Natural Vegetation Land Research Articles

Responsiveness of market equilibrium agricultural output, price and land use to shocks

AbstractWe assess the responsiveness of market equilibrium agricultural output, price and land use to shocks in agricultural demand, land yield and arable land area and the role of road infrastructure policy in offsetting them. We adapt a partial equilibrium model in the agricultural composite good and lands markets to guide the specification and estimation of a simultaneous equation model (SEM) for agricultural demand, land yield and acreage, and calculate market equilibrium responsiveness. We estimate the SEM by the generalised method of moments three‐stage least squares (GMM 3SLS) using a panel data set of the 10 biggest agricultural producer states in Brazil from 2001 to 2017. Using demand, land yield and acreage price elasticity estimates, we find that Brazil may expand equilibrium agricultural output while preserving its native vegetation land and dampening long‐term agricultural price escalation under a scenario of increasing worldwide demand for food, fibre and fuel and adverse climate shocks. Using acreage and land yield freight rate elasticity estimates, we show how shocks may be offset by road infrastructure policies that reduce freight rates to specific destination states, as they may be designed to induce less equilibrium land use for the same equilibrium output or raise equilibrium output with less equilibrium land use.

To what extent are ecosystem services provided by geodiversity affected by anthropogenic impacts? A quantitative study in Caraguatatuba, Southeast coast of Brazil

Ecosystem services (ES) provided by geodiversity are goods that directly and indirectly benefit society and can be classified into regulating, supporting, provisioning, cultural, and knowledge functions. The integrated assessment of geodiversity with an emphasis on ES is relevant for conservation and territorial management strategies. The current work aims the identification and assessment of impacts on ES provided by geodiversity in the Caraguatatuba county, with an emphasis in the Serra do Mar State Park (SMSP), on the Southeast coast of Brazil. The methodological procedures followed two steps: (i) identification of the ES based on the recognition of the Essential Geodiversity Variables (EGVs) and bibliographic research and (ii) quantitative assessment of the impacts on the ES provided by geodiversity based on land use categories. Seventy-five ES provided by geodiversity were identified in Caraguatatuba, being the ecosystem functions affected by urban area and native vegetation land use categories, respectively: supporting (50.9%), regulating (47.7%), cultural (41.9%), knowledge (34.9%), and provisioning (31.2%). The results indicate that the supporting and regulating functions, such as aquifers, fauna and flora habitats, and carbon sequestration and storage, are the ones that require the most effective environmental impact mitigation measures. This approach can contribute not only to academic works, but to different economic sectors to achieve sustainable development.

ASSESSMENT OF WETLAND DEGRADATION CONDITION AND TREND BASED ON LAND USE/COVER IN WAMI-RUVU RIVER BASIN USING MULTI-TEMPORAL LANDSAT IMAGES

The understanding of wetlands’ distribution and their level of susceptibility is important to enhance management and conservation efforts. The study aimed to map wetlands and assess their distribution pattern and their degradation based on the LULC by the years 2000, 2010 and 2020. Wetland types i.e., marshes, ponds, lakes, fens, rivers, floodplains, swamps, and open water bodies with other land use such as agriculture land, built-up and natural vegetation land were classified and mapped using random forest algorithm in Arc Map. Multi-temporal Landsat satellite data including thematic Mapper Landsat (+ETM) and Operational Land Imager (OLI) images were used for LULC mapping. The random forest classifier technique is used to analyse the satellite imagery for detecting the LULC changes during the whole study period. To assess the wetland area degradation three aspects were used in this study for the analysis; wetland area change rate, annual land cover change and annual land cover change rate. The study found about -34.41Km2/y of wetlands potentially are degraded annually due to human and natural stressors in 20 years of our study however the basin experienced a higher rate of wetland degradation in the second epoch of 2010-2020 where the basin experience -42.8Km2/y degradation which results to the total loss of -687.75 km2 total coverage of wetland area in the basin. This information could be used to improve wetland planning and management by wetland managers and other stakeholders.

Cambios recientes en la estructura paisajística del humedal de batuco, Chile Central

In spite of the copious regulations created in the last years to protect the Batuco wetland, located in Lampa county; at the northeast of the Metropolitan Region, Chile, this ecosystem has not stopped suffering a significant degradation, expressed by the modification of its landscape. In this study we evaluated the temporal change experienced in the last decades by the landscape structure of that wetland as a result of such degradation. To do this, we calculated a set of landscape metrics over their main land use/land covers; interpreted and mapped from an aerial photograph acquired in 2005 and a satellite image acquired in 2021, in order to allow us to measure the magnitude of its temporary variations. The doubling of the urban area within the period of interest was manifested by their continuous and regular sprawl over mainly two natural vegetation land covers of the wetland: wet brackish meadows and open thorn scrublands. Both have great ecological significance for the ecosystem under consideration, being reduced to patches with smaller core area; clear evidence of a fragmentation process confirming the degradation propitiated by the recent anthropic occupation of the wetland’s soils. Through this research it is expect to provide to the scientific community and the competent government agencies, quantitative data contributing to diagnose the degradation of the wetland in question, so that they can more efficiently guide monitoring and management actions for their conservation and restoration.

Dynamics of soil aggregate‐associated carbon as influenced by simulated tillage and runoff

AbstractTillage practices and water erosion are the most important anthropogenic and natural processes, respectively, driving soil organic C turnover in agricultural land. The aim of this study was to explore the responses of soil organic C (SOC) turnover to tillage and runoff by comparing the variation of soil aggregate‐associated organic C (AOC) and intra‐aggregate particulate organic C (iPOC) under simulated tillage and runoff conditions. Soil samples were collected from a native vegetation land with no cultivation history in the Mollisol region of Northeast China. After a series of simulated tillage (ST) and simulated runoff (SR) treatments, the samples were incubated for 30 d and then separated through 2‐, 1‐, 0.25‐, and 0.053‐mm sieves by wet‐sieving to obtain different aggregate size fractions. Each aggregate fraction was subsequently shaken for 18 h in 0.5% hexametaphosphate to get different intra‐aggregate particle size fractions. The proportion of the fractions and their AOC and iPOC were determined. The ST treatment promoted the reaggregation of macroaggregates (>2 mm) by accelerating the turnover of their coarse iPOC (0.25–2 mm), leading to a lower concentration of AOC. Runoff transformed larger aggregates (>0.25 mm) to smaller particles (<0.25 mm) without catalyzing C turnover. Fine iPOC (0.053–0.25 mm) could serve as an indicator for AOC (>1 mm) dynamics, especially associated with tillage operations. Our findings highlight the different influences of tillage and runoff, and the negative effect of tillage on SOC dynamics.

Modeling Conditions Appropriate for Wildfire in South East China – A Machine Learning Approach

Wildfire is one of the most common natural hazards in the world. Fire risk estimation for the purposes of risk reduction is an important aspect in disaster studies around the world. The aim of this research was to develop a machine learning workflow process for South East China to monitor fire risks over a large region by learning from a grid file database containing a time series of several of the important environmental parameters largely extracted from remote sensing data products, and highlight areas as fire risk or non-fire risk over a couple of weeks in the future. The study employed fire threshold and the transductive PU learning method to identify reliable non-fire/negative training samples from the grid file database using fire/positive training samples, labeled using the MODIS MCD14ML fire location product. Different models were trained for the three natural vegetation land covers, namely evergreen broadleaf forest, mixed forest, and woody savannas in the study area. On the test dataset, the three models exhibited high sensitivity (>80%) by identifying the majority of fires in the test dataset for all land covers. The use of the reliable negatives identified though the fire threshold and PU learning process resulted in low precision and accuracy. During the model verification process, the model for the mixed forest land cover performed the best with 70% of verification fires falling within the classified fire zone. It was found that the better representation of mixed forest in the training samples made this model perform more reliably as compared to others. Improving the individual models constructed for different land covers and combining them can provide fire classification for a larger region. There is room to improve the spatial precision of fire cell classification. Introducing finer scale features that have higher correlation with fire activity and exhibit high spatial variability seems a viable way forward.

A Multivariate and Spatiotemporal Analysis of Water Quality in Code River, Indonesia.

The efficacy of a water quality management strategy highly depends on the analysis of water quality data, which must be intensively analyzed from both spatial and temporal perspectives. This study aims to analyze spatial and temporal trends in water quality in Code River in Indonesia and correlate these with land use and land cover changes over a particular period. Water quality data consisting of 15 parameters and Landsat image data taken from 2011 to 2017 were collected and analyzed. We found that the concentrations of total dissolved solid, nitrite, nitrate, and zinc had increasing trends from upstream to downstream over time, whereas concentrations of parameter biological oxygen demand, cuprum, and fecal coliform consistently undermined water quality standards. This study also found that the proportion of natural vegetation land cover had a positive correlation with the quality of Code River's water, whereas agricultural land and built-up areas were the most sensitive to water pollution in the river. Moreover, the principal component analysis of water quality data suggested that organic matter, metals, and domestic wastewater were the most important factors for explaining the total variability of water quality in Code River. This study demonstrates the application of a GIS-based multivariate analysis to the interpretation of water quality monitoring data, which could aid watershed stakeholders in developing data-driven intervention strategies for improving the water quality in rivers and streams.

The Grain for Green Project May Enrich the Mercury Concentration in a Small Karst Catchment, Southwest China

The Chinese project, better known as the Grain for Green Project (GGP), has changed the land-use type in the karst area of Puding county, Guizhou province, southwest China, and this study is aimed at evaluating the Hg distribution and determining factors in soils after the land-use change. A total of ten soil profiles were selected in the typical karst region, and the land-use types were divided into native vegetation land (NVL), farmland (FL), and abandoned farmland (AFL). Total Hg concentration under different land-use types increased in the order: NVL (average 63.26 μg∙kg−1) < FL (average 71.48 μg∙kg−1) < AFL (average 98.22 μg∙kg−1). After agricultural abandonment for four to five years with a cover of native vegetation in the AFL, a higher concentration of Hg compared to the other two land-use types indicate that the Hg accumulation in soil results from vegetation restoration of AFL due to land-use change. Soil organic carbon (SOC) and macro-aggregates were highly correlated to Hg concentration in this study. Macro-aggregates can provide a stable condition for Hg due to the thin regolith and high porosity in the karst region. A high proportion of macro-aggregates can reduce the mobility of Hg in the karst area. Intense tillage can significantly reduce the formation of macro-aggregates in FL, but the macro-aggregates in AFL were recovered as well as those in NVL, resulting in the accumulation of Hg.

Assessing soil degradation under land-use change: insight from soil erosion and soil aggregate stability in a small karst catchment in southwest China.

BackgroundSoil erodibility (K factor) and soil aggregate stability are often used to assess soil degradation in an erodible environment. However, their applicability under land-use change is uncertain, especially agricultural abandonment.MethodsDifferent land-use types, including cropland, abandoned cropland, and native vegetation land, were converted into the successive stages following agricultural abandonment by space-for-time substitution approach in a small karst catchment, Southwest China. The indexes of soil aggregate stability and K factor of the Erosion Productivity Impact Calculator (EPIC) model in soil profiles were calculated to identify which method is suitable to indicate soil degradation under land-use change.ResultsThe indexes of soil aggregate stability in the soils at 0∼30 cm depth under native vegetation land were significantly larger than those under cropland and slightly larger than those under abandoned cropland. The K factor was not significantly different among the three land use examples because the EPIC model does not consider soil permeability. In the soil organic carbon (SOC)-rich soils (>2%), the K factor was significantly correlated with silt and clay content ranging within a narrow scope of near 0.010 t hm2 h/hm2/MJ/mm. While in the SOC-poor soils, the K factor was significantly increased with decreasing SOC content and was significantly correlated with soil aggregate stability.ConclusionsSoil aggregate stability is more suitable to indicate soil degradation under land-use change. Sufficient SOC in erodible soils would restrain soil degradation, while SOC loss can significantly increase soil erosion risk.

Effects of agricultural abandonment on soil aggregation, soil organic carbon storage and stabilization: Results from observation in a small karst catchment, Southwest China

Soil organic carbon (SOC) storage and stabilization under land-use change, including agricultural abandonment, are critical for the recuperation of soil productivity and feedback to climate change. A space-for-time substitution approach was applied to investigate the responses of soil aggregation, SOC storage and stabilization to agricultural abandonment in a small karst catchment in Southwest China. Soil aggregate distribution, SOC concentration and δ13C composition in bulk soils and different-sized aggregates in soil profiles under cropland, abandoned cropland and native vegetation land were determined. The results showed that SOC storage and soil aggregation were significantly reduced in the surface soils of croplands compared to those under native vegetation; SOC storage was slowly restored in 3–8 years abandoned cropland, but soil aggregation was rapidly recovered. The rapidly recovered macro-aggregates controlled the recuperation of SOC storage after agricultural abandonment because most SOC (64%–83%) was sequestrated by macro-aggregates. The relationships between SOC concentrations and δ13C values in different-sized aggregates of surface soils could indicate a change in SOC stabilization under land-use change. In this study, SOC stabilization was gradually enhanced following agricultural abandonment. These results suggest that soil aggregation, SOC storage and stabilization are recovered following agricultural abandonment in the karst region.

Effects of Soil Aggregate Stability on Soil Organic Carbon and Nitrogen under Land Use Change in an Erodible Region in Southwest China.

Soil aggregate stability can indicate soil quality, and affects soil organic carbon (SOC) and soil organic nitrogen (SON) sequestration. However, for erodible soils, the effects of soil aggregate stability on SOC and SON under land use change are not well known. In this study, soil aggregate distribution, SOC and SON content, soil aggregate stability, and soil erodibility were determined in the soils at different depths along the stages following agricultural abandonment, including cropland, abandoned cropland, and native vegetation land in an erodible region of Southwest China. Soil aggregation, soil aggregate stability, and SOC and SON content in the 0–20 cm depth soils increased after agricultural abandonment, but soil texture and soil erodibility were not affected by land use change. Soil erodibility remained in a low level when SOC contents were over 20 g·kg−1, and it significantly increased with the loss of soil organic matter (SOM). The SOC and SON contents increased with soil aggregate stability. This study suggests that rapidly recovered soil aggregate stability after agricultural abandonment promotes SOM sequestration, whereas sufficient SOM can effectively maintain soil quality in karst ecological restoration.

Assessing Naturalness Changes Resulting from a Historical Land Use in Brazil South Region: An Analysis of the 1986-2016 Period

The effects of land use and cover changes and the application of the Urbanity Index were analyzed to identify critical or non-critical naturalness scenery in the Northern Region of Rio Grande do Sul (Brazil), over a period of 30 years. Between 1986 and 2016, the main significant land use change was the reduction of the agricultural anthropic and the increase of the natural vegetation land use areas. About 90% - 80% of the total study areas were characterized by anthropic pattern features, with a predominantly agricultural matrix. The conversion of agricultural anthropic into natural areas resulted in increased naturalness landscape and a gain in the stock of natural capital. The increase in the natural vegetation area, mainly to the north and east of the region, set in a steep relief, became remarkable after 1990. The Urbanity Index values evidenced a highest naturalness condition (natural vegetation areas) to the northern and eastern, while a smaller naturalness condition (agricultural and non-agricultural areas) to the southern and western and central of the Northern Region of Rio Grande do Sul. These changes are related to a non-impaired (northern and eastern) and a impaired scenery (southern, western and central portion) of the ecological sustainability of the Northern Region of Rio Grande do Sul, after a 30-year period (1986-2016). These results pointed out that land use transitions resulted in a consolidated farming scenario in which agricultural intensification coincided with the reduction of farming area and increased naturalness as a reverse trend to the agricultural frontier dynamics.

The Effects of Land use Change on the Some Soil Properties in Gbonyin Local Government Area of Ekiti State, Nigeria

The aim of this research is to examine the response of some soil properties to the changes in land cover/land use in Gbonyin Local Government Area of Ekiti State, Nigeria. Land use changes as a result of human activities have been identified as one of the greatest pressures to soil and forest resources. The change from natural vegetation land use to built-up and agricultural land uses is becoming rampant in Gbonyin Local Government Area of Ekiti State, Nigeria. The objective of this study was to examine the effects of land use change on the some soil properties. Two major land use types which include forest lands and residential lands uses were explored. Soil samples were collected at the depth of 0 on 30cm through the use of soil auger from ten different locations in each of the two land use types in the study area making twenty soil samples. The use of t-test statistical tool was implored on the laboratory results in order to test for the differences between the soil in forest and residential land use types. Results revealed that the soil physico-chemical properties differed significantly between the sites. Chemical properties of the soil were found to be generally low in residential land use while they were high in vegetation land use. Bulk density was high in residential land use while it was low in forest land use.

Integrating management information with soil quality dynamics to monitor agricultural productivity

Sustainably utilizing global resources is critical for ensuring soil security which is pertinent for biomass production, climate change mitigation, environmental quality, biodiversity conservation and thus human wellbeing. A plethora of soil quality assessment metrics encapsulated in different concepts exist, with each typically biased towards identifying the interrelationship between agricultural production and specific physical, chemical or biological soil attributes. Because of diversity in soil classifications and crop requirements, considerable variation exist between these metrics making it difficult for end-users to select a suitable method. Here, Partial Least Squares Regression (PLSR) method is used to integrate the physical and chemical soil properties into a Soil Quality Index (SQI) which is then used to evaluate soil quality dynamics vis-à-vis crop yields over two growing seasons. Field data was acquired from 5 sites under No-Till (NT), Conventional Till (CT) management and Natural Vegetation (NV) land use. This SQI was computed under the hypothesis that site specific soil physico–chemical attributes depended on soil type, management, and depth. Under CT management Pw (Pewamo silty clay loam) had the highest soil quality; KbA (Kibbie fine sandy loam) soils had higher quality under NT management; whereas CtA (Crosby Celina silt loams) had relatively higher quality under NV land use. Soil bulk density (ρb), Soil Organic Carbon (SOC), Available Water Content (AWC) and Electrical Conductivity (EC) were the significant soil parameters influencing soil quality. The correlation between SQI and corn (Zea mays) yields was 0.6, whereas SQI and Soybean (Glycine max (L.) Merr.) yield was 0.9. Future research will evaluate SQI dynamics vis-à-vis socio-economic indicators and key climate variables.

Quantifying the interactions of land management practices and agricultural productivity using a soil quality index

AbstractIt is desirable to develop an objective Soil Quality Index (SQI) to guide sustainable agronomic intensification, thereby promoting socio‐economic well‐being. This study pioneers the use of Ward's cluster and principal component regression methods to evaluate soil homogeneity and construct a SQI (expressed as %). Field data were acquired from five different sites within Ohio, USA, that were under no‐till (NT), conventional till (CT) management and natural vegetation (NV) land use. Soil pH, carbon/nitrogen (C/N) ratio, nitrate and soil organic carbon (SOC) concentrations were identified as primary drivers of soil quality. Based on Ward's cluster method, the soil properties of croplands were not significantly different from those under NV land use. However, SQI ranked surface soils under CT management as higher in quality than NV and NT managed soils, respectively. The coefficient of determination (R2) between SQI and corn (Zea mays L.) and soya bean [Glycine max (L.) Merr.] yields was 0.7 and 0.9, respectively, implying this SQI effectively relates soil properties, a function of anthropogenic land management practices, with crop yields. In future, time series analyses will be used to assess SQI versus crop yield dynamics, with key socio‐economic and climate variables.

English

Soil quality is a function of inherent and dynamic properties of soil which determines the sustainability of crop and animal production. Based on this fact, the study was aimed to investigate the effects of land use systems and management practices on soil physical and chemical quality indicators of Vertisol at Pawe district, Northwestern Ethiopia. The result revealed that most of the soil physical and chemical properties were significantly (p ≤ 0.05) affected by the land uses and respective management practices. The land uses and respective management practices were selected as the cultivated homestead land (CHL), cultivated research farm (CRF), cultivated fertilized land (CFL) and cultivated unfertilized land( CUL) and native vegetation land (NVL) as a control. The cultivated land with application of farm yard manure (FYM) at the homestead area had higher soil porosity, aggregate size, organic matter (OM), total and mineral nitrogen, available phosphorus (AvP), cation exchange capacity (CEC), exchangeable cations, and micronutrients than the native vegetation land. On the other hand, most of these soil physical and chemical properties found to be declined in the research farm, fertilized and unfertilized cultivated lands. Therefore, integrated use of chemical fertilizer, farmyard manure application and reduced tillage are important soil management practices for sustainable agricultural use of soil in the study area. Key words: Soil quality, vertisol, land use, cultivated land, management practices.

Gap analysis as a basis for strategic spatial planning of green infrastructure: a case study in the Ukrainian Carpathians

ABSTRACTIncreased demand for natural resources and economic transition threaten natural and biocultural capital and thus ecosystem services for human well-being. We applied an evidence-based approach to strategic planning of functional green infrastructure in a European biodiversity hotspot: the Ukrainian Carpathian Mountains. We (1) described how potential natural vegetation types have been transformed, (2) applied evidence-based critical thresholds for each potential natural vegetation land cover, (3) measured how much of the potential natural vegetation land covers are protected, and (4) estimated the area of cultural landscapes that emerged. While only 2% of lowland land cover types were left, 55% of mountain forests and 94% of alpine land covers remained. Many mountain forests were transformed to valuable cultural landscapes. Beech and oak forests covered 42% of the study area but at low levels of protection (<5%). The highest protection level (12–17%) was in mixed beech–fir–spruce and in spruce forests. However, taking connectivity into account, only alpine land covers formed a functional habitat network. More areas need to be protected and planned to build a functional green infrastructure. Traditional village systems with biocultural values need support. We discuss how strategic analyses can encourage collaborative spatial planning and international development cooperation.

Towards a standard technique for soil quality assessment

A soil quality index (SQI) that integrates key soil attribute information would be beneficial in minimizing spillover effects of indiscriminate soil management such as shortages in food, water, energy and abate adverse repercussions of climate change. In this study, a new SQI that synthesizes soil attributes is developed using partial least squares regression (PLSR), and compared with crop yields. The field data were acquired in the year 2013 from 5 different on-farm sites within Ohio, USA that were under Natural Vegetation (NV), No-Till (NT), and Conventional Till (CT) management. The data shows that Pw (Pewamo silty clay loam) soil under NV land use had a higher quality, than GWA (Glynwood silt loam), kbA (Kibbie fine sandy loam), CrA (Crosby silt loam), and CtA (Crosby Celina silt loams) soil; whereas CT managed soil had Pw>CrA>kbA>CtA>GWA. The soil bulk density (ρb), electrical conductivity (EC), available water capacity (AWC) and soil organic carbon (SOC) greatly influenced the SQI especially at the soil surface. The SQI and yield were highly correlated, with that for corn (Zea mays L.) being 64%; whereas soybean (Glycine max (L.) Merr.) was 100%. This finding is of special relevance because it explicates the interconnection between on-farm soil quality vis-à-vis crop yields by objectively blending soil attributes from different management scenarios and soil layers. Future research will investigate techniques for integrating this SQI with socio-economic indicators of agro-ecosystem sustainability.

Impacts of Land Use, Fertilizer and Manure Application on the Stream Nutrient Loadings in the Salmon River Watershed, South-Central British Columbia, Canada

Manure and fertilizer applications can increase soil productivity and land economic values, but the controversial result can be a decline of water quality due to the increased nutrient exports from soils to the streams. The impacts of landuse, manure and fertilizer application on nutrient exports from soils to the streams were analyzed using the SWAT (Soil Water Assessment Tool) model for the Salmon River watershed in south-central British Columbia, Canada. The results showed that the animal farms had the highest rates of nutrient exports from soils to the streams and the natural forested lands had the lowest. It was estimated that the whole Salmon River watershed would export approximately 11.52 t·yr-1 of organic nitrogen (ON), 8.05 t·yr-1 of nitrate nitrogen (NO3-N), 2.30 t·yr-1 of organic phosphorus (OP) and 1.36 t·yr-1 of soluble reactive phosphorus (SRP) if the whole watershed was covered by natural vegetation without human disturbance. Current landuse changes, by converting natural vegetation lands to agriculture and animal farms and associated manure and fertilizer applications, have in-creased approximately 53.30 t·yr-1 of ON, 9.68 t·yr-1 of NO3-N, 22.69 t·y-1 of OP and 6.23 t·y-1 of SRP exports to the streams in the whole watershed. The SWAT model predicted that a daily 100 kg·ha-1 of fresh manure deposit from grazing cows during grazing season from later spring to later fall could increase 2.57 kg·ha-1·yr-1 of ON, 0.39 kg·ha-1·yr-1 of NO3-N, 2.35 kg·ha-1·yr-1 of OP and 0.48 kg·ha-1·yr-1 of SRP export to the streams. Fertilization could increase 1.57 kg ha-1 yr-1 of ON and 4.02 kg·ha-1·yr-1 of NO3-N export to the streams if 100 kg·ha-1·yr-1 of nitrogen (NH4NO3) fertilizer was applied in spring. Also fertilization could increase 1.18 kg·ha-1·yr-1 of OP and 0.20 kg·ha-1·yr-1 of SRP export to the streams if 100 kg·ha-1 phosphorus (P2O5) fertilizer was applied in spring.