Warming enabled upslope advance in western US forest fires.

Increases in burned area and large fire occurrence are widely documented over the western United States over the past half century. Here, we focus on the elevational distribution of forest fires in mountainous ecoregions of the western United States and show the largest increase rates in burned area above 2,500 m during 1984 to 2017. Furthermore, we show that high-elevation fires advanced upslope with a median cumulative change of 252 m (-107 to 656 m; 95% CI) in 34 y across studied ecoregions. We also document a strong interannual relationship between high-elevation fires and warm season vapor pressure deficit (VPD). The upslope advance of fires is consistent with observed warming reflected by a median upslope drift of VPD isolines of 295 m (59 to 704 m; 95% CI) during 1984 to 2017. These findings allow us to estimate that recent climate trends reduced the high-elevation flammability barrier and enabled fires in an additional 11% of western forests. Limited influences of fire management practices and longer fire-return intervals in these montane mesic systems suggest these changes are largely a byproduct of climate warming. Further weakening in the high-elevation flammability barrier with continued warming has the potential to transform montane fire regimes with numerous implications for ecosystems and watersheds.

A real-time hourly water index for flood risk monitoring: Pilot studies in Brisbane, Australia, and Dobong Observatory, South Korea.

A water resources index based on weight-accumulated precipitation over the passage of time in heavy rainfall events is used in this study for monitoring flood risk and peak danger, as well as to develop flood warnings. In this research, an hourly water resources index (WRIhr) based on rainfall accumulations over the passage of time is proposed. WRIhr is able to monitor flood risk by taking into account the hourly effective precipitation that accumulates the precipitation (Phr) of both current and antecedent hours, while the contributions from the preceding hours is subjected to a time-dependent reduction function that addresses the depletion of water volume by various hydrological processes (e.g., discharge, runoff, evapotranspiration). By converting rainfall into a water resources index (WRI), the hourly precipitation over a 24-h period is redistributed to formulate a long-term water resources index (WRIhr-L) that monitors flood status based on long-term (more than 1 year) fluctuations in Phr and a short-term water resources index (WRID-hr-S) that considers shorter (D = 24-148 hourly) accumulations of the Phr data. WRI was assessed for its potential in flood monitoring at two hydrologically diverse sites: Dobong (South Korea; August 1998) and Brisbane (Australia; December 2010-January 2011), and its applicability was verified using river water level (H) measurements at hydrological stations. The power spectrum density and spectral coherence of hourly rainfall, river water level, and the corresponding WRI showed good agreements, as did the low and high frequency wavelet components using the discrete wavelet transform algorithm. Importantly, WRI24-hr-S computed over 24 hourly accumulation periods was able to mimic the risk of short-term (flash-style) floods caused by concentrated rainfall, whereas WRIhr-L was more useful for flood risk assessment caused by an event over a long-term period. Dynamical changes in H were closely in-phase with the patterns of change noted in the WRIhr over the respective temporal scale. We conclude that the proposed WRI was able to replicate the flood evolution over the passage of time and, therefore, could possibly aid in the early warning of water-related disasters, demonstrating its practicality for continuous monitoring of the flood risk when a sustained period of rainfall event is observed.

Very short-term reactive forecasting of the solar ultraviolet index using an extreme learning machine integrated with the solar zenith angle.

Exposure to erythemally-effective solar ultraviolet radiation (UVR) that contributes to malignant keratinocyte cancers and associated health-risk is best mitigated through innovative decision-support systems, with global solar UV index (UVI) forecast necessary to inform real-time sun-protection behaviour recommendations. It follows that the UVI forecasting models are useful tools for such decision-making. In this study, a model for computationally-efficient data-driven forecasting of diffuse and global very short-term reactive (VSTR) (10-min lead-time) UVI, enhanced by drawing on the solar zenith angle (θs) data, was developed using an extreme learning machine (ELM) algorithm. An ELM algorithm typically serves to address complex and ill-defined forecasting problems. UV spectroradiometer situated in Toowoomba, Australia measured daily cycles (0500-1700h) of UVI over the austral summer period. After trialling activations functions based on sine, hard limit, logarithmic and tangent sigmoid and triangular and radial basis networks for best results, an optimal ELM architecture utilising logarithmic sigmoid equation in hidden layer, with lagged combinations of θs as the predictor data was developed. ELM's performance was evaluated using statistical metrics: correlation coefficient (r), Willmott's Index (WI), Nash-Sutcliffe efficiency coefficient (ENS), root mean square error (RMSE), and mean absolute error (MAE) between observed and forecasted UVI. Using these metrics, the ELM model's performance was compared to that of existing methods: multivariate adaptive regression spline (MARS), M5 Model Tree, and a semi-empirical (Pro6UV) clear sky model. Based on RMSE and MAE values, the ELM model (0.255, 0.346, respectively) outperformed the MARS (0.310, 0.438) and M5 Model Tree (0.346, 0.466) models. Concurring with these metrics, the Willmott's Index for the ELM, MARS and M5 Model Tree models were 0.966, 0.942 and 0.934, respectively. About 57% of the ELM model's absolute errors were small in magnitude (±0.25), whereas the MARS and M5 Model Tree models generated 53% and 48% of such errors, respectively, indicating the latter models' errors to be distributed in larger magnitude error range. In terms of peak global UVI forecasting, with half the level of error, the ELM model outperformed MARS and M5 Model Tree. A comparison of the magnitude of hourly-cumulated errors of 10-min lead time forecasts for diffuse and global UVI highlighted ELM model's greater accuracy compared to MARS, M5 Model Tree or Pro6UV models. This confirmed the versatility of an ELM model drawing on θsdata for VSTR forecasting of UVI at near real-time horizon. When applied to the goal of enhancing expert systems, ELM-based accurate forecasts capable of reacting quickly to measured conditions can enhance real-time exposure advice for the public, mitigating the potential for solar UV-exposure-related disease.

Assessing the impact of various irrigation technologies on agricultural production: A water-energy­carbon nexus perspective.

Effective coordination of water, energy, and carbon is vital for the sustainable development of irrigated agriculture. However, limited research has been conducted on the impact of irrigation technology on the coupling and coordination relationship of these elements, especially on the North China Plain (NCP) where irrigation is applied extensively. This study establishes a water-energy­carbon (WEC) nexus framework based on footprint theory and energy analysis. Water utilization, energy consumption, and carbon emissions in a wheat production system under conventional irrigation (CI), sprinkler irrigation (SI), and drip irrigation (DI) technology on the NCP from 2000 to 2019 were quantified. Subsequently, the coupling coordination degree (CCD) model is used to analyze the interactions and correlations of the WEC nexus. Results indicated that SI and CI effectively reduced water consumption and mitigated water degradation, but this came at the expense of increased energy consumption and carbon emissions. The irrigation process represented the predominant share of energy consumption, representing 40.54 % and 37.64 % of the production-based energy consumption under SI and DI, respectively. The primary contributors to the production-based carbon footprint under CI, SI, and DI were N fertilizer (23.67 %), pipeline production (59.10 %), and irrigation electricity (21.85 %), respectively. The CCD range of WEC systems under the three irrigation technologies varied from 0.35 to 0.50 on the NCP during the investigation period. There were some slight differences in the average annual CCD between each irrigation technology, with DI (0.43) > SI (0.40) > CI (0.39). SI and DI was in basic coordination, while CI was in imbalanced type. Meanwhile, the spatial heterogeneity of CCD was fully reflected over time. Promoting water-saving irrigation technologies, developing clean energy, controlling the expansion of irrigation areas, and strengthening the connections among various subsystems are crucial measure to achieve regional WEC nexus coupling coordination.

An integrated framework for improving green agricultural production sustainability in human-natural systems.

Water scarcity, land pollution, and global warming are serious challenges and crises facing the development of sustainable or green agriculture and need to be addressed using efficient and environmentally friendly management strategies. This paper proposed an integrated framework appropriate for agricultural green total factor productivity (AGTFP) assessment coupled with microscopic and mesoscopic perspectives under water-energy-food (WEF) nexus, which generated scientific and reasonable strategies for green and low-carbon agriculture from internal core factors and peripheral environmental impacts to improve green agricultural production sustainability. Taking the Lianshui irrigation district (LID) with three sub-areas as the object, internal core factors were explored by partial least squares regression (PLSR) and the external impact path through partial least squares structural equation modeling (PLS-SEM). Results indicated that AGTFP in LID was the smallest (0.818) compared to the three sub-areas and was in a fluctuating state. Meanwhile, AGTFP which was calculated considering undesirable outputs, was closer to tangible productivity. Resource endowments and technical facilities will promote agricultural production, desirable outputs will stimulate green production, and undesirable outputs can inhibit green production. The external influence pathway was shown to be primary environment - > secondary environment - > economic aspects - > social aspects - > AGTFP. The innovative perspectives presented in this study can facilitate preferable decisions and avoid unintended consequences for human-natural systems.

Leaf Stoichiometry of Potentilla fruticosa Across Elevations in China's Qilian Mountains.

As an individual plant species can develop its own leaf stoichiometry to adapt to environmental changes, this stoichiometry can provide critical information about a plant species' growth and its potential management in the ecosystem housing it. However, leaf stoichiometry is largely undocumented in regions with large environmental changes arising from differences in elevation. The leaf stoichiometry of Potentilla fruticosa L., a major alpine shrub playing an important role in supporting ecosystem functions and services in China's Qilian Mountains (Northeast Qinghai-Tibetan Plateau), was investigated at different elevations (2,400, 2,600, 2,800, 3,000, 3,200, 3,500, and 3,800 m). At each elevation, leaf elemental (C, N, and P) concentrations were measured in P. fruticosa leaves sampled from three plots (10 × 10 m), and edaphic properties were assessed in nine quadrats (1 × 1 m, three quadrats per plot). Temperature and precipitation were calculated using an empirical formula. Maximum and minimum leaf carbon (C) concentrations ([C] leaf ) of 524 ± 5.88 and 403 ± 3.01 g kg-1 were measured at 2,600 and 3,500 m, respectively. Leaf nitrogen (N) concentration ([N] leaf ) showed a generally increasing trend with elevation and peaked at 3,500 m (27.33 ± 0.26 g kg-1). Leaf phosphorus (P) concentration ([P] leaf ) varied slightly from 2,400 to 3,200 m and then dropped to a minimum (0.60 ± 0.10 g kg-1) at 3800 m. The [C] leaf :[N] leaf , [C] leaf :[P] leaf , and [N] leaf :[P] leaf varied little from 2,400 to 3,000 m but fluctuated somewhat at higher elevations. The main factors affecting P. fruticosa leaf stoichiometry were soil organic C, pH, and soil total P, and the main limiting element for the growth of P. fruticosa in the study area was P. In conclusion, changes in elevation affected leaf stoichiometry of P. fruticosa mainly due to altered soil properties, and addressing phosphorus limitation, especially at higher elevations mainly due to losses caused by high precipitation and sparse vegetation, is a key measure to promote P. fruticosa growth in this region.

The role of climate change and vegetation greening on the variation of terrestrial evapotranspiration in northwest China's Qilian Mountains.

Terrestrial evapotranspiration (ETa) reflects the complex interactions of climate, vegetation, soil and terrain and is a critical component in water and energy cycles. However, the manner in which climate change and vegetation greening influence ETa remains poorly understood, especially in alpine regions. Drawing on the Global Land Evaporation Amsterdam Model (GLEAM) ETa data, the interannual variability of ETa and its ties to precipitation (P), potential evaporation (ETp) and vegetation (NDVI) were analysed. The Budyko framework was implemented over the period of 1982 to 2015 to quantify the response of ETa to climate change's direct (P and ETp) and indirect (NDVI) impacts. The ETa, P, ETp and NDVI all showed significant increasing trends from 1981 to 2015 with rates of 1.52 mm yr-1, 3.18 mm yr-1, 0.89 mm yr-1 and 4.0 × 10-4 yr-1, respectively. At the regional level, the positive contribution of increases in P and NDVI offset the negative contribution of ETp to the change in ETa (∆ETa). The positive ∆ETa between 1982 and 2001 was strongly linked with the concomitant increase in NDVI. Increases in vegetation contributing to a positive ∆ETa differed among landscape types: for shrub, meadow and steppe they occurred during both periods, for alpine vegetation between 1982 and 2001, and for desert between 2002 and 2015. Climate change directly contributed to a rise in ETa, with P as the dominant factor affecting forested lands during both periods, and alpine vegetation between 2002 and 2015. Moreover, ETp was a dominant factor for the desert between 1982 and 2001, where the variation of P was not significant. The contributions of factors having an impact on ∆ETa are modulated by both the sensitivity of impact factors acting on ETa as well as the magnitudes of factor changes. The greening of vegetation can influence ETa by increasing vegetation transpiration and rainfall interception in forest, brush and meadow landscapes. These findings can help in developing a better understanding of the interaction of ecosystems and hydrology in alpine regions.

Causality of climate, food production and conflict over the last two millennia in the Hexi Corridor, China.

The relationship between climate and human society has frequently been investigated to ascertain whether climate variability can trigger social crises (e.g., migration and armed conflicts). In the current study, statistical methods (e.g., correlation analysis and Granger Causality Analysis) are used in a systematic analysis of the potential causality of climate variability on migration and armed conflicts. Specifically, the statistical methods are applied to determine the relationships between long-term fine-grained temperature and precipitation data and contemporary social conditions, gleaned from historical documents covering the last two millennia in China's Hexi Corridor. Results found the region's reconstructed temperature to be strongly coupled with precipitation dynamics, i.e., a warming climate was associated with a greater supply of moisture, whereas a cooling period was associated with more frequent drought. A prolonged cold period tended to coincide with societal instability, such as a shift from unification towards fragmentation. In contrast, a prolonged warm period coincided with rapid development, i.e., a shift from separation to unification. The statistical significance of the causality linkages between climate variability, bio-productivity, grain yield, migration and conflict suggests that climate variability is not the direct causative agent of these phenomena, but that climate reduced food production which gradually lead to migration and conflicts. A conceptual causal model developed through this study describes the causative pathway of climate variability impacts on migration and conflicts in the Hexi Corridor. Applied to current conditions, the model suggests that steady and proactive promotion of the nation's economic buffering capacity might best address the uncertainty brought on by a range of potential future climate scenarios and their potential impacts.

Effects of stand age on carbon storage in dragon spruce forest ecosystems in the upper reaches of the Bailongjiang River basin, China.

At an ecosystem level, stand age has a significant influence on carbon storage (CS). Dragon spruce (Picea asperata Mast.) situated along the upper reaches of the Bailongjiang River in northwest China were categorized into three age classes (29-32 years, Y1; 34-39 years, Y2; 40-46 years, Y3), and age-related differences in total carbon storage (TCS) of the forest ecosystem were investigated for the first time. Results showed that TCS for the Y1, Y2, and the Y3 age groups were 323.64, 240.66 and 174.60 Mg ha-1, respectively. The average TCS of the three age groups was 255.65 Mg C ha-1, with above-ground biomass, below-ground biomass, litter, and soil in the top 0.6 m contributing 15.0%, 3.7%, 12.1%, and 69.2%, respectively. CS in soil and TCS of the Y1 age group both significantly exceeded those of the Y3 age group (P < 0.05). Contrary to other recent findings, the present study supports the hypothesis that TCS is likely to decrease as stand age increases. This indicates that natural resource managers should rejuvenate forests by routinely thinning older stands, thereby not only achieving vegetation restoration, but also allowing these stands to create a long-term carbon sink for this important eco-region.