is observed much more often than hormetic trade-off 1, at least, this was demonstrated here for non-specific adaptive responses of plants. The hormetic stimulation of non-specific and specific adaptive mechanisms is part of the inducible adaptation of plants caused by stress factors and is an adaptation to random (unpredictable) changes in the environment.

Decreased precipitation in the late growing season weakens an ecosystem carbon sink in a semi‐arid grassland

AbstractNet ecosystem gas exchange (NEE), a balance between gross ecosystem primary productivity (GPP) and ecosystem respiration (ER), is an important indicator of terrestrial ecosystem CO2sink or source. Increasing frequency in droughts during different periods of the growing season may affect terrestrial ecosystem carbon (C) balance. However, detecting how drought timing controls ecosystem C processes is insufficiently explored because it is a challenge to accurately monitor and forecast drought dynamics.In a 5‐year (2015–2019) precipitation manipulation experiment in a temperate steppe in northern China, we imposed a 60% decrease in precipitation in the early (April–June, DEP) and late (July–September, DLP) growing seasons in plots under rainout shelters to simulate drought occurrence timing. The responses of GPP, ER and NEE to DEP and DLP were examined to determine how the timing of decreased precipitation affects CO2fluxes.Both DEP and DLP reduced GPP and ER. Decreased precipitation in the late growing season reduced NEE due to a greater decline in GPP than ER. In contrast, the lack of an effect of DEP on NEE can be attributed to a proportional decline in GPP and ER. Reduced normalized difference vegetation index (NDVI) and GPP induced by decreased precipitation explained the decline in GPP and ER respectively. Drought in the late growing season weakened the ecosystem C sink. The result indicates a low resistance in net C uptake to DLP. However, we did not find evidence that previous precipitation decreases resulted in a lower overall rate of ecosystem C exchange, indicating a high resilience in C processes in this semi‐arid grassland.Synthesis and applications. Our study provides solid evidence that drought in the late growing season weakens ecosystem C sink in the semi‐arid grassland. The findings suggest that management practices aimed at enhancing water availability during the late growing season should be preferred for increasing C sequestration.

A Regional Earth System Data Lab for Understanding Ecosystem Dynamics: An Example from Tropical South America

Tropical ecosystems experience particularly fast transformations largely as a consequence of land use and climate change. Consequences for ecosystem functioning and services are hard to predict and require analyzing multiple data sets simultaneously. Today, we are equipped with a wide range of spatio-temporal observation-based data streams that monitor the rapid transformations of tropical ecosystems in terms of state variables (e.g., biomass, leaf area, soil moisture) but also in terms of ecosystem processes (e.g., gross primary production, evapotranspiration, runoff). However, the underexplored joint potential of such data streams, combined with deficient access to data and processing, constrain our understanding of ecosystem functioning, despite the importance of tropical ecosystems in the regional-to-global carbon and water cycling. Our objectives are: 1. To facilitate access to regional “Analysis Ready Data Cubes” and enable efficient processing 2. To contribute to the understanding of ecosystem functioning and atmosphere-biosphere interactions. 3. To get a dynamic perspective of environmental conditions for biodiversity. To achieve our objectives, we developed a regional variant of an “Earth System Data Lab” (RegESDL) tailored to address the challenges of northern South America. The study region extensively covers natural ecosystems such as rainforest and savannas, and includes strong topographic gradients (0–6,500 masl). Currently, environmental threats such as deforestation and ecosystem degradation continue to increase. In this contribution, we show the value of the approach for characterizing ecosystem functioning through the efficient implementation of time series and dimensionality reduction analysis at pixel level. Specifically, we present an analysis of seasonality as it is manifested in multiple indicators of ecosystem primary production. We demonstrate that the RegESDL has the ability to underscore contrasting patterns of ecosystem seasonality and therefore has the potential to contribute to the characterization of ecosystem function. These results illustrate the potential of the RegESDL to explore complex land-surface processes and the need for further exploration. The paper concludes with some suggestions for developing future big-data infrastructures and its applications in the tropics.

Winter nitrogen enrichment does not alter the sensitivity of plant communities to precipitation in a semiarid grassland

Nitrogen (N) deposition often promotes aboveground net primary productivity (ANPP), but has adverse effects on terrestrial ecosystem biodiversity. It is unclear, however, whether biomass production and biodiversity are equally altered by seasonal N enrichment, as there is a temporal pattern to atmospheric N deposition. By adding N in autumn, winter, or growing season from October 2014 to May 2019 in a temperate grassland in China, we found that N addition promoted peak plant community ANPP, but tended to decrease plant richness. Regardless of seasonal N additions, precipitation was positively correlated with plant community ANPP, confirming that precipitation is the primary limiting factor in this semiarid grassland. Unexpectedly, N addition in autumn or growing season, but not in winter, increased the sensitivity of plant communities to precipitation (i.e., the slope of the positive relationship between community ANPP and precipitation), indicating that precipitation determines the influence of seasonal N enrichment on plant community biomass production. These findings suggest that previous studies in which N was added in a single season, e.g., the growing season, have likely overestimated the effects of N deposition on ecosystem primary productivity, especially during wet years. This study illustrates that multi-season N addition in agreement with predicted seasonal patterns of N deposition needs to be evaluated to precisely assess ecosystem responses.

Solving the fourth‐corner problem: forecasting ecosystem primary production from spatial multispecies trait‐based models

AbstractForecasting productivity and stress across an ecosystem is complicated by the multiple interactions between competing species, the unknown levels of intra‐ and interspecific trait plasticity, and the dependencies between those traits within individuals. Integrating these features into a trait‐based quantitative framework requires a conceptual and quantitative synthesis of how multiple species and their functional traits interact and respond to changing environments, a challenge known in community ecology as the “fourth‐corner problem.” We propose such a novel synthesis, implemented as an integrated Bayesian hierarchical model. This allows us to (1) simultaneously model trait–trait and trait–environment relationships by explicitly accounting for both intra‐ and interspecific trait variabilities in a single analysis using all available data types, (2) quantify the strength of the trait–environment relationships, (3) identify trade‐offs between multiple traits in multiple species, and (4) faithfully propagate our modeling uncertainties when making species‐specific and community‐wide trait predictions, reducing false confidence in our spatial prediction results. We apply this integrated approach to the world’s largest mangrove forest, the Sundarbans, a sentinel ecosystem impacted simultaneously by both climate change and multiple types of human exploitation. The Sundarbans presents extensive variability in environmental variables, such as salinity and siltation, driven by changing seawater levels from the south and freshwater damming from the north. We find that tree species growing under stress have a typical functional response to the environmental drivers with inter‐specific variability around this average, and the amount of variability is further contingent upon the nature and magnitude of the environmental drivers. Our model captures the retreat in traits related to resource acquisition and a plastic enhancement of traits related to resource conservation, both clear indications of stress. We predict that, if historical increases in salinity and siltation are maintained, one‐third of whole‐ecosystem productivity will be lost by 2050. Our integrated modeling approach bridges community and ecosystem ecology through simultaneously modeling trait–environment correlations and trait–trait trade‐offs at organismal, community, and ecosystem levels; provides a generalizable foundation for powerful modeling of trait‐environment linkages under changing environments to predict their consequences on ecosystem functioning and services; and is readily applicable across the Earth’s ecosystems.

Effects of Climate, Plant Height, and Evolutionary Age on Geographical Patterns of Fruit Type.

Fruit type is a key reproductive trait associated with plant evolution and adaptation. However, large-scale geographical patterns in fruit type composition and the mechanisms driving these patterns remain to be established. Contemporary environment, plant functional traits and evolutionary age may all influence fruit type composition, while their relative importance remains unclear. Here, using data on fruit types, plant height and distributions of 28,222 (∼ 90.1%) angiosperm species in China, we analyzed the geographical patterns in the proportion of fleshy-fruited species for all angiosperms, trees, shrubs, and herbaceous species separately, and compared the relative effects of contemporary climate, ecosystem primary productivity, plant height, and evolutionary age on these patterns. We found that the proportion of fleshy-fruited species per grid cell for all species and different growth forms all showed significant latitudinal patterns, being the highest in southeastern China. Mean plant height per grid cell and actual evapotranspiration (AET) representing ecosystem primary productivity were the strongest drivers of geographical variations in the proportion of fleshy-fruited species, but their relative importance varied between growth forms. From herbaceous species to shrubs and trees, the relative effects of mean plant height decreased. Mean genus age had significant yet consistently weaker effects on proportion of fleshy-fruited species than mean plant height and AET, and environmental temperature and precipitation contributed to those of only trees and shrubs. These results suggest that biotic and environmental factors and evolutionary age of floras jointly shape the pattern in proportion of fleshy-fruited species, and improve our understanding of the mechanisms underlying geographical variations in fruit type composition. Our study also demonstrates the need of integrating multiple biotic and abiotic factors to fully understand the drivers of large-scale patterns of plant reproductive traits.