Faced with the dual pressures of global climate change and the intensification of human activity, sophisticated social–ecological systems (SES) are generating unprecedented challenges for sustainable development. Nevertheless, current research primarily emphasizes the dynamic variations of ecosystem services (ESs), with a specific focus on the dynamics of their supply, demand and flow, but with insufficient exploration of the complex mutual feedback mechanism between ecosystems and social systems. Network approaches have significant potential in the research of ESs, but their practical applications still require further exploration. This study selected the Shiyang River Basin (SRB) as a representative case and employs ESs as a bridging framework by introducing partial correlation networks, aiming to analyse how ESs are intricately linked with social–ecological factors (SEF). Results indicated that from 2010 to 2020, within the SRB, ESs demonstrated distinct spatial heterogeneity. Through network analysis, this study reveals the complex interrelationships between SEF and ESs in the SRB, identifying critical nodes and connecting pathways in the network. Among them, the importance and influence of precipitation in the network have gradually become prominent, with its node strength increasing from 0.92 in 2010 to 1.20 in 2020, becoming a key element driving the evolution of the network structure. Population density consistently served as a pivotal social factor throughout the study period, exacerbating the demand for multiple ESs. The persistent influence of human activities poses potential risks to SES. Additionally, the least absolute shrinkage and selection operator method eliminates over 50% of false connections, significantly enhancing the reliability of results. Furthermore, the study emphasizes that achieving sustainable development requires not only enhanced management of key elements but also greater attention to the relationships between SEF and multiple ESs, thereby establishing a systematic governance framework. This study not only provides a fresh angle to understand the complex interplay between ESs and SEF but also offers scientific foundations and practical guidance for ecological management in arid inland river basins.
In desert basins where phreatophyte species are common, the contribution of groundwater evapotranspiration (ETg) and vadose zone ET (ETsoil) to total ET remains an important uncertainty. Here, ETg and ETsoil, and proportional contributions of each to total ET, were estimated for a phreatophyte (shrub)-dominated desert ecosystem in California, USA. ETg and ETsoil were estimated from a water balance approach using daily ET, daily precipitation and monthly vadose zone soil water storage (SWS) data collected across five sites and over 2 years. Precipitation was ~ 40% below average during the first year (2022) and ~ 110% above average during the second year (2023). Isotopic sampling of shrubs, soil and groundwater was also used to determine spatial and temporal changes in shrub water sources. We found that ETg/ET averaged 0.28 over the full 2-year period. On average, ETg/ET was higher in the dry year (0.36) than the wet year (0.22). Winter precipitation and summer rain events strongly influenced SWS and estimated ETg and ETsoil. Isotopic analysis indicated that shrubs used mostly vadose zone water (~ 50% to > 90%) when SWS was high or increasing, which were periods of peak shrub growth and high ET. Shrubs used mostly groundwater (40% to > 90%) when SWS was low or decreasing, which occurred during periods of limited growth and low ET. Our results highlight the importance of accounting for changes in SWS in estimates of ETg and ETsoil and demonstrate the influence of temporal changes in shrub water sources on vadose zone water and groundwater contributions to ET.
As climate change increasingly threatens the northern peatland net carbon sequestration function, there is a pressing need to better understand the limits of ecohydrological regulatory mechanisms. This is especially urgent for shallow peatlands (< 40-cm average peat depth), which consistently experience water stress with greater intensity, frequency and duration than deep peatlands and may represent sentinels for climate change. In this ‘part 2’ paper, we review the peatland hydrological feedbacks originally proposed a decade prior in Hydrological Feedbacks in Northern Peatlands ‘part 1’ (Waddington et al. 2015) to investigate the strength of feedback mechanisms as a function of peat depth. We show that in some hydrogeomorphic and hydroclimatic settings there are differences in hydrophysical properties and vegetation cover between shallow and deep peatlands. These structural characteristics influence the strength of the fast (i.e., function on a timescale of seconds to days) hydrological feedbacks (moss surface resistance and albedo, transmissivity, peat deformation and specific yield). In contrast, the slow feedbacks (i.e., operating on the scale of months to decades) related to vegetation community change and peat decomposition directly impact peatland physical characteristics (patterns and composition of vegetation, bulk density, etc.). We discuss how the vulnerability of shallow peatlands arises from the interactions between regulatory (negative) and destabilizing (positive) ecohydrological feedbacks.
Non-perennial streams are globally prevalent. These streams are vital components of ecosystems, yet their drying patterns and resulting impacts on hydrologic connectivity remain poorly understood at the watershed scale. Aridity is a dominant driver of stream drying, but its influences on hydrologic connectivity have not been fully explored. In this study, we investigated the role of aridity in shaping streamflow and connectivity patterns in non-perennial stream networks that span the continental United States aridity gradient. Using hydrologic models, we simulated daily streamflow and stream network connectivity under current and future climate scenarios. Our findings support previous research showing that aridity and streamflow are strongly linked. We also found that connectivity was related to aridity, although this relationship was weaker. Under the future climate scenario, mean runoff increased in most watersheds in the future, while mean connectivity decreased in the majority of watersheds. This difference is an indicator of the complex relationship between streamflow and connectivity. Aridity was a strong predictor of changes in very high and very low connectivity periods that resulted from climate change, but aridity did not predict changes in mean connectivity. Arid watersheds tended to experience more high connectivity days due to climate change while humid networks tended to have more low connectivity days. By modelling climate impacts at the network scale and across a broad hydroclimatic gradient, we highlight the importance of considering context-dependent changes in network connectivity in river flow management and watershed conservation plans.
Extreme climatic events can cause a high degree of impacts on forest carbon dynamics, particularly in more sensitive subtropical regions. We investigated the dynamics of carbon exchange, light use efficiency (LUE) and water use efficiency (WUE) in a subtropical forest ecosystem representing Central China's Yangtze River basin. The region is located at the East Asian monsoonal zone largely characterized by hot and humid summers and cold and dry winters. Using eddy-covariance measurements, we find that the climatically sensitive subtropical forest ecosystem acts as a robust carbon sink, sequestering carbon at an annual rate of 8.26 t C ha−1, exceeding the average C sink of broadleaf forests. Despite favourable hydrothermal conditions in summer, excessive solar radiation and vapour pressure deficit (VPD) suppress carbon sink potential, highlighting the sensitivity of carbon exchange to extreme climatic events. The LUE of the subtropical forest exhibits a nonlinear relationship with leaf area index (LAI) as high as 2.6 m2 m−2, while water use efficiency (WUE) variability is strongly driven by VPD, reflecting the combined effects of environmental factors including temperature, precipitation and biological factors. In comparison, carbon exchange in the subtropical forest in YRB is highly sensitive to climate change, while LUE remains the most stable. The critical balance of water and thermal conditions for optimal carbon uptake of subtropical forests in YRB provides insights into the climatic extremities, as revealed by strong interactions among carbon exchange, LUE and WUE, highlighting the potentially important role in carbon offsets in the region.
Understanding the influence of vegetation on nitrogen transport is crucial for assessing the ‘nitrogen status’ of watersheds and advancing sustainable ecosystem management, particularly in vulnerable permafrost-affected regions. Daily riverine nitrogen data during the ice-free period (from 9 April to 26 October) in 2021 of a boreal forest watershed of the permafrost region in northeast China were investigated. Results showed that the nitrogen wet deposition during the growing season significantly exceeded the riverine nitrogen export. The vegetation (including trees, shrubs, herbs and mosses) significantly influenced the riverine nitrogen export during this period. The modified double mass curve and Pettitt's test were used to quantitatively assess the impact of vegetation on riverine nitrogen export. Runoff variations could explain 51.35% of the riverine nitrogen export in the non-growing season. However, vegetation attenuated the impact of runoff on riverine nitrogen export, thus ensuring a relatively stable relationship between runoff and riverine nitrogen export in the growing season. When daily runoff was below 1.40 mm (the daily runoff threshold at which riverine nitrogen export underwent a significant change), vegetation reduced nitrogen export by 31.89%. Above this threshold, the reduction increased to 60.51%. These results provide new mechanistic insights into the seasonal nitrogen dynamics of permafrost watersheds under climate change.
The surface of peatlands is constantly in motion. While pristine mires are characterized by peat growth and reversible surface fluctuation, induced by water level fluctuations, drained peatlands show subsidence due to peat mineralization and physical compaction. Still, drained peatlands show smaller but marked short-term surface fluctuation as the water level continues fluctuating after drainage. This concurrence of physical and biochemical processes complicates the determination of greenhouse gas emissions from subsidence measurements. Restored peatlands may regain surface motion dynamics of pristine sites. Besides informing on carbon exchange, surface motion data might serve as an indicator for ecohydrological conditions. This review study compiles the key processes causing surface motion, methods to determine surface motion and subsidence models. A global meta-analysis of 670 data points on subsidence (121 studies) and 70 data points on surface oscillation (29 studies) revealed large variability, with subsidence rates from −3.2 to 37.5 cm yr−1 and annual peak-to-peak amplitudes from 0.1 to 20 cm. Subsidence was influenced by time since drainage, climate, drainage depth, peat thickness and land use intensity. The subsidence rate decreased with time, while the share of physical compaction decreased, and the share of mineralization increased. With increasing temperature, mineralization and hence subsidence rate increased. Increasing drainage depth and thus land use intensity positively influence both mineralization and physical compaction. Subsidence rate and the share of physical compaction increased with increasing peat thickness. By combining existing model approaches, using the most available variables, we introduce four models to estimate subsidence rates on a global scale.
Disassociating the independent effects of flow and water quality on the ecology of flowing waters is an overarching goal in water resource science needed to improve the efficacy of watershed management. However, the interrelatedness of these gradients and their subsequent alteration due to land use change has constrained progress made on this front. The objective of this study was to use benthic macroinvertebrate and fish assemblage data to characterize flow-ecology relationships that were unchanged by water quality impacts across two southeastern landscapes in the USA to help detect ecological change driven by flow alteration. General linear latent models were used to identify taxa that were responsive to high or low flow metrics and water quality gradients. Bayesian hierarchical generalized additive models were then developed using these indicator taxa and three biological metrics to identify flow-specific relationships that were unaffected by water quality impacts. Three low flow-specific relationships were identified, illustrating how potential agricultural or urban impacts to hydrology reduced stream biological health. Importantly, flow-ecology relationships developed using indicator taxa in this study effectively captured hydrology-specific impacts while biological metrics typical of state monitoring and assessment programs did not. Therefore, developing flow-specific biological metrics is a critical step when developing management strategies targeting flow alteration. Implementing standardized frameworks such as the one characterized here can limit contradictory findings and improve streamflow enhancement and restoration project efficacy. These low flow-specific relationships will enhance managers' capacity to develop environmental flow standards, monitor their success, and better understand urban and agricultural impacts on stream assemblages.
Beaver dams substantially reshape peatland hydrology, yet their influence on plant phenology, a key driver of ecosystem carbon dynamics, remains poorly understood. We used UAV-based RGB imagery to quantify seasonal changes in greenness (GCC) of sedge (Carex spp.) across three hydrological treatments in a Canadian Rocky Mountain peatland: flooded beaver pond, drained beaver pond and unimpacted fen. Repeat imagery captured from May to September 2023 revealed that beaver damming, whether current or legacy, significantly altered sedge phenology. Phenology in the flooded beaver pond followed a similar trajectory as the unimpacted fen but delayed green-up by 2.5 weeks. Interestingly, the drained beaver pond exhibited the earliest green-up, beginning 12 days earlier and reached a 12% higher peak greenness while having a similar length of season as the unimpacted fen, likely due to warmer peat and later-season water stress. The flooded beaver pond maintained a high, stable water table which delayed senescence and extended the growing season by 6 weeks. These hydrological legacies created a patchwork of phenological responses across the peatland. Our findings highlight how beaver engineering via manipulation of water table elevation controls plant phenology, with potential indirect downstream effects on carbon cycling and forage availability in montane peatlands.
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