Ecosystem Scale Research Articles

The Ecosystem Ecology of Coral Reefs Revisited

Early studies in coral reefs showed that simple measurements of ecosystem metabolism (primary production and ecosystem respiration) were useful for understanding complex reef dynamics at an ecosystem scale. These studies also helped establish the field of ecosystem ecology, but contemporary coral reef ecology has shifted away from these origins. In this manuscript, I describe the historical development of a theory of ecosystem metabolism that was foundational for the discipline of ecosystem ecology, and I update this theory to fully incorporate dynamics on coral reefs (and all ecosystems). I use this updated theory to (a) identify important controls on coral reef processes and (b) provide a rationale for patterns of coral reef carbon dynamics that allow me to generate hypotheses of coral reef ecosystem production. I then use existing data to broadly evaluate these hypotheses. My findings emphasize the importance of integrating measurements of ecosystem metabolism with current approaches to improve the development of theory and the efficacy of conservation and management of coral reefs.

Divergent mechanisms driving nutrient stoichiometry in surface and deep soils of desert ecosystems on the Qinghai–Tibetan plateau

The ecological stoichiometric properties of desert soils determine nutrient availability and contribute to biodiversity and ecosystem stability. We obtained 1784 soil samples from 330 soil profiles distributed across the desert area of the Qinghai–Tibet Plateau (QTP). We measured the content of soil organic carbon (SOC), total nitrogen (TN), total phosphorus (TP), total potassium (TK), alkali-hydrolyzed nitrogen (AN), available phosphorus (AP), and available potassium (AK) to elucidate the vertical patterns of soil stoichiometric characteristics and their driving factors. We found a unique vertical distribution of SOC and soil nutrients in the QTP desert ecosystem: the proportions of SOC and nutrient storage in the topsoil (0–20 cm) were the highest that have been reported to date, especially for the proportion of SOC, which reached 54 %. The vertical distributions of SOC and AN fit an exponential function (r = 0.247 and 0.249), TN fit a linear function (r = 0.115), and TP, AP, and AK fit a curvilinear function (r = 0.127, 0.175, and 0.103), indicating that soil components exhibited a depth-dependent distribution in the alpine desert ecosystem. With increasing soil depth, C:N and C:P decreased significantly, AN:AP first increased and then decreased, and AP:AK first decreased and then increased. The factors that influenced soil nutrients and stoichiometry differed between the topsoil (0–20 cm) and deep soil (20–100 cm) layers. In the topsoil (0–20 cm), vegetation and precipitation were the dominant factors for soil nutrients and stoichiometry, while topography and climate affected soil nutrients and stoichiometry indirectly by influencing vegetation growth. In the deep soil (20–100 cm), silt particles and precipitation were the dominant factors for soil nutrients and stoichiometry, but climate affected soil nutrients and stoichiometry indirectly, mainly by influencing soil texture. The inconsistencies of nutrient stoichiometric driving mechanisms in surface and deep soils contributed to a comprehensive understanding of soil stoichiometric properties at the profile scale of desert ecosystems.

Global patterns in vegetation accessible subsurface water storage emerge from spatially varying importance of individual drivers

Abstract Vegetation roots play an essential role in regulating the hydrological cycle by removing water from the subsurface and releasing it to the atmosphere. However, the present understanding of the drivers of ecosystem-scale root development and their spatial variability globally is limited. This study investigates the varying roles of climate, landscape, and vegetation on the magnitude of root zone storage capacity ( S r ) worldwide, which is defined as the maximum volume of subsurface moisture accessible to vegetation roots. To this aim, we quantified S r and evaluated 21 possible climate, landscape, and vegetation controls for 3612 river catchments worldwide using a random forest machine learning model. Our findings reveal climate as primary, but spatially varying, driver of ecosystem scale S r with landscape and vegetation characteristics playing a minor role. More specifically, we found the mean inter-storm duration as most dominant control of S r globally, followed by mean temperature, mean precipitation, and mean topographic slope. While the inter-storm duration, temperature, and slope exhibit a consistent relation with S r globally, the relation between precipitation and S r varies spatially. Based on this spatial variability, we classified two different regimes: precipitation driven and energy limited. The precipitation-driven regime exhibits a positive relation between precipitation and S r for precipitation of up to 3 mm d − 1 , above which the relation flattens and eventually becomes negative. The energy-limited regime exhibits a strictly negative relation between precipitation and S r . Using the random forest model based on these three dominant climate variables and the landscape variable slope, we generated a global gridded dataset of S r , which closely resembles other global datasets of root characteristics. This suggests that our parsimonious approach based on four globally available variables to estimate S r on a global scale has the potential to be readily and easily integrated into the parameterization of S r in global hydrological and land surface models. This may enhance the accuracy of global predictions of land–atmosphere exchange fluxes and hydrological extremes by providing a robust representation of both spatial and temporal variability in vegetation root characteristics.

Widespread forest-savanna coexistence but limited bistability at a landscape scale in Central Africa

Abstract Tropical forest and savanna frequently coexist under the same climatic conditions, which has led to the hypothesis that they could represent alternative ecosystem states, stabilized by internal feedbacks. An implication of this hypothesis is that forest and savanna may be bistable and exhibit tipping behavior in response to changing conditions. However, we pose that the local presence of forest and savanna within coexistence landscapes is not sufficient evidence that these are alternative stable states at larger ecosystem scales. Therefore, we explore forest-savanna coexistence and bistability at landscape scale in Central Africa. Using remote sensing data on tree cover, we classify 0.1° x 0.1° (approx. 10 x 10 km) landscapes as homogeneous forest, homogeneous savanna, or coexistence, and analyze the roles of climate, topography and soil sand content in driving their distributions. We find that local coexistence of forest and savanna within landscapes is common and occurs for the whole range of mean annual precipitation in our study area. At low precipitation, however, coexistence increases with topographic roughness and is therefore likely driven by local redistribution of resources rather than internal feedbacks. Coexistence within intermediate and high precipitation landscapes remains unexplained by the studied variables, and may be caused either by heterogeneity in unmeasured drivers or by feedback-driven bistability. At landscape scale, the precipitation ranges for which homogeneous forest and savanna occur have only limited overlap, and this overlap can be largely explained by other external drivers, such as seasonality, soil sand content, and topography. This lack of evidence that homogeneous forest and savanna in Central Africa are alternative ecosystem states at this landscape scale means that transitions between them may be mostly local, resulting in coexistence states. Therefore, we conclude that the likelihood of large-scale tipping between homogeneous forest and savanna ecosystems may be lower than previously thought.

Water quality–fisheries tradeoffs in a changing climate underscore the need for adaptive ecosystem–based management

Changes driven by both unanticipated human activities and management actions are creating wicked management landscapes in freshwater and marine ecosystems that require new approaches to support decision-making. By linking a predictive model of nutrient- and temperature-driven bottom hypoxia with observed commercial fishery harvest data from Lake Erie (United States-Canada) over the past century (1928-2022) and climate projections (2030-2099), we show how simple, yet robust models and routine monitoring data can be used to identify tradeoffs associated with nutrient management and guide decision-making in even the largest of aquatic ecosystems now and in the future. Our approach enabled us to assess planned nutrient load reduction targets designed to mitigate nutrient-driven hypoxia and show why they appear overly restrictive based on current fishery needs, indicating tradeoffs between water quality and fisheries management goals. At the same time, our temperature results show that projected climate change impacts on hypoxic extent will require more stringent nutrient regulations in the future. Beyond providing a rare example of bottom hypoxia driving changes in fishery harvests at an ecosystem scale, our study illustrates the need for adaptive ecosystem-based management, which can be informed by simple predictive models that can be readily applied over long time periods, account for tradeoffs across multiple management sectors (e.g., water quality, fisheries), and address ecosystem nonstationarity (e.g., climate change impacts on management targets). Such approaches will be critical for maintaining valued ecosystem services in the many aquatic systems worldwide that are vulnerable to multiple drivers of environmental change.

Global influence of soil texture on ecosystem water limitation.

Low soil moisture and high vapour pressure deficit (VPD) cause plant water stress and lead to a variety of drought responses, including a reduction in transpiration and photosynthesis1,2. When soils dry below critical soil moisture thresholds, ecosystems transition from energy to water limitation as stomata close to alleviate water stress3,4. However, the mechanisms behind these thresholds remain poorly defined at the ecosystem scale. Here, by analysing observations of critical soil moisture thresholds globally, we show the prominent role of soil texture in modulating the onset of ecosystem water limitation through the soil hydraulic conductivity curve, whose steepness increases with sand fraction. This clarifies how ecosystem sensitivity to VPD versus soil moisture is shaped by soil texture, with ecosystems in sandy soils being relatively more sensitive to soil drying, whereas ecosystems in clayey soils are relatively more sensitive to VPD. For the same reason, plants in sandy soils have limited potential to adjust to water limitations, which has an impact on how climate change affects terrestrial ecosystems. In summary, although vegetation-atmosphere exchanges are driven by atmospheric conditions and mediated by plant adjustments, their fate is ultimately dependent on the soil.

Domesticating the wild through escapees of two iconic mediterranean farmed fish species

Extractive fisheries and marine aquaculture share space and target species. Several regional-scale examples exist of escapees entering wild fisheries landings, yet no study has assessed the influence of aquaculture on landings at an ecosystem scale. We examined the effects of farmed fish escapes on fisheries using FAO data and published escape rates for Gilthead seabream (Sparus aurata) and European seabass (Dicentrarchus labrax). Seabream landings were significantly correlated with the estimated biomass of escaped seabream entering the wild. There was a similar pattern for seabass until 2005, but the overall relationship between landings and escapes was not significant due to the dramatic drop in catches in recent years. We argue that seabass escapees’ relatively high mortality, lower capturability, and minor ‘leaking’ from farms may obscure their influence on landings. Significant positive fisheries regime shifts were detected for both species, matching the onset of aquaculture in the Mediterranean and the period when escapees from aquaculture surpassed landings. Our results suggest that fish escapes of these two iconic species may mask wild stock overexploitation, confound stock assessments, alter genetic diversity, increase the risk of spreading pathogens and parasites, and compete with wild conspecifics while boosting fisheries landings.

Long-term alien marsh grass in China brings high carbon uptake capacity but cannot sustain high-temperature weather

Coastal wetlands, crucial in the global carbon cycle, face increasing challenges brought by extreme climate events, particularly high temperatures above plant tolerance thresholds. These conditions often exert great impact on plant, thereby potentially reducing overall ecosystem productivity. However, it has been observed that alien species, typically exhibiting higher productivity compared to native plant. Would plant invasion offset the loss of productivity caused by high-temperature events at ecosystem scale? In this study, we utilized data from 2020 to 2023 in China's Yangtze Estuary to investigate the responses of Spartina alterniflora (alien) and Phragmites australis (native) to high-temperature stress. Our results demonstrate that though the alien vegetation exhibits higher productivity before high temperature events, it experiences significant declines during high temperatures. In average, net ecosystem productivity (NEP) and gross primary productivity (GPP) of alien plant drops by 21.03% overall, with a notable 29.59% reduction during Neap tide. In contrast, native vegetation maintains a more stable productivity profile under the same conditions. Spring tide alleviate the negative impact of high temperatures on the alien vegetation, exhibiting a distinct environmental buffering effect. Photosynthetic photon flux density emerged as a crucial factor driving productivity, yet its effectiveness was moderated by aerodynamic conductance for heat transfer (Ga_h). Through the application of the Michaelis-Menten model, we confirmed that both species maintain similar maximum light utilization efficiencies, yet native vegetation demonstrates greater resilience to thermal stress. Additionally, we observed a 33.82% overestimation in productivity by the vegetation photosynthesis model (VPM) under high temperatures, emphasizing the need to refine how Ga_h impacts are integrated, particularly when comparing the resilience of native and alien species. We emphasize necessity of incorporating canopy structure factors into ecological models and underscore the importance of maintaining tidal dynamics for coastal wetland management.

Evaluating variation of respiration:photosynthesis ratio in sagebrush species: Implications for carbon flux modeling

AbstractPlant respiration and photosynthesis are the two main processes influencing carbon (C) flux balance at leaf‐to‐ecosystem scales. The ratio of respiration to photosynthesis (R:A) or carbon use efficiency (CUE) is considered an important trait for determining global carbon storage in the near future. One school of thought assumes that R:A is constant in terrestrial productivity models, irrespective of biomass, climate, and species. Others believe it is variable, although within a limited range. Semiarid systems dominated by woody vegetation, such as sagebrush steppe, have been recognized as potentially important C sinks on regional to global scales in the context of future climate scenarios. Therefore, there is a critical need to study R:A over different organizational scales (i.e., at the leaf, whole plant, and ecosystem scales) to use this approach for future C flux predictions under climate change scenarios. The objective of this study was to compare leaf‐, shrub‐, and ecosystem‐scale R:A among three sagebrush (Artemisia spp.) communities, and to determine how R:A varies throughout the growing season (i.e., early, mid‐, and late summer) among these communities. We measured photosynthesis and respiration monthly in three sagebrush communities spanning a 685‐m elevation gradient at the Reynolds Creek Experimental Watershed and Critical Zone Observatory in southwestern Idaho. Consistent with our expectations, we found large seasonal variations in R and A at all scales, but with differences in A among the three sagebrush communities significant only at the leaf scale. The R:A ratio was not significantly different among the three species at all organizational scales. However, the R:A ratio did vary among months at the leaf level and there was a statistical interaction between species and month at both leaf and shrub levels. Our study indicates that the R:A ratio is generally conservative, although not tightly constrained (range: 0.12–0.77) among three sagebrush species. Therefore, approaches that assume conservative R:A ratios in terrestrial productivity models need to be considered carefully to evaluate the impact of projected climatic changes on future C cycling in shrub‐dominated rangeland ecosystems.

Reduced ligninase‐cellulase ratio enhances soil carbon sequestration following afforestation of agricultural land

AbstractIntroductionAfforestation of agricultural land is one of the most essential approaches to mitigate climate change by enhancing the sequestration of atmospheric carbon (C) into the soil. C‐degrading extracellular enzymes produced by soil microbes regulated the decomposition and fate of sequestrated soil organic carbon (SOC), with potential divergent variations following afforestation across different ecosystem scales. However, the feedbacks of different C‐degrading enzymes and their relationships with SOC following afforestation of agricultural land remain unclear.Materials and MethodsWe investigated the changes in enzyme activity and their relationships with SOC in soil aggregates across two typical climatic vegetation restoration regions in China, and explored the mechanisms through which changes in enzyme activity contribute to SOC sequestration following afforestation of agricultural land.ResultsAfforestation of agricultural land generally decreased ligninase activity and increased cellulase activity across various aggregate fractions, compared to the adjacent croplands in both subtropic (Danjiangkou Reservoir, DJK) and temperate (Maoershan, MES) region. Additionally, the ratio of ligninase to cellulase (L:C) was lower in afforested lands than in the croplands, with L:C as the major factor explaining the variations of SOC sequestration following afforestation. Specifically, ligninase and L:C were negatively correlated with SOC, whereas cellulase showed positive correlations with SOC. Further analyses suggested that microbial biomass C and nitrogen (MBC and MBN) and the ratio of SOC and total nitrogen (SOC:TN) were important factors influencing L:C and subsequently regulating SOC. These results suggest that shifts in microbial enzyme production from ligninase to cellulase following afforestation, reduced the decomposition of recalcitrant C, thus contributing to SOC sequestration.ConclusionOur work underscores the critical role of reduced L:C in enhancing SOC sequestration following the restoration of croplands to afforested lands. These findings advance the understanding of the influence of microbial community physiological adaptations on C sequestration across different land use types.

Self-organization in spatial ecology

Biologists have long known that populations of organisms - microbes, plants, animals - can self-organize into emergent patterns. Yet, the fact that such patterns can arise with remarkable symmetry at the scale of entire ecosystems remains astonishing, even as aerial imagery has documented their existence across all continents. As the enormous scale of landscape patterns makes them experimentally intractable, ecologists have relied on theoretical modelling - typically rooted in physics - to investigate the underlying pattern-forming mechanisms. Such models have succeeded in generating mechanistic hypotheses and indicate that self-organized spatial patterns can reflect the health of an ecosystem. However, most of these hypotheses remain untested. This essay reflects on our current understanding of the causes and consequences of ecosystem-scale pattern formation.

Heat tolerance varies considerably within a reef-building coral species on the Great Barrier Reef

Reef-building coral populations face unprecedented threats from climate warming. Standing variation in heat tolerance is crucial for evolutionary processes necessary for corals to persist. Yet, the spatial distribution of heat-tolerant corals and the underlying factors that determine heat tolerance are poorly understood from individual to ecosystem scales. Here, we show extensive variation in the heat tolerance of a foundational coral species complex across the Great Barrier Reef. Thermal thresholds of 569 individuals differed by up to 7.3 °C across scales from meters to >1250 km. Variation in thresholds among reefs was consistent with local adaptation and acclimatization to historical and recent thermal history. However, variation within reefs was sometimes greater than among reefs and largely unexplained by environmental predictors, putative host species, or symbiont communities. This indicates that within-reef heat tolerance differences may be informed primarily by other factors, such as adaptive genomic variation. We anticipate our findings will inform conservation and restoration actions, including targeting individuals for selective breeding of enhanced heat tolerance.

Measuring quantity in ecosystem markets and ecosystem accounts

AbstractThe quantity of ecosystem services produced from land cannot be readily measured at the site level needed for participation in ecosystem markets, or at a regional level needed to create ecosystem accounts. This paper applies biological scaling principles to develop a quantity metric in which areas of ecosystem (extent) scale allometrically to ecosystem services (a capacity measure) according to a scaling exponent defined by the fractal dimension of ecosystem vegetation. A key conclusion of this paper is that the quantity of ecosystem services arising from ecosystem degradation and conservation activities cannot be estimated unless information about the space‐filling properties of vegetation is observed and included in the quantity measurement methodology. The paper demonstrates how remote sensing techniques can be applied to systematically measure ecosystem extent and fractal dimension. It illustrates the economic efficiency and environmental outcome implications of such a quantity metric through comparison with current quantity estimation methods that assume isometric scaling. The quantity metric proposed has potential applications to ecosystem accounting. It enables information currently reported in land accounts to be combined with information reported in ecosystem condition accounts to create ecosystem stock accounts measured in physical units.

Whole-lake coarse woody habitat addition facilitates ecosystem regime restructuring in an oligotrophic lake

Preul-Stimetz T, Shaw SL, Sass GG. 2024. Whole-lake coarse woody habitat addition facilitates ecosystem regime restructuring in an oligotrophic lake. Lake Reserv Manag. XXX-XXX. The loss of vital littoral zone and riparian habitat due to lakeshore residential development is a pervasive issue across temperate aquatic ecosystems. Oligotrophic glacial lakes may be particularly vulnerable to reductions in coarse woody habitat (CWH) due to their lack of alternative structural habitat. Although influences of CWH on fish populations have been well documented, questions remain regarding CWH influences on lower trophic levels and water quality. We conducted a whole-lake CWH addition experiment within a BACI framework using 2 lakes, Sanford (treatment) and Escanaba (reference), in the Northern Highland Lake District of Wisconsin. Premanipulation monitoring began in 2015, trees were dropped in 2018, and data collection continued until 2023. We monitored limnological, planktonic, and benthic macroinvertebrate parameters to test whether CWH addition initiated trophic shifts and altered the structure of the aquatic food web. We found that CWH addition minimally affected water quality and changed some characteristics of Sanford Lake at lower trophic levels. Chlorophyll a concentrations in Sanford Lake significantly increased but Secchi depth was unaffected. The abundance of macrophytes increased in both systems; that in Sanford Lake increased more and was linked to the CWH addition. Dissolved oxygen significantly increased at multiple depth strata. Water temperature was unaffected. We observed declines in total zooplankton that were not related to CWH addition, but the decline in relative abundance of large grazers was. Our results provide a mechanistic understanding of the effects of habitat enhancement at an ecosystem scale and can help guide stakeholder and manager expectations following CWH addition.

An enhanced chlorophyll estimation model with a canopy structural trait in maize crops: Use of multi-spectral UAV images and machine learning algorithm

Leaf chlorophyll concentration (LCC) is a key indicator of leaf nitrogen (N) and changes in canopy structure, particularly the leaf area index (LAI), play a significant role in estimating LCC. Spectral prediction models for chlorophyll are a useful tool for timely nutritional management, particularly in precision agriculture. However, the accuracy of LCC estimation is influenced by the LAI. Considering LAI data as input in the spectral prediction model is still inadequate for improving LCC estimation. This study tested the hypothesis that LCC estimate accuracy could be enhanced by using LAI as an input using high-resolution (5 cm) multi-spectral images from an unmanned aerial vehicle (UAV). For this, maize was grown as a test crop under different nutrient management in the hilly ecosystem of Meghalaya. LCC was measured using laboratory destruction methods from ground sampling that coincided with UAV flights. Machine learning algorithms such as random forest (RF), support vector machine (SVM), and kernel ridge regression (KKR) were employed to develop the LCC estimation model, utilizing band reflectance, vegetation indexes, and measured chlorophyll. The model was assessed for its sensitivity to LCC estimation using LAI data. KKR outperformed other two algorithms (RF and SVM) in accuracy of LCC estimation by >11.0 to 19.0 %. The KKR-derived LCC estimation model was significantly improved by the inclusion of LAI (R2 increased from 0.785 to 0.928 and RMSE decreased from 0.065 to 0.053 mg g−1). The model's reliability was proven on multiple UAV flights for maize crops that are healthy and nutrient-stressed. Thus, LCC models derived from multispectral UAV images using KKR algorithms could benefit the adoption of precision agriculture at field scale in mountain ecosystems.

Enhancing Burned Area Mapping Accuracy: Integrating Multi-temporal PCA with NDVI Analysis

Forested lands in the west coast of Turkey, with their similarity to Mediterranean forests, are often found to be highly susceptible to wildfires, necessitating the development of a forest management program to refine and quantify forest fires and their impacts on the environment. In light of this fact, a multi-temporal approach combining Principal Component Analysis (PCA) and Normalized Difference Vegetation Index (NDVI) analysis derived from Sentinel-2 imagery is suggested in the current study. Through PCA of carefully selected bands of Sentinel-2, both recent and historic fire impacts are attempted to be captured. It was found that the first two principal components (PC1 and PC2) predominantly describe landscape characteristics, while the third and fourth components (PC3 and PC4) have high abilities in detecting burn scars. It is worth noting that an increase in the ability to detect burn scars was observed with the inclusion of NDVI and its difference in time (dNDVI) within the PCA process. A high effectiveness level in distinguishing burnt areas from unburnt landscapes was presented by the multi-temporal PCA approach, particularly with dNDVI integration. PC2 and PC3, especially with dNDVI integration, are found to be strong indicative factors of burnt areas. In the classification result, accuracies of different years of fire events differed, and a high accuracy of 98.76% was found in the last fire event year of 2019. However, slight underestimation and overestimation were also observed in older fire scars. Mean accuracy, on average, for the PCA-dNDVI method was found to be higher than that of the MLC method. Furthermore, significant vegetation losses by fire, particularly by the 2019 fire incident, were realized through NDVI assessment. Although it worked well in recent fire scars, overestimating the extent in the case of burned areas from previous years was observed. The potential of multi-temporal PCA integration with NDVI for analysis in mapping burned areas at different scales in fire-prone ecosystems in western Turkey is underlined by the results of this work. Much more successful forest management and assessment strategies after fires have occurred in these ecosystems are helped to be created by this approach. Moreover, the approach is suggested to be one of the strong tools for monitoring fire induced damages across many time scales toward better understanding and management of long-term impacts caused by forest fires in the region.

Scale‐sensitive marine law and policy design: Towards ecosystem‐based management across spatial and temporal scales

AbstractEcosystem‐based management (EBM) is promoted in scholarly literature and international policy as a way to improve marine ecosystem outcomes, through the integration of marine law and policies across sectors, communities, and scales. A legal and policy framework that supports EBM at appropriate temporal and spatial scales is fundamental to the successful deployment of EBM. However, marine management is typically fragmented and misaligned, with a range of laws, policies, governance institutions, and sectoral frameworks applying to different marine spaces and working on varying timescales. In this focus article, we draw on our comprehensive study of Aotearoa New Zealand's marine law and policy to analyze the challenges scale mismatches present for marine law and policy implementation, focusing on key policy areas across fisheries, environment, conservation, and Indigenous rights and interests. We identify key opportunities to better align marine law and policy to ecosystem scale dynamics, revealing critical lessons for the imperative of scale‐sensitive marine law and policy design, globally.This article is categorized under: Policy and Economics > Research and Development Policy and Economics > Governance and Regulation Climate and Environment > Ecosystem Services

Tropospheric ozone pollution increases the sensitivity of plant production to vapor pressure deficit across diverse ecosystems in the Northern Hemisphere

Tropospheric ozone (O3) pollution often accompanies droughts and heatwaves, which could collectively reduce plant productivity. Previous research suggested that O3 pollution can alter plant responses to drought by interfering with stomatal closure while drought can reduce stomatal conductance and provide protection against O3 stress. However, the interactions between O3 pollution and drought stress remain poorly understood at ecosystem scales with diverse plant functional types. To address this research gap, we used 10-year (2012−2021) satellite near-infrared reflectance of vegetation (NIRv) observations, reanalysis data of vapor pressure deficit (VPD), soil moisture (SM), and air temperature (Ta), along with O3 measurements and reanalysis data across the Northern Hemisphere to statistically disentangle the interconnections between NIRv, VPD, SM, and Ta under varying O3 levels. We found that high O3 concentrations significantly exacerbate the sensitivity of NIRv to VPD while have no notable impacts on the sensitivity of NIRv to Ta or SM for all plant functional types, indicating an enhanced combined impact of VPD and O3 on plants. Specifically, the sensitivity of NIRv to VPD increased by >75 % when O3 anomalies increased from the lowest 10 to the highest 10 percentiles across diverse plant functional types. This is likely because long-term exposure to high O3 concentrations can inhibit stomatal closure and photosynthetic enzyme activities, resulting in reduced water use efficiency and photosynthetic efficiency. This study highlights the need to consider O3 in understanding plant responses to climate factors and that O3 can alter plant responses to VPD independently of Ta and SM.

Multi-scale beta-diversity patterns in testate amoeba communities: species turnover and nestedness along a latitudinal gradient.

The relationship between species diversity and spatial scale is a central topic in spatial community ecology. Latitudinal gradient is among the core mechanisms driving biodiversity distribution on most scales. Patterns of β-diversity along latitudinal gradient have been well studied for aboveground terrestrial and marine communities, whereas soil organisms remain poorly investigated in this regard. The West Siberian Plain is a good model to address diversity scale-dependence since the latitudinal gradient does not overlap with other possible factors such as elevational or maritime. Here, we collected 111 samples following hierarchical sampling (sub-zones, ecosystem types, microhabitat and replicate samples) and performed multi-scale partitioning of β-diversity of testate amoeba assemblages as a model of study. We found that among-ecosystem β-diversity is a leading scale in testate amoeba assemblages variation. Rare species determine β-diversity at all scale levels especially in the northern regions, where rare taxa almost exclusively accounted for the diversity at the ecosystem level. β-Diversity is generally dominated by the turnover component at all scales in lower latitudes, whereas nestedness prevailed at among-ecosystem scale in higher latitudes. These findings indicate that microbial assemblages in northern latitudes are spatially homogeneous and constrained by historical drivers at larger scales, whereas in southern regions, it is dominated by the turnover component both at the microhabitat and ecosystem scales and therefore determined by recent vegetation and environmental heterogeneity. Overall, we have provided the evidence for the existence of negative latitudinal gradient for among-ecosystem β-diversity but not for among-microhabitat and among-sample β-diversity for terrestrial testate amoeba communities.

Vegetative stage and soil horizon respectively determine direction and magnitude of rhizosphere priming effects in contrasting tree line soils

Abstract Tree lines in high latitudes and high altitudes are considered sentinels of global change. This manifests in accelerated encroachment of trees and shrubs and enhanced plant productivity, with currently unknown implications for the carbon balance of these biomes. Given the large soil organic carbon stocks in many tree line soils, we here wondered whether introducing highly productive plants would accelerate carbon cycling through rhizosphere priming effects and if certain soils would be more vulnerable to carbon loss from positive priming than others. To test this, organic and mineral soils were sampled above and below tree lines in the Swedish sub‐arctic and the Peruvian Andes. A greenhouse experiment was then performed to quantify plant‐induced changes in soil mineralisation rates (rhizosphere priming effect) and new C formation using natural abundance labelling and the C4‐species Cynodon dactylon. Several environmental, plant, soil and microbial parameter were monitored during the experiment to complement the observations on soil C cycling. Priming was predominantly positive at the beginning of the experiment, then systematically decreased in all soils during the plant growth season to be mostly negative at the end of the experiment at plant senescence. Independent of direction of priming, the magnitude of priming was always greater in organic than in corresponding mineral soils, which was best explained by the higher C contents of these soils. Integrated over the entire study period, the overall impact of priming (positive and negative) on the soil C balance was mostly negligible. Though net soil C loss was observed in organic soils from the sub‐arctic tundra in Sweden. Most notably, positive and negative priming effects were not mutually exclusive, rather omnipresent across ecosystems, depending on sampling time. The direction of priming seems to be fluctuating with plant productivity, rhizosphere carbon inputs and nutrient uptake. This highlights the need for integrative long‐term studies if we aim to understand priming effects at ecosystem scale and greenhouse and laboratory studies must be validated in situ to enable reliable ecological upscaling. Read the free Plain Language Summary for this article on the Journal blog.