Modeling rangelands as spatially-explicit complex adaptive systems.

Rangelands cover one third of the earth's land area, provide livelihoods for one billion persons, and most have been degraded by overgrazing of domestic livestock. Recent debate about best management practices often has centered on comparison of continuous grazing and rotational grazing. Resolution to this debate may lie in viewing rangelands as complex adaptive systems. We describe a spatially-structured, individual-based model of rangelands that embodies this perspective, and simulate forage dynamics and cattle production under semi-arid rangeland conditions typical of the southern Great Plains of the USA employing both continuous and rotational grazing. Relative "success" of simulated grazing schemes depended primarily on the evaluation metric used (e.g., rangeland ecological condition, sale weight of cattle, secondary production efficiency) and the particular manage scheme employed, and neither continuous nor rotational grazing schemes were uniformly more successful. Our results demonstrate that solution of the grazing systems debate is unlikely to be found in a single group of grazing schemes, but, rather, in adaptive management of feedbacks among system components. The present work provides an example of how modeling rangelands as complex adaptive systems can aid in the evaluation of management schemes.

Qualitative Dynamics of Suspended Particulate Matter in the Changjiang Estuary from Geostationary Ocean Color Images: An Empirical, Regional Modeling Approach.

The suspended particulate matter (SPM) in Changjiang Estuary is characterized by a high concentration of significant diurnal dynamics. With a higher temporal resolution (eight images obtained per day), Geostationary Ocean Color Imager (GOCI) was selected as the primary remote sensor for the dynamics monitoring in this paper, instead of other satellite sensor working in polar orbit. Based on the characteristics of the field spectra measured in the estuary, an empirical model was established with the band ratio of Rrs745 divided by Rrs490 and proven effective in Suspended Particulate Matter (SPM) estimation (R² = 0.9376, RMSE = 89.32 mg/L). While, Validation results showed that the model performed better in coastal turbid waters than offshore clear waters with higher chlorophyll-a concentration, stressing the importance of partitioning SPM into its major components and doing separate analysis. The hourly observations from GOCI showed that the diurnal variation magnitudes exhibited clear regional characteristics, with a maximum in the turbidity belt near the mouth and a minimum in the offshore deeper areas. In addition, comparing the monthly averaged SPM distribution with the amount of sediment discharged into the estuary, the variation in estuarine turbidity maximum zone is more likely contributed by the sediments resuspended from the sea bed that has already accumulated in the estuarine delta.

When does diversity matter? Species functional diversity and ecosystem functioning across habitats and seasons in a field experiment.

Despite ample experimental evidence indicating that biodiversity might be an important driver of ecosystem processes, its role in the functioning of real ecosystems remains unclear. In particular, the understanding of which aspects of biodiversity are most important for ecosystem functioning, their importance relative to other biotic and abiotic drivers, and the circumstances under which biodiversity is most likely to influence functioning in nature, is limited. We conducted a field study that focussed on a guild of insect detritivores in streams, in which we quantified variation in the process of leaf decomposition across two habitats (riffles and pools) and two seasons (autumn and spring). The study was conducted in six streams, and the same locations were sampled in the two seasons. With the aid of structural equations modelling, we assessed spatiotemporal variation in the roles of three key biotic drivers in this process: functional diversity, quantified based on a species trait matrix, consumer density and biomass. Our models also accounted for variability related to different litter resources, and other sources of biotic and abiotic variability among streams. All three of our focal biotic drivers influenced leaf decomposition, but none was important in all habitats and seasons. Functional diversity had contrasting effects on decomposition between habitats and seasons. A positive relationship was observed in pool habitats in spring, associated with high trait dispersion, whereas a negative relationship was observed in riffle habitats during autumn. Our results demonstrate that functional biodiversity can be as significant for functioning in natural ecosystems as other important biotic drivers. In particular, variation in the role of functional diversity between seasons highlights the importance of fluctuations in the relative abundances of traits for ecosystem process rates in real ecosystems.

Methane ebullition fluxes and temperature sensitivity in a shallow lake.

Inland waters are important sources of atmospheric methane (CH4), with a major contribution from the CH4 ebullition pathway. However, there is still a lack of CH4 ebullition flux (eFCH4) and their temperature sensitivity (Q10) in shallow lakes, which might lead to large uncertainties in CH4 emission response from aquatic to climate and environmental change. Herein, the magnitude and regulatory of two CH4 pathways (ebullition and diffusion) were studied in subtropical Lake Chaohu, China, using the real-time portable greenhouse gas (GHG) analyzer-floating chamber method at 18 sites over four seasons. eFCH4 (12.06 ± 4.10 nmol m-2 s-1) was the dominant contributing pathway (73.0 %) to the two CH4 emission pathways in Lake Chaohu. The whole-lake mass balance calculation demonstrated that 56.6 % of the CH4 emitted from the sediment escaped through the ebullition pathway. eFCH4 was significantly higher in the western (WL: 16.54 ± 22.22 nmol m-2 s-1) and eastern lake zones (EL: 11.89 ± 15.43 nmol m-2 s-1) than in the middle lake zone (ML: 8.86 ± 13.78 nmol m-2 s-1; p < 0.05) and were significantly higher in the nearshore lake zone (NL: 15.94 ± 19.58 nmol m-2 s-1) than in the pelagic lake zone (PL: 6.64 ± 12.37 nmol m-2 s-1; p < 0.05). eFCH4 was significantly higher in summer (32.12 ± 13.82 nmol m-2 s-1) than in other seasons (p < 0.05). eFCH4 had a strong temperature dependence. Sediment total organic carbon (STOC) is an important ecosystem level Q10 driver of eFCH4. The meta-analysis also verified that across ecosystems the ecosystem-level Q10 of eFCH4 was significantly positively correlated with STOC and latitude (p < 0.05). This study suggests that eFCH4 will become increasingly crucial in shallow lake ecosystems as climate change and human activities increase. The potential increase in ebullition fluxes in high-latitude lakes is of great importance.

Heavy metals in centralized drinking water sources of the Yangtze River: A comprehensive study from a basin-wide perspective.

Water quality in the Yangtze River Basin (YRB) has received considerable attention because it supplies water to 400 million people. However, the trends, sources, and risks associated with heavy metals (HMs) in water of centralized drinking water sources (CDWSs) in the YRB region are not well understood due to the lack of high-frequency, large-scale monitoring data. Moreover, research on the factors affecting the transportation of HMs in natural water are limited, all of which significantly reduce the effectiveness of CDWSs management. Therefore, this study utilized data on 11 HMs and water quality from 114 CDWSs, covering 71 prefecture-level cities (PLC) in 15 provinces (cities), to map unprecedented geospatial distribution of HMs in the YRB region and examine their concentrations in relation to water chemistry parameters. The findings revealed that the frequency of detection (FOD) of 11 HMs ranged from 28.59% (Hg) to 99.64% (Ba). The mean concentrations are ranked as follows: Ba (40.775 µg/L) > B (21.866 µg/L) > Zn (5.133 µg/L) > V (2.668 µg/L) > Cu (2.049 µg/L) > As (1.989 µg/L) > Mo (1.505 µg/L) > Ni (1.108 µg/L) > Sb (0.613 µg/L) > Pb (0.553 µg/L) > Hg (0.002 µg/L). Concentrations of Zn, As, Hg, Pb, Mo, Sb, Ni, and Ba exhibited decreasing trends from 2018 to 2022. Human activities, including industrial and agricultural production, have led to higher pollution levels in the midstream and downstream of the river than in its upstream. Additionally, the high concentrations of Ba and B are influenced by natural geological factors. Anion concentrations and nutrient levels, play a significant role in the transport of HMs in water. Probabilistic health risk assessment indicates that As, Ba, and Sb pose a potential carcinogenic risk. Additionally, non-carcinogenic risk to children under extreme conditions should also be considered.

Modeling spatial-temporal variability of PM2.5 concentrations in Belt and Road Initiative (BRI) region via functional adaptive density approach.

The rapid development of the Belt and Road Initiative (BRI) has led to severe air pollution dominated by PM2.5 concentrations which can cause a profound negative impact on human health and economic activity. This problem poses a critical environmental challenge to efficiently handling large-scale spatial-temporal PM2.5 data in this extended region. Functional data analysis (FDA) technique offers powerful tools that have the potential to enhance the analysis of spatial distributions and temporal dynamic changes in high-dimensional pollution data. However, modeling the spatial-temporal variability of PM2.5 concentrations by FDA remains unrevealed in the BRI region. To address this research gap, our study aimed to achieve two main objectives: first, to model the spatial-temporal dynamic variability of PM2.5 in 125 BRI nations (1998-2021), and second, to identify the underlying clusters behind the variations. We employed the recently developed functional adaptive density peak (FADP) clustering approach to solve the current problem. The proposed method is based on the joint use of functional principal components (FPCs) and functional cluster analyses. The main results are as follows: (i) The first three FPCs almost captured 99% of the total variations involving all valuable information on PM2.5 concentrations. (ii) PM2.5 pollution was highly concentrated in the developing countries (Pakistan, Bangladesh, and Nigeria) and the developed countries (Arabian Gulf countries: Qatar, United Arab Emirates, Bahrain, Saudi Arabia, Oman), and the least developed countries (Yemen and Chad). (iii) Three optimal clusters were identified and thus classified the PM2.5 into three distinct degrees of pollution: severe, moderate, and light. (iv) Cluster 1 had a severe pollution effect degree with a high rate of change, and it covered the Arabian Peninsula countries, African countries (Cameroon, Egypt, Gambia, Mali, Mauritania, Nigeria, Sudan, Senegal, Chad), Bangladesh, and Pakistan. (v) About 62 BRI countries belonged to cluster 2 showing a light pollution degree with annul average of less than 20 [Formula: see text]; this pointed out that the PM2.5 concentration remains stable in the cluster 2-related countries. The findings of this research would benefit governments and policymakers in preventing and controlling PM2.5 pollution exposure in BRI. Furthermore, this research could pay attention to sustainable development goals and the vision of the Green BRI policy.

Decreasing mercury levels in consumer fish over the three decades of increasing mercury emissions in China.

Fish consumption is the primary dietary route of human exposure to methylmercury. It has been well documented that elevated mercury concentration in fish in North America and Europe is linked to anthropogenic mercury emissions. China is the world's largest producer, consumer, and emitter of mercury, as well as the world's largest commercial fish producer and consumer. Although mercury pollution in fish in China is currently receiving much attention worldwide, its status remains largely unknown. Here, we conducted a meta-analysis on total mercury concentrations in marine and freshwater fish samples, covering 35,464 samples collected in China over the past 30 years. It is found that, opposite to the increasing emission and documented mercury contamination events, mercury levels in fish have gradually decreased in China over the past 30 years. The results were in sharp contrast to those found in North America and Europe. The mercury concentrations in fish were significantly anticorrelated with the fish catch and fish aquaculture and were inverse to trophic levels. Overfishing and the short lifecycle of aquaculture fish, both reducing the trophic level and the duration of mercury accumulation, were the most likely causes leading to the decline of mercury concentrations found in fish in China.

Review on pollution damage costs accounting.

Although the concept of damage cost accounting is already well-studied and applied, its application to pollution still lacks of an integrated accounting framework, while the spatial-temporal variability of accounting results has not been fully discussed. To fill this gap, this review frames the existing models and their limitations into static and dynamic categories, outlining the characteristics of different methods, which consider both human and non-human damages caused by pollution. Existing data sources, that could be used for accounting purposes, are detailed. Finally, this work discusses the relevance of spatial scales for the computation process, in order to obtain a more detailed information support for environmental policies for future compensatory actions. Conclusions highlights the need to develop a more comprehensive database of exposure-response relationships and to incorporate system alternatives into models to achieve a more accurate damage assessment.

Evaluating national ecological risk of agricultural pesticides from 2004 to 2017 in China.

In recent years, excessive application and loss of pesticides have caused great risks to the aquatic systems, but the spatio-temporal variability in the ecological risk that agricultural pesticides pose to aquatic systems has not been explored at the national scale. In this study, an integrated assessment framework was proposed for the potential ecological risk of surface water caused by agricultural pesticide loss. The spatio-temporal variability in the potential ecological risk caused by agricultural pesticide runoff was evaluated. Based on the results, the total pesticide emissions increased from 165.47 tons in 2004 to 179.77 tons in 2017. Among the three pesticide types, insecticide had the largest application, but its runoff was estimated as the lowest. High-risk areas of insecticide runoff were concentrated in the east, south and central part of China, while the central region of China was identified as a hotspot due to the high and the ever-increasing ecological risk. This study provides an integrated method for potential ecological risk assessment of agricultural pesticide runoff to adjacent water bodies in large-scale regions and the results of the study have direct implications for environmental policies on pesticide management in China and around the world.

Asian Culturally Specific Predictors in a Large-Scale Land Use Regression Model to Predict Spatial-Temporal Variability of Ozone Concentration.

This paper developed a land use regression (LUR) model to study the spatial-temporal variability of O3 concentrations in Taiwan, which has typical Asian cultural characteristics with diverse local emission sources. The Environmental Protection Agency's (EPA) data of O3 concentrations from 2000 and 2013 were used to develop this model, while observations from 2014 were used as the external data verification to assess model reliability. The distribution of temples, cemeteries, and crematoriums was included for a potential predictor as an Asian culturally specific source for incense and joss money burning. We used stepwise regression for the LUR model development, and applied 10-fold cross-validation and external data for the verification of model reliability. With the overall model R² of 0.74 and a 10-fold cross-validated R² of 0.70, this model presented a mid-high prediction performance level. Moreover, during the stepwise selection procedures, the number of temples, cemeteries, and crematoriums was selected as an important predictor. By using the long-term monitoring data to establish an LUR model with culture specific predictors, this model can better depict O3 concentration variation in Asian areas.

Meteorological influences on process-based spatial-temporal pattern of throughfall of a xerophytic shrub in arid lands of northern China.

Numerous field experiments had demonstrated great spatial variability and temporal stability of throughfall under tree canopies within forested ecosystems. Nonetheless, no known studies have investigated the intrastorm spatial-temporal variability of throughfall beneath xerophytic shrub canopies within arid desert ecosystems where water is typically the principal limiting factor determining the structure and dynamics of ecosystems. Here we investigated the spatial-temporal pattern of throughfall at intrastorm scale, and systematically examined the effects of meteorological variables on throughfall based on the principal components analysis (PCA) and a multiple regression model. Throughfall was monitored at 10-min intervals by placing tipping-bucket rain gauges at different radial directions beneath 3 shrubs of Caragana korshinskii during the growing season of 2016 within a water-limited arid desert ecosystem of northern China. We found the temporal heterogeneity of rainfall clearly affected the timing of throughfall beneath shrub canopies within discrete rainfall events. Throughfall also differed markedly among different radial directions beneath shrub canopies, which was found to be well associated with wind directions during rainfall events. PCA on meteorological variables indicated that three principal components accounted for 84.2% of the total variance, and we found that the second principal component (loaded strongly on rainfall amount and maximum 10-min rainfall intensity) was the dominant component controlling throughfall and its spatial variability after introducing three principal components into a multiple linear regression model. Our findings highlight the spatial-temporal variability of throughfall at the intrastorm scale, and are expected to be helpful for an improved process-based characterization and modelling of throughfall in vast arid desert ecosystems.

Multi-Temporal and Spectral Analysis of High-Resolution Hyperspectral Airborne Imagery for Precision Agriculture: Assessment of Wheat Grain Yield and Grain Protein Content.

This study evaluates the potential of high resolution hyperspectral airborne imagery to capture within-field variability of durum wheat grain yield (GY) and grain protein content (GPC) in two commercial fields in the Yaqui Valley (northwestern Mexico). Through a weekly/biweekly airborne flight campaign, we acquired 10 mosaics with a micro-hyperspectral Vis-NIR imaging sensor ranging from 400-850 nanometres (nm). Just before harvest, 114 georeferenced grain samples were obtained manually. Using spectral exploratory analysis, we calculated narrow-band physiological spectral indices-normalized difference spectral index (NDSI) and ratio spectral index (RSI)-from every single hyperspectral mosaic using complete two by two combinations of wavelengths. We applied two methods for the multi-temporal hyperspectral exploratory analysis: (a) Temporal Principal Component Analysis (tPCA) on wavelengths across all images and (b) the integration of vegetation indices over time based on area under the curve (AUC) calculations. For GY, the best R2 (0.32) were found using both the spectral (NDSI-Ri, 750 to 840 nm and Rj, ±720-736 nm) and the multi-temporal AUC exploratory analysis (EVI and OSAVI through AUC) methods. For GPC, all exploratory analysis methods tested revealed (a) a low to very low coefficient of determination (R2 ≤ 0.21), (b) a relatively low overall prediction error (RMSE: 0.45-0.49%), compared to results from other literature studies, and (c) that the spectral exploratory analysis approach is slightly better than the multi-temporal approaches, with early season NDSI of 700 with 574 nm and late season NDSI of 707 with 523 nm as the best indicators. Using residual maps from the regression analyses of NDSIs and GPC, we visualized GPC within-field variability and showed that up to 75% of the field area could be mapped with relatively good predictability (residual class: -0.25 to 0.25%), therefore showing the potential of remote sensing imagery to capture the within-field variation of GPC under conventional agricultural practices.

Contrasting effects of nitrogen addition on soil respiration in two Mediterranean ecosystems.

Increased atmospheric nitrogen (N) deposition is known to alter ecosystem carbon source-sink dynamics through changes in soil CO2 fluxes. However, a limited number of experiments have been conducted to assess the effects of realistic N deposition in the Mediterranean Basin, and none of them have explored the effects of N addition on soil respiration (R s ). To fill this gap, we assessed the effects of N supply on R s dynamics in the following two Mediterranean sites: Capo Caccia (Italy), where 30 kg ha-1 year-1 was supplied for 3 years, and El Regajal (Spain), where plots were treated with 10, 20, or 50 kg N ha-1 year-1 for 8 years. Results show a complex, non-linear response of soil respiration (R s ) to N additions with R s overall increasing at Capo Caccia and decreasing at El Regajal. This suggests that the response of R s to N addition depends on dose and duration of N supply, and the existence of a threshold above which the N introduced in the ecosystem can affect the ecosystem's functioning. Soil cover and seasonality of precipitations also play a key role in determining the effects of N on R s as shown by the different responses observed across seasons and in bare soil vs. the soil under canopy of the dominant species. These results show how increasing rates of N addition may influence soil C dynamics in semiarid ecosystems in the Mediterranean Basin and represent a valuable contribution for the understanding and the protection of Mediterranean ecosystems.

Spatial and temporal variability of (7)Be and (210)Pb wet deposition during four successive monsoon storms in a catchment of northern Laos.

Fallout radionuclides (7)Be and (210)Pb have been identified as potentially relevant temporal tracers for studying soil particles dynamics (surface vs. subsurface sources contribution; remobilization of in-channel sediment) during erosive events in river catchments. An increasing number of studies compared (7)Be: (210)Pb activity ratio in rainwater and sediment to estimate percentages of freshly eroded particles. However, the lack of data regarding the spatial and temporal variability of radionuclide wet deposition during individual storms has been identified as one of the main gaps in these estimates. In order to determine these key parameters, rainwater samples were collected at three stations during four storms that occurred at the beginning of the monsoon (June 2013) in the Houay Xon mountainous catchment in northern Laos. Rainwater (7)Be and (210)Pb activities measured using very low background hyperpure Germanium detectors ranged from 0.05 to 1.72 Bq L(-1) and 0.02 to 0.26 Bq L(-1), respectively. Water δ(18)O were determined on the same samples. Total rainfall amount of the four sampled storms ranged from 4.8 to 26.4 mm (51 mm in total) at the time-fractionated collection point. Corresponding cumulative (7)Be and (210)Pb wet depositions during the sampling period were 17.6 and 2.9 Bq m(-2), respectively. The (7)Be: (210)Pb activity ratio varied (1) in space from 6 to 9 for daily deposition and (2) in time from 3 to 12 for samples successively collected. Intra-event evolution of rainwater (7)Be and (210)Pb activities as well as δ(18)O highlighted the progressive depletion of local infra-cloud atmosphere radionuclide stock with time (washout), which remains consistent with a Raleigh-type distillation process for water vapour. Intra-storm ratio increasing with time showed the increasing contribution of rainout scavenging. Implications of such variability for soil particle labelling and erosion studies are briefly discussed and recommendations are formulated for the collection of rainwater signature in studies based on the (7)Be: (210)Pb ratio method, especially in tropical areas under high erosive pressure.