| 1. |
- Adler, Karl, et al.
(författare)
-
Digital soil mapping of copper in Sweden: Using the prediction and uncertainty as decision support in crop micronutrient management
- 2022
-
Ingår i: Geoderma Regional. - : Elsevier BV. - 2352-0094. ; 30
-
Tidskriftsartikel (refereegranskat)abstract
- Digital soil mapping (DSM) of topsoil copper (Cu) concentrations and prediction intervals covering 90% of agricultural land in Sweden was performed, in order to identify areas at risk of Cu deficiency. A total of 12,527 soil samples were used to calibrate the DSM model, using airborne gamma radiation data, climate data, topographical data and soil texture class data. Among the samples included, 11,093 had no laboratory-analysed Cu concentrations, so their Cu concentrations were predicted using portable X-ray fluorescence (PXRF) measurements. Cross-validation of the PXRF model resulted in Nash-Sutcliffe model efficiency coefficient (E) of 0.66 and mean absolute error (MAE) of 3.3 mg kg−1. Cross-validation of the DSM model showed somewhat lower performance (E = 0.57, MAE = 4.1 mg kg−1). Based on the lower bound of the prediction interval (5th percentile), 48% of agricultural soils in Sweden are most likely not at risk of Cu deficiency (>7 mg kg−1). The Cu map was also validated against concentrations in soil samples from five fields (25–47 ha in size; four samples per ha). The field means were predicted with a MAE of 1.0 mg kg−1 and within-field variation was reproduced with a field-wise squared Pearson correlation coefficient (r2) of 0–0.36. The classification metric ‘recall’ showed that the map of soil Cu concentrations might not predict all possible areas at risk of being Cu deficient, as observational data indicates that about 22% of soils in the mapped area should have Cu concentrations below the risk limit. However, the metric ‘precision’ showed that when the soil map predicted a concentration at or below 7 mg kg−1, it was generally correct. Increasing the limit resulted in the recall and precision increasing rapidly. The remaining 52% of agricultural soils at risk of being below the Cu concentration limit can be targeted by laboratory analysis or monitoring.
|
|
| 2. |
- Bölenius, Elisabeth, et al.
(författare)
-
Within field cereal yield variability as affected by soil physical properties and weather variations - A case study in east central Sweden
- 2017
-
Ingår i: Geoderma Regional. - : Elsevier BV. - 2352-0094. ; 11, s. 96-103
-
Tidskriftsartikel (refereegranskat)abstract
- Yield variations within fields can be substantial and soil physical properties are important as explanatory factors. However, correlations between yield and soil physical properties change between years, mainly depending on weather conditions. This study examined yield variations within a field and the explanatory power of interactions with soil physical factors. It also examined whether soil penetration resistance measurements can indicate areas where soil physical properties are potentially yield-limiting. Field measurements and soil sampling were carried out at 20 locations spread across a 7.5 ha area on a Eutric Cambisol within a 28 ha field at Kvarnbo farm in Uppsala, Sweden (59 degrees 50'N, 17 degrees 32'E). Yield was monitored in 1996-2000 and 2004. Soil sampling was performed in spring 2004 for measurement of soil texture, organic matter content, saturated hydraulic conductivity, bulk density and water-holding capacity at two matric tensions, 0.5 kPa and 10 kPa. Penetration resistance was measured on three separate occasions in 2004 and 2005, to cover any changes within and between seasons. "Simple" regression and principal component analysis (PCA) was used to test for significant differences in the data. Texture proved to be the main factor explaining the overall variation between sampling points, but penetration resistance was the most influential factor for yield variations. Yield in 2000 differed from that in other years due to excess water in lower-lying parts of the field (r=-0.70 between yield in 2000 and water-holding capacity in the subsoil, compared with r=0.6 in dry years). Since penetration resistance was correlated to several other measured soil properties it could be suitable as a screening tool to identify areas with poorer soil physical status for further investigations. Soil physical properties and their effects on yield were highly dependent on the weather. In high-yielding years, when water was not the limiting factor, soil physical status mattered less.
|
|
| 3. |
- Delavar, Mohammad Amir, et al.
(författare)
-
Soil salinity mapping by remote sensing south of Urmia Lake, Iran
- 2020
-
Ingår i: Geoderma Regional. - : Elsevier. - 2352-0094. ; 22
-
Tidskriftsartikel (refereegranskat)abstract
- Urmia Lake is a shallow terminal Lake located in northwest Iran and it is one of the largest permanent Lakes in the Middle East. In this study, the changes in soil salinity at Urmia Lake were investigated using satellite images and the oldest salinity map of the area over a period of 45 years from 1973 to 2018. The distribution of salinity in 2018 was estimated using the supervised classification by the nonlinear hybrid model of artificial multi-layered neural network-genetic algorithm model (ANN-GA) while the salinity map for the years of 1985, 1995, 2005 and 2015 was estimated by the unsupervised method. Further, the salinity data of surface soil in the region for the year 1973 was also digitized and utilized. For this purpose, 291 surface samples (258 samples for modeling and 33 samples for the re-evaluation of the model) of the studied region were collected and analyzed in 2018. The input neurons were selected by analyzing the satellite imagery bands, salinity indices, salinity ratio index and normalized difference vegetation index. The correlation coefficient and root-mean-square error of the training network model were equal to 0.94 and 0.04, respectively. The salinity map of the studied region was estimated using this model and classified into six classes (S0 to S5). The produced map of 2018 was used to re-evaluate the results. It showed that lower estimation accuracy was in classes S1 and S2. The obtained results in this study indicated that roughness, moisture, the density of halophyte plants and sodium slickspot were some of the sources for estimation of errors in lower salinity classes. The time-series changes in the salinity class of estimated maps showed that S3, S4 and S5 classes have expanded between 1973 and 2018. These are in agreement with the field observation and with the other scientific reports about the studied area.
|
|
| 4. |
- Eriksson, Jan, et al.
(författare)
-
Spatial patterns of essential trace element concentrations in Swedish soils and crops
- 2017
-
Ingår i: Geoderma Regional. - : Elsevier BV. - 2352-0094. ; 10, s. 163-174
-
Tidskriftsartikel (refereegranskat)abstract
- Trace element (TE) concentrations in topsoil of Swedish arable soils and grain of winter wheat, spring barley and oats are regularly monitored. Data on Co, Cr, Cu, Mn, Mo, Ni and Zn were analysed in this study, in order to determine spatial patterns of geographical variation in concentrations and their correlations with soil parent material and bedrock geology, and to identify areas with possible TE deficiency or excess with regard to crop and livestock production and product quality. The results showed that pseudo-total (7 M HNO3extraction) concentrations of Co, Cr, Cu, Ni and Zn were elevated in heavy clay soils. Areas influenced by sedimentary rock containing alum shale clearly showed elevated concentrations of various TEs, but otherwise it was difficult to find a clear correlation between soil TE concentration and bedrock geology. This may be because in the recently glaciated Swedish landscape, the ice sheet itself and the melt water from the declining ice sheet have transported soil material over large distances and/or because of low sampling density in many parts of the country. Despite weak correlations for individual elements, there was a general correlation between concentration in soil and concentration in cereal grain for many of the elements studied. One exception was Mn, for which pH was much more important than the concentration in soil. However, there was large variation in TE concentrations within short distances, indicating that soils with high and low concentrations can exist side by side. Nevertheless, for most TE, the risk of low concentrations in crop plants appeared to be greatest on coarse-textured soils on felsic rock and on soils on sedimentary rock (other than alum shale) in southern Sweden. While soils in this region generally have lower concentrations of Co, Cr, Cu, Mn, Ni and Zn than soils in most of western and central Europe, it was difficult to find documented deficiency of elements other than Cu and Mn among those that are essential to plants. Comparing the data on cereal grain presented on this study with suggested critical values indicates possible Cu and Ni deficiency. For the cationic TEs, the generally lower pH in arable soils in Sweden may be one explanation for the modest deficiency problems observed despite rather low soil concentrations. No excessive TE concentrations in crops were recorded, but on clayey soils in eastern Sweden the concentrations were higher than the national average.
|
|
| 5. |
- Gharahi Ghehi, N., et al.
(författare)
-
N2O and NO emission from the Nyungwe tropical highland rainforest in Rwanda
- 2014
-
Ingår i: Geoderma Regional. - 2352-0094. ; 2-3, s. 41-49
-
Tidskriftsartikel (refereegranskat)abstract
- Tropical forest soils are a significant source for N2O and NO. Current estimates of N2O and NO emissions are uncertain due to the limited number of fieldmeasurements and model input data. Furthermore, considerable spatial and temporal variability exists due to variation of soil properties, vegetation characteristics and meteorology.We used a process-based model (ForestDNDC-tropica) to estimate N2O and NO emissions from the entire (970 km2) tropical highland forest (Nyungwe) in southwestern Rwanda. Scaling these results to that regional level using legacy soil, meteorological and simulated vegetation data we found in most cases agreement between N2O and NO measurements and model predictions. Limited agreement was found for acid soils with high clay content and reduced metals, indicating that abiotic N2O and NO forming processes in acidic soils might be under-represented in the current ForestDNDC-tropica model. The Nyungwe forest was estimated to emit 439 t N2O-N year−1 (2.8– 5.5 kg N2O-N ha−1 year−1) and 244 t NO-N year−1 (0.8–5.1 kg N ha−1 year−1), corroborating previous studies in tropical forests and highlighting that also tropical highland rainforest soils are a major source of atmospheric N2O and NO. The uncertainty for the N2O and NO emission estimates was 153 and 50 t N2O-N year−1 and 36 and 16 t NO-N year−1 considering uncertainty in model input data and annual variability, respectively. The results showed that soil bulk density and pH were the most influential factors driving spatial variation and model uncertainty. To improve global model-based estimates of N2O and NO emission from tropical forest focus should therefore also be oriented in delivering more detailed soil and vegetation data.
|
|
| 6. |
- Hounkpatin, Ozias
(författare)
-
Assessment of the soil fertility status in Benin (West Africa) – Digital soil mapping using machine learning
- 2022
-
Ingår i: Geoderma Regional. - : Elsevier BV. - 2352-0094. ; 28
-
Tidskriftsartikel (refereegranskat)abstract
- A soil fertility index map (SFIm) can provide key information to decision-makers in regard to spatial planning in the context of sustainable land management. The establishment of such SFIm requires basic soil properties that can be modelled for spatial mapping. The objective of this study was to take advantage of Benin soil legacy data to produce a digital SFIm at a national level based on 8 soil properties (soil organic matter, nitrogen, pH (water), exchangeable potassium, assimilable phosphorus, sum of bases, cation exchange capacity and base saturation). Specific research aims were (1) to model and develop digital soil maps, (2) to identify the key covariates influencing soil nutrients, and (3) to build an SFIm using digital maps of the soil properties. For each soil property, modelling procedures involved the use of different covariates, including soil type, topographic, bioclimatic and spectral data, along with the comparative assessment of the cubist (CB) and quantile random forest (QRF) models. Models were evaluated not only on the basis of classical error metrics (RMSE, R2) but also on the ability to predict local uncertainty based on the prediction interval coverage probability (PICP). The results revealed that CB performed marginally better than the QRF based on classical error metrics (R2, RMSE) but produced the worst uncertainty with an overestimation of the local uncertainty. This suggested that the use of accuracy plots such as PICP to evaluate models can identify accuracy problems not evident with classical error metrics. The analysis revealed that the distance to the nearest stream, which was part of topographic covariates, had strong predictive ability for all the soil properties along with the bioclimatic variables. The spatial distribution of the different classes of SFIm showed a preponderance of low fertility levels with severe limitations for crop development. A limited number of high and average fertility level soils were found in the low elevation areas of southern Benin, and policy could advocate for their sole use for agricultural purposes and promote sustainable management practices.
|
|
| 7. |
- Muoni, Tarirai, et al.
(författare)
-
Critical slope length for soil loss mitigation in maize-bean cropping systems in SW Kenya
- 2020
-
Ingår i: Geoderma. - : Elsevier BV. - 0016-7061 .- 1872-6259. ; 22
-
Tidskriftsartikel (refereegranskat)abstract
- Soil erosion and land fragmentation threaten agricultural production of sub-Saharan African highlands. At our study site in Western Kenya, farm size is mostly < 2 ha, laid out in narrow strips in slope direction and ploughed downhill. Soil conservation measures like hedgerows and green manures can reduce effective slope length for erosion, but compete with crops for space and labour. Knowledge of critical slope length can minimise interventions and trade-offs. Hence, a maize-bean intercrop (MzBn) slope length trial on 20, 60 and 84 m long plots, replicated twice on three farms was carried out in Rongo, Migori County, during one rainy season. Soil loss from 84 m slope length (SL) plots was 250 % higher than from 60 m and 710% higher than from 20 m plots, while soil loss from 20 and 60 m plots did not differ (p < 0.05). Conversely, runoff was lower on the 84 m than on the 60 m (p < 0.05) or the 20 m SL (p < 0.05). Across all three farms slope gradient and length had highest explanatory power to predict soil loss. At individual farm level, under similar slope and soil texture, slope length and profile curvature were most influential. Regarding results of the slope length experiments, food crop plot lengths < 50 m appear essential considering soil loss, sediment load, and soil loss to yield ratio under the given rainfall, soil and slope (10-14%) conditions. Our results call for designing integrating slope length options and cropping systems for effective soil conservation. We recommend planting Mucuna and Calliandra-hedgerows as buffer strips below the critical slope length, and legume cash crops and maize uphill. Such approaches are critical against the backdrop of land fragmentation and labour limitation to sustainably maximise food production from the available land area in the region. (c) 2020 Elsevier B.V. All rights reserved.
|
|
| 8. |
- Norberg, Lisbet, et al.
(författare)
-
Seasonal CO2 emission under different cropping systems on Histosols in southern Sweden
- 2016
-
Ingår i: Geoderma Regional. - : Elsevier BV. - 2352-0094. ; 7, s. 338-345
-
Tidskriftsartikel (refereegranskat)abstract
- Drained and cultivated organic soils contribute a substantial proportion of estimated anthropogenic greenhouse gas emissions in Sweden. According to rough estimates, different cropping systems give rise to different subsidence rates and, since some of this subsidence originates from oxidation of organic material, soil respiration may also vary with different crops. This field study investigated the possibility of mitigating carbon dioxide (CO2) emissions from cultivated organic soils by using a specific cropping system. The CO2 emission rates from soils under different crops in similar environmental conditions were measured at 11 field sites in southern Sweden representing different types of organic soils. The variation in emissions between the crops tested was low compared with total CO2 emissions from the soil and differences between crops were not consistent. This shows that growing a particular crop cannot be recommended as a mitigation option for limiting CO2 emissions from cultivated organic soils. (c) 2016 Elsevier B.V. All rights reserved.
|
|
| 9. |
|
|
| 10. |
- Poeplau, Christopher, et al.
(författare)
-
Effect of perennial ryegrass cover crop on soil organic carbon stocks in southern Sweden
- 2015
-
Ingår i: Geoderma Regional. - : Elsevier BV. - 2352-0094. ; 4, s. 126-133
-
Tidskriftsartikel (refereegranskat)abstract
- Soil organic carbon (SOC) is an important ecosystem property and a potential sink for atmospheric CO2. Many agricultural soils are depleted in SOC and thus have the need and potential to sequester carbon. Cover crops used to prevent nitrate leaching in agroecosystems might be an additional cost-effective and multi-beneficial carbon input, but little is known about their effect on SOC stocks. This study examined the effect of an ryegrass cover crop on SOC stocks in three Swedish long-term experiments (16–24years) and compared it with that at a North American site (Sultan, Washington). Growth was temperature- and light-limited in Sweden and thus the ryegrass was undersown, while it was sown after harvest of the main crop at the Sultan site. In total, seven pairs of cover crop/no cover crop treatments were investigated. The introductory carbon balance model (ICBM) was used to calculate humification coefficients for ryegrass at each site as a measure of carbon sequestration efficiency. Mean aboveground biomass of ryegrass ranged from 550–1050kgDMha−1yr−1in the Swedish experiments and was 4650kgDMha−1yr−1at the Sultan site. Yield of the main crop was not significantly affected by the cover crop. Cover crop incorporation increased SOC stocks, with a significant mean carbon sequestration rate (0.32±0.28MgCha−1yr−1) at the Sultan site and all Swedish sites except one. Mean humification coefficient of the ryegrass cover crop was 0.33±0.27, which is comparable to that of highly efficient organic amendments such as farmyard manure and sewage sludge. This was attributed to high belowground productivity of ryegrass, although that was the most uncertain model input variable. A ryegrass cover crop is thus an effective, multi-beneficial measure to increase SOC stocks, even when undersown at northerly latitudes (55–58°N).
|
|
