Journal Paper Digests

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Journal Paper Digests 2019 #6

  • Prominence of the tropics in the recent rise of global nitrogen pollution
  • Estimation of Surface Soil Moisture With Downscaled Land Surface Temperatures Using a Data Fusion Approach for Heterogeneous Agricultural Land
  • Characterization of contamination levels of heavy metals in agricultural soils using geochemical baseline concentrations
  • Building Ecological Resilience in Highly Modified Landscapes
  • Robust soil mapping at the farm scale with vis-NIR spectroscopy
  • Lanthanides in granulometric fractions of Mediterranean soils. Can they be used as fingerprints of provenance?
  • A novel hierarchical clustering analysis method based on Kullback-Leibler divergence and application on dalaimiao geochemical exploration data
  • Can alternative cropping systems mitigate nitrogen losses and improve GHG balance? Results from a 19-yr experiment in Northern France

Prominence of the tropics in the recent rise of global nitrogen pollution

Authors: Lee, M; Shevliakova, E; Stock, CA; Malyshev, S; Milly, PCD

Source: NATURE COMMUNICATIONS, 10 1437-1437; MAR 29 2019

Abstract: Nitrogen (N) pollution is shaped by multiple processes, the combined effects of which remain uncertain, particularly in the tropics. We use a global land biosphere model to analyze historical terrestrial-freshwater N budgets, considering the effects of anthropogenic N inputs, atmospheric CO2, land use, and climate. We estimate that globally, land currently sequesters 11 (10-13)% of annual N inputs. Some river basins, however, sequester >50% of their N inputs, buffering coastal waters against eutrophication and society against greenhouse gas-induced warming. Other basins, releasing >25% more than they receive, are mostly located in the tropics, where recent deforestation, agricultural intensification, and/or exports of land N storage can create large N pollution sources. The tropics produce 56 +/- 6% of global land N pollution despite covering only 34% of global land area and receiving far lower amounts of fertilizers than the extratropics. Tropical land use should thus be tho roughly considered in managing global N pollution.

Estimation of Surface Soil Moisture With Downscaled Land Surface Temperatures Using a Data Fusion Approach for Heterogeneous Agricultural Land

Authors: Bai, LL; Long, D; Yan, L

Source: WATER RESOURCES RESEARCH, 55 (2):1105-1128; FEB 2019

Abstract: Field-scale surface soil moisture (SSM, 0-10cm), which is closely linked with land surface temperature (LST), is particularly important to agricultural water resource management. Active and passive microwave remote sensing-based SSM retrievals on the order of kilometer squared resolutions are difficult to apply to heterogeneous agricultural land surfaces that may need SSM data at a resolution of 30m. In this study, the High-resolution Urban Thermal Sharpener and Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model were applied to downscale optical and thermal remote sensing data simultaneously by blending Landsat and MODIS red-near infrared-LST data, with the ultimate goal to generate field-scale SSM values from the trapezoidal approach. To evaluate the performance of the downscaled LSTE (based on the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model method) and SSM, an irrigation district (Area 1) in Inner Mongolia and an irrigation district in the N orth China Plain (Area 2) with varying spatial heterogeneity were selected as the testbeds. Results indicated that the downscaled LSTE was highly consistent with synchronous Landsat LSTH and in situ LST measurements in Area 1, with the root-mean-square error ranging from 0.73 to 2.75K. Compared with the MODIS SSM, the average root-mean-square error of the downscaled SSM improved from 0.048 to 0.038cm(3)/cm(3) for both areas. The downscaled LSTE and SSM developed in this study enhance the spatiotemporal resolutions of the SSM estimates, maximizing the potential of remotely sensed information for agricultural water resource management.Plain Language Summary Field-scale (30 m) surface soil moisture (SSM), closely linked with land surface temperature (LST), is particularly important for agricultural water resource management, such as for assessment of agricultural droughts, optimization of irrigation schedules and improvement of water use efficiency, particularly in the heteroge neous agricultural land. Here, the High resolution Urban The! rmal Sharpener (HUTS) and Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM) were jointly adopted to downscale optical and thermal remote sensing data simultaneously by blending Landsat and MODIS Red-Near infrared-LST data, with the ultimate goal to generate field-scale SSM values from the downscaled Red-Near infrared-LST remote sensing data using the theoretical trapezoidal approach. The field-scale LST and SSM developed in this study maximize the potential of remotely sensed information, improve both the spatial and temporal resolutions of SSM, and provide more valuable information on heterogeneous land surfaces for agricultural water resource management.

Characterization of contamination levels of heavy metals in agricultural soils using geochemical baseline concentrations

Authors: Niu, SP; Gao, LM; Wang, X

Source: JOURNAL OF SOILS AND SEDIMENTS, 19 (4):1697-1707; APR 2019

Abstract: Purpose It is currently very difficult to accurately evaluate the soil contamination by heavy metals (HMs) attributed to the unavailability of local geochemical background values (LGBVs). This study was performed to establish the geochemical baseline concentrations (GBCs), as an alternative for LGBVs to use for HM pollution assessment of agricultural soil.Materials and methods GBCs of the HMs selected were determined using the cumulative frequency distribution curves (CFDCs). GBCs were then used to pursue the HM soil pollution and associated ecological risks, via calculation of geo-accumulation indices (I-geo), pollution load indices (PLI), as well as potential ecological risk indices (RI).Results and discussion As to the soil investigated, the GBCs of Ni, Zn, Pb, and Cr were 29.34mg/kg, 45.54mg/kg, 21.81mg/kg, and 33.65mg/kg, respectively. I-geo values ranged from -4.58 to 0.33 (Ni), from -2.46 to 2.14 (Zn), from -5.32 to 0.77 (Pb), and from -3.83 to 0.96 (Cr), suggesting th at the region was not polluted by these HMs. PLI values ranged from 0.08 to 2.45 with an average of 1.02. 49.6% of soil samples had the PLI values >1.0, indicating that some of the soil may be moderately contaminated by HMs. The RI values of selected HMs were <150, indicating a low potential ecological risk. Principal component analysis (PCA) implied Zn, Pb, and Cr were mainly sourced from parent (geological) materials, as well as agricultural activities, atmospheric deposition, etc., depending on the element.ConclusionsThe present study illustrates the necessity of the characterization of GBCs at a regional scale, allowing for more accurate assessment of soil contamination by HMs. We hope that this will eventually lead to further development of better environmental management practices for agricultural soil polluted by HMs.

Building Ecological Resilience in Highly Modified Landscapes

Authors: Beller, EE; Spotswood, EN; Robinson, AH; Anderson, MG; Higgs, ES; Hobbs, RJ; Suding, KN; Zavaleta, ES; Grenier, JL; Grossinger, RM

Source: BIOSCIENCE, 69 (1):80-92; JAN 2019

Abstract: Ecological resilience is a powerful heuristic for ecosystem management in the context of rapid environmental change. Significant efforts are underway to improve the resilience of biodiversity and ecological function to extreme events and directional change across all types of landscapes, from intact natural systems to highly modified landscapes such as cities and agricultural regions. However, identifying management strategies likely to promote ecological resilience remains a challenge. In this article, we present seven core dimensions to guide long-term and large-scale resilience planning in highly modified landscapes, with the objective of providing a structure and shared vocabulary for recognizing opportunities and actions likely to increase resilience across the whole landscape. We illustrate application of our approach to landscape-scale ecosystem management through case studies from two highly modified California landscapes, Silicon Valley and the Sacramento-San Joaquin Delta. We propose that resilience-based management is best implemented at large spatial scales and through collaborative, cross-sector partnerships.

Robust soil mapping at the farm scale with vis-NIR spectroscopy

Authors: Ramirez-Lopez, L; Wadoux, AMJC; Franceschini, MHD; Terra, FS; Marques, KPP; Sayao, VM; Dematte, JAM

Source: EUROPEAN JOURNAL OF SOIL SCIENCE, 70 (2):378-393; MAR 2019

Abstract: Sustainable agriculture practices are often hampered by the prohibitive costs associated with the generation of fine-resolution soil maps. Recently, several papers have been published highlighting how visible and near infrared (vis-NIR) reflectance spectroscopy may offer an alternative to address this problem by increasing the density of soil sampling and by reducing the number of conventional laboratory analyses needed. However, for farm-scale soil mapping, previous studies rarely focused on sample optimization for the calibration of vis-NIR models or on robust modelling of the spatial variation of soil properties predicted by vis-NIR spectroscopy. In the present study, we used soil vis-NIR spectroscopy models optimized in terms of both number of calibration samples and accuracy for high-resolution robust farm-scale soil mapping and addressed some of the most common pitfalls identified in previous research. We collected 910 samples from 458 locations at two depths (A, 0-0.20 m; B, 0.80-1.0 m) in the state of Sao Paulo, Brazil. All soil samples were analysed by conventional methods and scanned in the vis-NIR spectral range. With the vis-NIR spectra only, we inferred statistically the optimal set size and the best samples with which to calibrate vis-NIR models. The calibrated vis-NIR models were validated and used to predict soil properties for the rest of the samples. The prediction error of the spectroscopic model was propagated through the spatial analysis, in which robust block kriging was used to predict particle-size fractions and exchangeable calcium content for each depth. The results indicated that statistical selection of the calibration samples based on vis-NIR spectra considerably decreased the need for conventional chemical analysis for a given level of mapping accuracy. The methods tested in this research were developed and implemented using open-source software. All codes and data are provided for reproducible research purposes.

Lanthanides in granulometric fractions of Mediterranean soils. Can they be used as fingerprints of provenance?

Authors: Martin-Garcia, JM; Molinero-Garcia, A; Calero, J; Fernandez-Gonzalez, MV; Parraga, J; Delgado, R

Source: EUROPEAN JOURNAL OF SOIL SCIENCE, 70 (2):394-410; MAR 2019

Abstract: There is geochemical interest in the lanthanides because they behave like a group that is closely related to the parent materials during surface processes, although they also undergo fractionation as a result of supergene dynamics. We analysed lanthanide concentrations (ICPms) in the granulometric fractions fine sand, clay and free forms of clay (FFclay-CDB and FFclay-Ox: extracted with citrate-dithionite-sodium bicarbonate and with ammonium oxalate, respectively) from a soil chronosequence of Mediterranean soils. There was a relative enrichment of heavy rare earth elements (HREE) in the clay fraction and its free forms with respect to fine sand. The clay free forms behaved as scavengers of lanthanides, and oxidative scavenging of cerium (Ce) in FFclay-CDB was also detected. Lanthanide concentrations (lanthanum to gadolinium in fine sand; terbium to lutetium in clay) varied with soil age, and chronofunctions were established. There was a strong positive collinearity between m ost of the lanthanide concentrations. Furthermore, the value of the correlation index (Pearson’s r) of the concentrations between couples of lanthanides (r(CLC)) decreased significantly with increasing separation between the elements in the periodic table; this has never been described in soils. Several geochemical properties and indices in the fine sand and clay soil fractions and in the geological materials of the Guadalquivir catchment showed, on the one hand, a genetic relation between them all, enabling the lanthanides to be used as fingerprints of provenance; on the other hand, fractionation between fine sand and clay showed these are actively involved in soil lanthanide dynamics.

A novel hierarchical clustering analysis method based on Kullback-Leibler divergence and application on dalaimiao geochemical exploration data

Authors: Yang, J; Grunsky, E; Cheng, QM

Source: COMPUTERS & GEOSCIENCES, 123 10-19; FEB 2019

Abstract: In this paper, we propose a new hierarchical clustering analysis method (HCA) that uses Kullback-Leibler divergence (D-KLS) of pairwise geochemical datasets of geo-objects (e.g., lithological units) as a measure of proximity. The method can reveal relationships among geo-objects based on geochemistry. This capability is verified through an application with geochemical exploration data from regolith that overlies the Dalaimiao region in China. D-KLSM and D-KLSC, two parts of D-KLS, respectively describe the differences on the mean and the differences on covariance and are also used as measures of proximity. D-KLSM characterizes rock type and D-KLSC. describes spatial relationships and component similarities between geo-objects. This contribution not only provides a tool that can reveal relationships between geo-objects based on geochemical data, but also reveals that D-KLS and its two parts can characterize geochemical differences from different perspectives. These measures ho ld promise in the enhancement of methods for recognizing geochemical patterns.

Can alternative cropping systems mitigate nitrogen losses and improve GHG balance? Results from a 19-yr experiment in Northern France

Authors: Autret, B; Beaudoin, N; Rakotovololona, L; Bertrand, M; Grandeau, G; Grehan, E; Ferchaud, F; Mary, B

Source: GEODERMA, 342 20-33; MAY 15 2019

Abstract: Alternative cropping systems are promoted to reduce nitrogen (N) losses in the environment and mitigate greenhouse gas (GHG) emissions. However, these supposed benefits are not fully known, rarely studied together and on the long-term. Here, we studied the N inputs, N exports, soil organic N (SON) storage, N leaching, gaseous N emissions and GHG balance in a 19-yr field experiment comparing four arable cropping systems without manure fertilization, under conventional (CON), low-input (LI), conservation agriculture (CA) and organic (ORG) managements. The N surplus, i.e. the difference between total N inputs and exports, was lowest in LI (43 kg ha(-1) yr(-1)), intermediary for CON and ORG with 63 kg ha(-1) yr(-1) and highest in CA (163 kg ha(-1) yr(-1)). CA and ORG received high amounts of N derived from biological fixation from alfalfa. The annual SON storage rates markedly differed between CA (55 kg ha(-1) yr(-1)) and both CON and LI (13 and 6 kg ha(-1) yr(-1)), with intermed iary value in ORG (30 kg ha(-1) yr(-1)). N leaching, calculated using soil mineral N measurements, reached an average of 21 kg ha(-1) yr(-1) and did not significantly differ between treatments, The gaseous N emissions (volatilization + denitrification), calculated as the difference between N surplus, SON storage and N leaching, ranged from 12 kg ha(-1) yr(-1) in ORG to 83 kg ha(-1) yr(-1) in CA. N2O emissions were continuously monitored with automatic chambers during 40 months. They varied from 1.20 kg ha(-1) yr(-1) in LI to 4.09 kg ha(-1) yr(-1) in CA system and were highly correlated with calculated gaseous N emissions. The GHG balance, calculated using SOC and N2O measurements, varied widely between systems: it was highest in CON and LI, with 2198 and 1763 kg CO2eq ha(-1) yr(-1) respectively. In CA, the GHG balance was much more favourable (306 kg CO2eq ha(-1) yr(-1)), despite important N2O losses which partly offset the benefit of SOC storage. ORG was the system with the smallest GHG balance (-65 kg CO2eq ha(-1) yr(-1)), acting a! s a CO2 sink in the long-term. Similar trends were observed when GHG was expressed per unit of N input or N exported. The N surplus alone was not a good indicator of the N fate in the four agricultural systems. Complementary predictors of N losses and GHG balance are required to obtain a true overview of the C and N environmental impacts of cropping systems. On an operational point of view, these results should lead to investigate the variability of the GHG emissions within each cropping system.

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