Ecosystem Scale Research Articles

Response of stomatal conductance, transpiration, and photosynthesis to light and CO2 for rice leaves with different appearance days.

To investigate the dynamics of stomata, transpiration, and photosynthesis under varying light intensities and CO2 conditions during leaf development, the light response and CO2 response of stomatal conductance (g sw), transpiration rate (T r), and net photosynthetic rate (P n) were observed for rice leaves at different days after leaf emergence (DAE). The results showed that (1) as photosynthetically active radiation (PAR) increased, leaf g sw, T r, and P n initially increased rapidly and linearly, followed by a more gradual rise to maximum values, and then either stabilized or showed a declining trend. The maximum g sw, T r, and P n were smaller and occurred earlier for old leaves than for young leaves. The g sw, T r, and P n all exhibited a linear decreasing trend with increasing DAE, and the rate of decrease slowed down with the reduction in PAR; (2) as the CO2 concentration (C a) increased, g sw and T r decreased gradually to a stable minimum value, while P n increased linearly and slowly up to the maximum and then kept stable or decreased. The g sw, T r, and P n values initially kept high and then decreased with the increase of DAE. These results contribute to understanding the dynamics in g sw, T r, and P n during rice leaf growth and their response to varied light and CO2 concentration conditions and provide mechanistic support to estimate dynamic evapotranspiration and net ecosystem productivity at field-scale and a larger scale in paddy field ecosystems through the upscaling of leaf-level stomatal conductance, transpiration, and photosynthesis.

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.

No positive effects of biodiversity on ecological resilience of lake ecosystems

<p>Ecological resilience is critical for ecosystems to persist in the face of perturbations without shifting to a different state. Global biodiversity loss in multiple ecosystems is considered to be associated with decreasing ecological resilience and increasing the risk of ecosystem collapse. However, how temporal changes in biodiversity affect ecological resilience in natural ecosystems remains poorly elucidated. By analyzing subfossil records of diatoms, chironomids, and cladocerans from 53 lake sediment cores across the globe, we found that species richness showed an increasing trend with time, while beta diversity and ecological resilience presented a decreasing temporal trend when ecosystems are approaching the abrupt shift. Asynchronous fluctuations among species and temporal stability at species level are suggested to be the mechanisms that contribute to the maintenance of temporal community stability. We found species richness and beta diversity have positive effects on species asynchrony but negative effects on species stability. However, we found that species asynchrony and species stability had negative relationships with ecological resilience, with species richness and beta diversity overall having no positive effects on ecological resilience. We highlighted that biodiversity effects on ecological resilience are not only the role of species richness, but also the species assemblage and network complexity of species-species interactions. Our study indicates that increased species diversity and community heterogeneity may be not beneficial for the ecosystem to recover from disturbances at a lake ecosystem scale, which has great implications for the assessment of ecological resilience and predicting ecosystem collapse in future global environmental change scenarios.</p>

Working together to scale ecosystem restoration: collective approaches to community action in Aotearoa New Zealand

Working together to scale ecosystem restoration: collective approaches to community action in Aotearoa New Zealand

Net Methane Production Predicted by Patch Characteristics in a Freshwater Wetland

AbstractMethane (CH4) dynamics in wetlands are spatially variable and difficult to estimate at ecosystem scales. Patches with different plant functional types (PFT) represent discrete units within wetlands that may help characterize patterns in CH4 variability. We investigate dissolved porewater CH4 concentrations, a representation of net CH4 production and potential source of atmospheric flux, in five wetland patches characterized by a dominant PFT or lack of plants. Using soil, porewater, and plant variables we hypothesized to influence CH4, we used three modeling approaches—Classification and regression tree, AIC model selection, and Structural Equation Modeling—to identify direct and indirect influences on porewater CH4 dynamics. Across all three models, dissolved porewater CO2 concentration was the dominant driver of CH4 concentrations, partly through the influence of PFT patches. Plants in each patch type likely had variable influence on CH4 via root exudates (a substrate for methanogens), capacity to transport gas (both O2 from and CH4 to the atmosphere), and plant litter quality which impacted soil respiration and production of CO2 in the porewater. We attribute the importance of CO2 to the dominant methanogenic pathway we identified, which uses CO2 as a terminal electron acceptor. We propose a mechanistic relationship between PFT patches and porewater CH4 dynamics which, when combined with sources of CH4 loss including methanotrophy, oxidation, or plant‐mediated transport, can provide patch‐scale estimates of CH4 flux. Combining these estimates with the distribution of PFTs can improve ecosystem CH4 flux estimates in heterogenous wetlands and improve global CH4 budgets.

Understanding temporal variability across trophic levels and spatial scales in freshwater ecosystems.

A tenet of ecology is that temporal variability in ecological structure and processes tends to decrease with increasing spatial scales (from locales to regions) and levels of biological organization (from populations to communities). However, patterns in temporal variability across trophic levels and the mechanisms that produce them remain poorly understood. Here we analyzed the abundance time series of spatially structured communities (i.e., metacommunities) spanning basal resources to top predators from 355 freshwater sites across three continents. Specifically, we used a hierarchical partitioning method to disentangle the propagation of temporal variability in abundance across spatial scales and trophic levels. We then used structural equation modeling to determine if the strength and direction of relationships between temporal variability, synchrony, biodiversity, and environmental and spatial settings depended on trophic level and spatial scale. We found that temporal variability in abundance decreased from producers to tertiary consumers but did so mainly at the local scale. Species population synchrony within sites increased with trophic level, whereas synchrony among communities decreased. At the local scale, temporal variability in precipitation and species diversity were associated with population variability (linear partial coefficient, β = 0.23) and population synchrony (β = -0.39) similarly across trophic levels, respectively. At the regional scale, community synchrony was not related to climatic or spatial predictors, but the strength of relationships between metacommunity variability and community synchrony decreased systematically from top predators (β = 0.73) to secondary consumers (β = 0.54), to primary consumers (β = 0.30) to producers (β = 0). Our results suggest that mobile predators may often stabilize metacommunities by buffering variability that originates at the base of food webs. This finding illustrates that the trophic structure of metacommunities, which integrates variation in organismal body size and its correlates, should be considered when investigating ecological stability in natural systems. More broadly, our work advances the notion that temporal stability is an emergent property of ecosystems that may be threatened in complex ways by biodiversity loss and habitat fragmentation.

Impacts of site aridity on intra-annual radial variation of two alpine coniferous species in cold and dry ecosystems

Climate change alters regional aridity and species composition in dryland ecosystems. However, the effect of varying aridity and species-specific responses on tree growth remains unclear. Here, we used high-resolution dendrometers to analyze the climatic factors controlling stem diameter variation in two alpine coniferous species, Qilian juniper (Juniperus przewalskii) and Qinghai spruce (Picea crassifolia), in their eastern- and western-most distributions (two species × two sites) in the Qilian Mountains during the 2018–2021 growing seasons. We observed species-, site-, and year-specific differences in growth phenology and radial growth dynamics. Juniper had early growth onset and cessation, but short growing season compared to spruce. Trees in the eastern sites showed earlier growth onset, later cessation, and a much longer growing season than those in the western sites for both species. Daily stem growth revealed similar responses for both species and site aridity, with daily vapor pressure deficit, maximum temperature, and solar radiation negatively, and relative humidity and precipitation positively affecting stem increments. However, when observation was extended to 7 or 21 days, the effect of precipitation on stem increments became weak or negligible in the wetter eastern sites, while continuing in the arid western sites. Further, soil water content appeared to have an impact on growth in the arid western site for both species. These results were confirmed by linear mixed-effects models, which revealed that site-aridity play an important role on tree stem variation, especially in junipers. Our results suggest that although short-term atmospheric water conditions influence radial stem variation, intra-annual tree growth still depends on soil water availability in drylands. Our findings provide new evidence of potential uses of dendrometers to measure environmental stress on tree growth and reveal that site aridity and species influence tree growth at different time scales in cold and arid ecosystems.

Evaluating data-driven and hybrid modeling of terrestrial actual evapotranspiration based on an automatic machine learning approach

The performances of physics-based, data-driven, and hybrid models for estimating terrestrial actual evapotranspiration (ETa) is currently under debate, which requires thorough evaluations of those models particularly with recent developments in automatic machine learning (AML) techniques. In this study, six AML-based models were first constructed using the H2O-AML platform, from which an optimal (AML-OP) model was selected for estimating daily ETa at ecosystem scales. In addition, hybrid models were developed by combining the six AML models with surface conductance (Gs) inverted from the Penman-Monteith equation and an optimal (PM-OP) model was also selected. With 15 predictor variables as model inputs that were compiled from various data sources, the performances of those models for estimating daily ETa were evaluated using observed data from the FLUXNET2015 dataset. The results revealed that no models showed consistently low noise levels across different ecosystem types, making it necessary to use AML techniques for selecting ecosystem-specific models. Interestingly, the AML-OP models (root mean square error (RMSE) and symmetric mean absolute percentage error (SMAPE) were 0.16–0.31 mm d-1 and 9 %–36 % respectively) showed slightly better predictive results than the PM-OP models (RMSE and SMAPE were 0.23–0.36 mm d-1 and 15 %–68 % respectively), likely owing to model parameter uncertainties and tight constraints of physical models on application condition. Secondly, as ETa nonlinearly responds to environmental variables, model predictability under extreme weather (drought and heatwave) conditions was examined. The results showed that the prediction of the AML-OP and PM-OP models expectedly worsened (RMSE and SMAPE increased by 0.06–0.77 mm d-1 and −19 % to 79 %, respectively); however, the AML-OP model still outperformed the PM-OP model in most ecosystems, further underscoring the need to understand ETa regulation mechanisms under varying climatic conditions. Finally, the PM-OP models developed here provided better daily ETa estimates compared to other recently proposed hybrid models (RMSE reduced by 0.98–1.80 mm d-1). Both models can be better applied to wetlands that have been less frequently evaluated previously (RMSE reduction of 0.22 mm d-1 and 0.18 mm d-1 for the AML-OP and PM-OP models).

Spatial patterns of light response parameters and their regulation on gross primary productivity in China

Light response parameters are used to model the photosynthetic processes of ecosystems, but they are usually considered as fixed or empirical values for specific vegetation type and their geographical variation and influence mechanisms at ecosystem scale remain unclear. In this study, we analyzed the light response parameters (photosynthetic quantum yields, α; maximum gross photosynthetic rate, Amax) at 64 typical ecosystems of ChinaFLUX over 20 years’ measurement, to explore their spatial patterns and controlling factors. The results showed that the light response parameters significantly varied with ecosystem types: in grassland and desert ecosystems, both α and Amax were significantly lower than other ecosystems, and in cropland ecosystems, the Amax was significantly higher than that of other ecosystems. The light response parameters significantly decreased with increasing altitude. Vegetation index and photosynthetically active radiation were the dominant factor for the spatial variation of α, while the spatial variation of Amax was mainly controlled by moisture conditions. Compared to Amax, α was more stable which varied less with hydrothermal conditions. The dominant factors of light response parameters also differed among ecosystem types. Hydrothermal conditions regulated vegetation indexes and further modulate light response parameters and GPP. This study suggested that the quantitative analysis and simulation prediction of photosynthesis should consider the spatial heterogeneity of light response parameters and their different environmental responses at ecosystem scale in future studies.

A cockle-induced bioturbation model and its impact on sediment erodibility: A meta-analysis

Modelling the dynamics of an estuary and the evolution of its morphology requires a process-based description not only of the physical processes, but also of the influence of benthic fauna on sediment characteristics at ecosystem scale. A meta-analysis was tested as an approach for modelling the effect of bioturbation exerted by the cockle Cerastoderma edule on sediment erodibility. Six different erosion flume datasets were collected to ensure a broad range of experimental conditions including bed shear stress, population characteristics, and sediment composition. First, a model was built to describe the biogenic fluff layer created by C. edule activity in relation to (i) bioturbation activity using the population metabolic rate [mW·m−2] as a proxy for faunal metabolic energy, and (ii) the silt content [%] of the sediment. Second, different erosion models were compared by testing parameterization steps incorporating both erosion of the fluff layer and/or mass erosion of the sediment bed. Structural differences in the flumes and in the preparation of samples in the six different datasets makes it difficult to propose a single model that satisfactorily simulates all the data and encompasses both types of subsequent erosion, that of the fluff layer and that of the underlying consolidated bed. However, a generic model is proposed for the surficial fluff layer erosion covering a moderate range of bed shear stress (<1 Pa). This study shows that including several datasets covering a wide range of environmental conditions is a key to the robustness of this model, and that new insights can be gained by integrating the complexity of sediment features. We expect that this two-part model can be used in broad contexts in terms of cockle populations, estuarine habitats, and climatic conditions and can combined with various hydro-morpho-sedimentary models that include these biological effects.

МОДЕЛИ ПОДДЕРЖКИ ИННОВАЦИОННЫХ ТЕХНОЛОГИЧЕСКИХ ПРОЕКТОВ В УСЛОВИЯХ ФОРМИРОВАНИЯ ПРЕДПОСЫЛОК ДЛЯ ПЕРЕХОДА К ТЕХНОЭКОНОМИКЕ НА ПРИМЕРЕ ПРОЕКТОВ ПОЛИМЕРНОГО КЛАСТЕРА СПБ

In the new economic condition, non-standard approaches to the development of mechanisms that contribute to the implementation of tasks to strengthen the competitiveness of the enterprise are required. Innovation is becoming one of the main tools to achieve this goal. But innovation is not easy to introduce in the industrial segment of SMEs. And, first of all, for this it is necessary to assess existing own and partner resources, state support measures, the scale of the innovative ecosystem of the region. As a rule, everything we need for growth now has already been created, accessible and requires only dynamic integration and digital modernization for modern purposes.

Emerging sensing, imaging, and computational technologies to scale nano-to macroscale rhizosphere dynamics – Review and research perspectives

The soil region influenced by plant roots, i.e., the rhizosphere, is one of the most complex biological habitats on Earth and significantly impacts global carbon flow and transformation. Understanding the structure and function of the rhizosphere is critically important for maintaining sustainable plant ecosystem services, designing engineered ecosystems for long-term soil carbon storage, and mitigating the effects of climate change. However, studying the biological and ecological processes and interactions in the rhizosphere requires advanced integrated technologies capable of decoding such a complex system at different scales. Here, we review how emerging approaches in sensing, imaging, and computational modeling can advance our understanding of the complex rhizosphere system. Particularly, we provide our perspectives and discuss future directions in developing in situ rhizosphere sensing technologies that could potentially correlate local-scale interactions to ecosystem scale impacts. We first review integrated multimodal imaging techniques for tracking inorganic elements and organic carbon flow at nano-to microscale in the rhizosphere, followed by a discussion on the use of synthetic soil and plant habitats that bridge laboratory-to-field studies on the rhizosphere processes. We then describe applications of genetically encoded biosensors in monitoring nutrient and chemical exchanges in the rhizosphere, and the novel nanotechnology-mediated delivery approaches for introducing biosensors into the root tissues. Next, we review the recent progress and express our vision on field-deployable sensing technologies such as planar optodes for quantifying the distribution of chemical and analyte gradients in the rhizosphere under field conditions. Moreover, we provide perspectives on the challenges of linking complex rhizosphere interactions to ecosystem sensing for detecting biological traits across scales, which arguably requires using the best-available model predictions including the model-experiment and image-based modeling approaches. Experimental platforms relevant to field conditions like SMART (Sensors at Mesoscales with Advanced Remote Telemetry) soils testbed, coupled with ecosystem sensing and predictive models, can be effective tools to explore coupled ecosystem behavior and responses to environmental perturbations. Finally, we envision that with the advent of novel high-resolution imaging capabilities spanning from nano-to macroscale, and remote biosensing technologies, combined with advanced computational models, future studies will lead to detection and upscaling of rhizosphere processes toward ecosystem and global predictions.

Existing evidence on the effects of photovoltaic panels on biodiversity: a systematic map with critical appraisal of study validity

BackgroundTo phase out fossil fuels and reach a carbon–neutral future, solar energy and notably photovoltaic (PV) installations are being rapidly scaled up. Unlike other types of renewable energies such as wind and hydroelectricity, evidence on the effects of PV installations on biodiversity has been building up only fairly recently and suggests that they may directly impact ecosystems and species through, for instance, habitat change and loss, mortality, behaviour alteration or population displacements. Hence, we conducted a systematic map of existing evidence aiming at answering the following question: what evidence exists regarding the effects of PV installations on wild terrestrial and semi-aquatic species?MethodsWe searched for relevant citations on four online publication databases, on Google Scholar, on four specialised websites and through a call for grey literature. Citations were then screened for eligibility in order to only retain citations referring to wild terrestrial and semi-aquatic species as well as PV and solar thermal installations, therefore excluding concentrated solar power. Accepted articles were first split into studies (corresponding to one experimental design) subjected to critical appraisal and then further split into observations (i.e. one population and one outcome) during metadata extraction. The current state of the literature was characterised and knowledge clusters and gaps identified.Review findingsSearching captured 8121 unique citations, which resulted in 158 relevant articles being accepted after screening. Even though the first article was published in 2005, the publication rate increased rapidly in 2020. The 97 included primary research and modelling articles were split into 137 unique studies and rated with either a low (43.8%), a high (41.6%) or an unclear overall risk of bias (14.6%) after internal validity assessment. Studies were further split into 434 observations, mainly carried out in the United States (23.0%) and the United Kingdom (21.0%), preferentially in temperate climates (64.5%). Plants and arthropods were the two most studied taxa (41.7% and 26.3%, respectively). Utility-scale solar energy (USSE) facilities were most often investigated (70.1%). Observations mainly focused on the effect of the presence of PV installations (51.8%). Species abundance, community composition and species diversity were the most common outcomes assessed (23.0%, 18.4% and 16.1%, respectively).ConclusionsThree knowledge clusters for which a systematic review should be contemplated were identified: (i) the effects of PV installations on plant and (ii) arthropod communities and, (iii) their effects at a larger ecosystem scale on overall species abundance. However, the currently available evidence regarding the effects of photovoltaic installations on biodiversity is still scarce. More research is urgently needed on non-flying mammals and bats as well as amphibians and reptiles. Solar thermal panels and floating PV installations should also be further investigated. Studies comparing different designs of PV installations, management practices or contexts should be conducted as well. Indeed, more evidence is still needed to allow decision-makers to accurately and reliably select the types of PV installations and management practices that are least damaging to biodiversity.

Altered Trends in Light Use Efficiency of Grassland Ecosystem in Northern China

Light use efficiency (LUE) is a crucial indicator used to reflect the ability of terrestrial ecosystems to transform light energy. Understanding the long-term trends in LUE and its influencing factors are essential for determining the future carbon sink and carbon sequestration potential of terrestrial ecosystems. However, the long-term interannual variability of LUE in grasslands in northern China at the ecosystem scale is poorly understood due to the limitations of the year length and the coverage of the site data. In this study, we assessed the long-term LUE trends in the grasslands of northern China from 1982 to 2018 and then revealed the relationships between interannual variability in LUE and climate factors. Our study showed a substantial rising trend for LUE from 1982 to 2018 in the grasslands of northern China (3.42 × 10−3 g C/MJ/yr). Regarding the different grassland types, alpine meadow had the highest growth rate (4.85 × 10−3 g C/MJ/yr), while temperate steppe had the lowest growth rate (1.58 × 10−3 g C/MJ/yr). The climate factors driving LUE dynamics were spatially heterogeneous in grasslands. Increasing precipitation accelerated the interannual growth rate of LUE in temperate steppe, and increasing temperature accelerated the interannual growth rate of LUE in other types. In addition, the temporal dynamic of LUE showed different trends in relation to time scales, and the growth trend slowed down after 1998. Our results should be considered in developing future grassland management measures and predicting carbon cycle–climate interactions.

Consistently heterogeneous structures observed at multiple spatial scales across fire-intact reference sites

Yellow pine and mixed-conifer (YPMC) forests of California’s Sierra Nevada have experienced widespread fire suppression for over a century, resulting in ingrowth and densification of trees, heavy fuel accumulation, and shifts in species composition. Under warmer and drier climates, these forests are primed for stand-replacing fires and severe drought mortality, requiring management interventions to improve their resilience and mitigate future impacts. Observations from functioning frequent-fire systems (e.g., contemporary reference sites) can provide key insights about pattern-process relationships in fire-intact systems, which can be used to inform regional management efforts. In this study, we used airborne lidar data to quantify and compare forest structure at multiple spatial scales between contemporary reference sites (i.e., forests with a restored frequent, low-intensity fire regime) and control sites (i.e., typical fire-suppressed forests). We evaluated structures at the neighborhood- (∼1 ha), site- (∼100–1,000 ha), and among-site- (∼10,000–100,000 ha) levels. In reference sites, high proportions of individual trees, small clumps of 2–4 trees, and open space formed mostly open canopy structures at the neighborhood-level, and patches of these neighborhood-level structures were arranged in heterogeneous spatial patterns within sites. We observed low variability in site-level structures among reference sites, indicating a stabilizing effect of frequent, low-intensity fire across broad, ecosystem scales. In fire-suppressed control sites, edaphic factors and other non-fire disturbances occasionally produced heterogeneity at the neighborhood- and site-level, but the degree of heterogeneity was not consistent across sites. Structural patterns in contemporary reference sites suggest improved resilience to future disturbances and climate change, and increased provisioning of ecosystem services relative to control sites. We suggest applying these metrics to help inform multi-scale and multi-resource management in Sierra Nevada forests.

REGIONAL ECOSYSTEM OF USED COOKING OIL (UCO) MANAGEMENT IN CENTRAL JAVA PROVINCE

Indonesia is listed as the world's most used cooking oil (UCO) producing country. Biodiesel from UCO blends is claimed to have lower carbon emissions. A regional scale of sustainable UCO collection and processing ecosystem needs to be established to enhance the role of local authorities in the circular economy. Central Java has the potential for ecosystem planning for UCO management with a circular economy approach. Central Java Province has a total UCO potential of 36,217 kilo liters and can be used for biodiesel potential of 27,094 kilo liters per year. If it is assumed that the processing cost is IDR 9,000.00/liter. The biodiesel production cost for a year is IDR 243.86 trillion/year. Total revenue assumption of IDR 298.04 trillion/year (base price IDR 11,000.00/liter). The profit gain is IDR 54 trillion/year or IDR 4.5 billion/month. The B/C ratio of biodiesel processing is 0.22 and is considered profitable. This program is called Turn Oil On (TOOn). Keywords: Used cooking oil, Biodiesel, Circular economy, Central Java

Factors of global change affecting plants act at different levels of the ecological hierarchy.

Plants and ecosystems worldwide are exposed to a wide range of chemical, physical, and biological factors of global change, many of which act concurrently. As bringing order to the array of factors is required in order to generate an enhanced understanding of simultaneous impacts, classification schemes have been developed. One such classification scheme is dedicated to capturing the different targets of global change factors along the ecological hierarchy. We build on this pioneering work, and refine the conceptual framework in several ways, focusing on plants and terrestrial systems: (i) we more strictly define the target level of the hierarchy, such that every factor typically has just one target level, and not many; (ii) we include effects above the level of the community, that is, there are effects also at the ecosystem scale that cannot be reduced to any level below this; (iii) we introduce the level of the landscape to capture certain land use change effects while abandoning the level below the individual. We discuss how effects can propagate along the levels of the ecological hierarchy, upwards and downwards, presenting opportunities for explaining non-additivity of effects of multiple factors. We hope that this updated conceptual framework will help inform the next generation of plant-focused global change experiments, specifically aimed at non-additivity of effects at the confluence of many factors.

Unlocking Natural Capital in the Megadiverse Colombian Pacific Basin: Navigating Challenges and Governance Gaps

The Pacific region is considered a biodiversity hotspot and presents high species endemic levels. The Colombian Pacific basin occupies an area of approximately eight million hectares, located in the country’s west. The literature about the economic valuation of ecosystem services (ES) and the spatial information on natural resources in the Colombian Pacific basin was revised through various information sources to document the earliest approximation to the state, spatial distribution, and economic value of the natural capital at the scale of biomes, specific ecosystems, and political-administrative units. Our assessment estimated a natural capital loss of 40 billion Int.$2020/year (15% of Colombian GDP in 2020) and a remnant natural capital worth 139 billion Int.$2020/year (51% of Colombia’s GDP in 2020) for 15 ecosystem services. This research establishes that a potential expansion in livestock production systems will generate an additional loss of natural capital between six and eight billion Int.$2020/year. Additionally, we include an analysis based on the GLOBIO4 initiative models, identifying future natural capital losses between 7.5 and 7.6 billion Int.$2020/year. Lastly, the policy challenges and gaps in research and management concerning this remaining natural capital in the Colombian Pacific basin are pointed out.

Relationships of stomatal morphology to the environment across plant communities

The relationship between stomatal traits and environmental drivers across plant communities has important implications for ecosystem carbon and water fluxes, but it has remained unclear. Here, we measure the stomatal morphology of 4492 species-site combinations in 340 vegetation plots across China and calculate their community-weighted values for mean, variance, skewness, and kurtosis. We demonstrate a trade-off between stomatal density and size at the community level. The community-weighted mean and variance of stomatal density are mainly associated with precipitation, while that of stomatal size is mainly associated with temperature, and the skewness and kurtosis of stomatal traits are less related to climatic and soil variables. Beyond mean climate variables, stomatal trait moments also vary with climatic seasonality and extreme conditions. Our findings extend the knowledge of stomatal trait–environment relationships to the ecosystem scale, with applications in predicting future water and carbon cycles.

Spatio-temporal patterns and control mechanism of the ecosystem carbon use efficiency across the Mongolian Plateau

Carbon use efficiency (CUE) is a crucial parameter that reflects the carbon storage within ecosystems, providing insight into the potential for carbon sequestration at the ecosystem scale and its feedback on climate change. The Mongolian Plateau exemplifies an arid and semi-arid region with a delicate ecological environment that displays heightened sensitivity to global climate change. Understanding the variation and control of CUE is critical for assessing regional carbon. However, few studies have focused on the interaction of factors influencing CUE; furthermore, how CUE responds to climate change and anthropogenic activities remains unclear. Here, we aimed to investigate spatiotemporal patterns and their control mechanisms by generating CUE data based on multi-source remote sensing data. CUE demonstrated a slow downward trend from 2000 to 2018, with higher values in relatively dry–cool regions and lower values in relatively humid–warm regions. Furthermore, CUE values were ranked by biome as follows: grassland > sandy vegetation > cropland > shrubs > forest, driven by climate characteristics, vegetation coverage, water stress, stand age, and management practices. Additionally, climatic factors affected CUE more than the soil variables, except for alpine meadows. The climate factors of precipitation (PPT), index of water availability (IWA) (QPPT = 0.487, QIWA = 0.444), and soil factors, e.g., pH and soil organic content (SOC) (QPH = 0.397, QSOC = 0.372), had the greatest influence on CUE. Finally, most two explanatory factors interacted to effectively enhance the explanation of CUE; the synergy of the IWA and PPT contributed the most to CUE (QIWA∩PPT = 0.604). Moreover, the joint effect of climate change and anthropogenic activities was identified as the major contributor (68 %) to the decline in CUE within this region. This study presents compelling evidence highlighting the importance of considering climate change and anthropogenic disturbances in ecosystem management and conservation efforts in arid and semi-arid regions.