Interactions between landscape defined management zones and grazing management systems

2017 ◽  
Vol 8 (2) ◽  
pp. 787-791 ◽  
Author(s):  
E. M. Pena-Yewtukhiw ◽  
D. Mata-Padrino ◽  
J. H. Grove

Yield and landscape are commonly used to guide management zone delineation. However, production system choice and management can interact with landscape attributes and weather. The objective of this study was to evaluate forage yield and soil properties in three landscape defined (elevation based) management zones, and under two different grazing systems. Changes in soil properties (soil strength, bulk density, moisture, bioavailable nutrients) and forage productivity (biomass), as related to grazing management and management zone, were measured. Bulk density, moisture, and forage biomass were greater at higher elevation. Soil strength decreased as elevation increased, and was greater near-surface after winter grazing ended. The response of landscape delineated management zones varied with extreme weather conditions and treatment. Lower zones were more sensitive to weather extremes than higher elevations, directly affecting biomass accumulation. In conclusion, we observed interactions between the grazing treatments and the management zones.

2017 ◽  
Vol 60 (3) ◽  
pp. 683-692 ◽  
Author(s):  
Yongjin Cho ◽  
Kenneth A. Sudduth ◽  
Scott T. Drummond

Abstract. Combining data collected in-field from multiple soil sensors has the potential to improve the efficiency and accuracy of soil property estimates. Optical diffuse reflectance spectroscopy (DRS) has been used to estimate many important soil properties, such as soil carbon, water content, and texture. Other common soil sensors include penetrometers that measure soil strength and apparent electrical conductivity (ECa) sensors. Previous field research has related these sensor measurements to soil properties such as bulk density, water content, and texture. A commercial instrument that can simultaneously collect reflectance spectra, ECa, and soil strength data is now available. The objective of this research was to relate laboratory-measured soil properties, including bulk density (BD), total organic carbon (TOC), water content (WC), and texture fractions to sensor data from this instrument. At four field sites in mid-Missouri, profile sensor measurements were obtained to 0.9 m depth, followed by collection of soil cores at each site for laboratory measurements. Using only DRS data, BD, TOC, and WC were not well-estimated (R2 = 0.32, 0.67, and 0.40, respectively). Adding ECa and soil strength data provided only a slight improvement in WC estimation (R2 = 0.47) and little to no improvement in BD and TOC estimation. When data were analyzed separately by major land resource area (MLRA), fusion of data from all sensors improved soil texture fraction estimates. The largest improvement compared to reflectance alone was for MLRA 115B, where estimation errors for the various soil properties were reduced by approximately 14% to 26%. This study showed promise for in-field sensor measurement of some soil properties. Additional field data collection and model development are needed for those soil properties for which a combination of data from multiple sensors is required. Keywords: NIR spectroscopy, Precision agriculture, Reflectance spectra, Soil properties, Soil sensing.


2016 ◽  
Vol 51 (9) ◽  
pp. 1283-1294 ◽  
Author(s):  
Henrique Oldoni ◽  
Luís Henrique Bassoi

Abstract The objective of this work was to delineate irrigation management zones using geostatistics and multivariate analysis in different combinations of physical and hydraulic soil properties, as well as to determine the optimal number of management zones in order to avoid overlaping. A field experiment was carried out in a Quartzipsamment, for two years, in an irrigated orchard of table grape, in the Senador Nilo Coelho Irrigation Scheme, in the municipality of Petrolina, in the state of Pernanbuco, Brazil. Soil samples were collected for the determination of soil physico-hydraulic properties. A portable meter was used to measure soil apparent electrical conductivity. Spatial distribution maps were generated using ordinary kriging. Management zones for five different combinations of soil properties were defined using the fuzzy c-means clustering algorithm, and two indexes were applied to determine the optimal number of management zones. Two combinations of soil properties can be used in the management zone planning in order to monitor soil moisture.


2020 ◽  
Vol 3 (1) ◽  
pp. 106
Author(s):  
Yevhen Melnyk ◽  
Vladimir Voron

Preservation and increase of forest area are necessary conditions for the biosphere functioning. Forest ecosystems in most parts of the world are affected by fires. According to the latest data, the forest fire situation has become complicated in Ukraine, and this issue requires ongoing investigation. The aim of the study was to analyse the dynamics of wildfires in Ukrainian forests over recent decades and to assess the complex indicator of wildfire occurrence in various forest management zones and administrative regions. The average annual complex indicator of fire occurrence, in terms of wildfire number and burned area, was studied in detail in the forests of various administrative regions and forest management zones in Ukraine from 1998 to 2017. The results show that fire occurrence in both the number and area of fires can vary significantly in various forest management zones. There is a very noticeable difference in these indicators in some administrative regions within a particular forest management zone. The data show that the number of forest fires depends not only on the natural and climatic conditions of such regions, but also on anthropogenic factors.


2021 ◽  
Author(s):  
Richard Mommertz ◽  
Lars Konen ◽  
Martin Schodlok

<p>Soil is one of the world’s most important natural resources for human livelihood as it provides food and clean water. Therefore, its preservation is of huge importance. For this purpose, a proficient regional database on soil properties is needed. The project “ReCharBo” (Regional Characterisation of Soil Properties) has the objective to combine remote sensing, geophysical and pedological methods to determine soil characteristics on a regional scale. Its aim is to characterise soils non-invasive, time and cost efficient and with a minimal number of soil samples to calibrate the measurements. Konen et al. (2021) give detailed information on the research concept and first field results in a presentation in the session “SSS10.3 Digital Soil Mapping and Assessment”. Hyperspectral remote sensing is a powerful and well known technique to characterise near surface soil properties. Depending on the sensor technology and the data quality, a wide variety of soil properties can be derived with remotely sensed data (Chabrillat et al. 2019, Stenberg et al. 2010). The project aims to investigate the effects of up and downscaling, namely which detail of information is preserved on a regional scale and how a change in scales affects the analysis algorithms and the possibility to retrieve valid soil parameter information. Thus, e.g. laboratory and field spectroscopy are applied to gain information of samples and fieldspots, respectively. Various UAV-based sensors, e.g. thermal & hyperspectral sensors, are applied to study soil properties of arable land in different study areas at field scale. Finally, airborne (helicopter) hyperspectral data will cover the regional scale. Additionally forthcoming spaceborne hyperspectral satellite data (e.g. Prisma, EnMAP, Sentinel-CHIME) are a promising outlook to gain detailed regional soil information. In this context it will be discussed how the multisensor data acquisition is best managed to optimise soil parameter retrieval. Sensor specific properties regarding time and date of acquisition as well as weather/atmospheric conditions are outlined. The presentation addresses and discusses the impact of a multisensor and multiscale remote sensing data collection regarding the results on soil parameter retrieval.</p><p> </p><p>References</p><p>Chabrillat, S., Ben-Dor, E. Cierniewski, J., Gomez, C., Schmid, T. & van Wesemael, B. (2019): Imaging Spectroscopy for Soil Mapping and Monitoring. Surveys in Geophysics 40:361–399. https://doi.org/10.1007/s10712-019-09524-0</p><p>Stenberg, B., Viscarra Rossel, R. A., Mounem Mouazen, A. & Wetterlind, J. (2010): Visible and Near Infrared Spectroscopy in Soil Science. In: Donald L. Sparks (editor): Advances in Agronomy. Vol. 107. Academic Press:163-215. http://dx.doi.org/10.1016/S0065-2113(10)07005-7</p>


2021 ◽  
Author(s):  
Martín Senande-Rivera ◽  
Gonzalo Miguez-Macho

<p>Extreme wildfire events associated with strong pyroconvection have gained the attention of the scientific community and the society in recent years. Strong convection in the fire plume can influence fire behaviour, as downdrafts can cause abrupt variations in surface wind direction and speed that can result in bursts of unexpected fire propagation. Climate change is expected to increase the length of the fire season and the extreme wildfire potential, so the risk of pyroconvection occurence might be also altered. Here, we analyse atmospheric stability and near-surface fire weather conditions in the Iberian Peninsula at the end of the 21st century to assess the projected changes in pyroconvective risk during favourable weather conditions for wildfire spread.  </p>


2009 ◽  
Vol 9 (7) ◽  
pp. 2413-2418 ◽  
Author(s):  
N. David ◽  
P. Alpert ◽  
H. Messer

Abstract. We propose a new technique that overcomes the obstacles of the existing methods for monitoring near-surface water vapour, by estimating humidity from data collected through existing wireless communication networks. Weather conditions and atmospheric phenomena affect the electromagnetic channel, causing attenuations to the radio signals. Thus, wireless communication networks are in effect built-in environmental monitoring facilities. The wireless microwave links, used in these networks, are widely deployed by cellular providers for backhaul communication between base stations, a few tens of meters above ground level. As a result, if all available measurements are used, the proposed method can provide moisture observations with high spatial resolution and potentially high temporal resolution. Further, the implementation cost is minimal, since the data used are already collected and saved by the cellular operators. In addition – many of these links are installed in areas where access is difficult such as orographic terrain and complex topography. As such, our method enables measurements in places that have been hard to measure in the past, or have never been measured before. The technique is restricted to weather conditions which exclude rain, fog or clouds along the propagation path. Strong winds that may cause movement of the link transmitter or receiver (or both) may also interfere with the ability to conduct accurate measurements. We present results from real-data measurements taken from two microwave links used in a backhaul cellular network that show convincing correlation to surface station humidity measurements. The measurements were taken daily in two sites, one in northern Israel (28 measurements), the other in central Israel (29 measurements). The correlation between the microwave link measurements and the humidity gauges were 0.9 and 0.82 for the north and central sites, respectively. The Root Mean Square Differences (RMSD) were 1.8 g/m3 and 3.4 g/m3 for the northern and central site measurements, respectively.


2012 ◽  
Vol 29 (7) ◽  
pp. 933-943 ◽  
Author(s):  
Weinan Pan ◽  
R. P. Boyles ◽  
J. G. White ◽  
J. L. Heitman

Abstract Soil moisture has important implications for meteorology, climatology, hydrology, and agriculture. This has led to growing interest in development of in situ soil moisture monitoring networks. Measurement interpretation is severely limited without soil property data. In North Carolina, soil moisture has been monitored since 1999 as a routine parameter in the statewide Environment and Climate Observing Network (ECONet), but with little soils information available for ECONet sites. The objective of this paper is to provide soils data for ECONet development. The authors studied soil physical properties at 27 ECONet sites and generated a database with 13 soil physical parameters, including sand, silt, and clay contents; bulk density; total porosity; saturated hydraulic conductivity; air-dried water content; and water retention at six pressures. Soil properties were highly variable among individual ECONet sites [coefficients of variation (CVs) ranging from 12% to 80%]. This wide range of properties suggests very different behavior among sites with respect to soil moisture. A principal component analysis indicated parameter groupings associated primarily with soil texture, bulk density, and air-dried water content accounted for 80% of the total variance in the dataset. These results suggested that a few specific soil properties could be measured to provide an understanding of differences in sites with respect to major soil properties. The authors also illustrate how the measured soil properties have been used to develop new soil moisture products and data screening for the North Carolina ECONet. The methods, analysis, and results presented here have applications to North Carolina and for other regions with heterogeneous soils where soil moisture monitoring is valuable.


2002 ◽  
Vol 11 (4) ◽  
pp. 381-390
Author(s):  
A. TALKKARI ◽  
L. JAUHIAINEN ◽  
M. YLI-HALLA

In precision farming fields may be divided into management zones according to the spatial variation in soil properties. Clay content is an important soil characteristic, because it is associated with other soil properties that are important in management. Soil survey data from 150 sampling sites taken from an area of 218 ha were used to predict the spatial variation of clay percentage geostatistically in an agricultural soil in Jokioinen, Finland. The exponential and spherical models with a nugget component were fitted to the experimental variogram. This indicated that the medium-range pattern could be modelled, but the short-range variation could not, due to sparsity of sample points at short distances. The effect of sampling density on the kriging error was evaluated using the random simulation method. Kriging with a spherical model produced a map with smooth variation in clay percentage. The standard error of kriging estimates decreased only slightly when the density of samples was increased. The predictions were divided into three classes based on the clay percentage. Areas with clay content below 30%, between 30% and 60% and over 60% belong to non-clay, clay and heavy clay zones, respectively. With additional information from the soil samples on the contents of nutrients and organic matter these areas can serve as agricultural management zones.;


2016 ◽  
Vol 13 (1) ◽  
pp. 59-68
Author(s):  
Roshan M. Bajracharya ◽  
Him Lal Shrestha ◽  
Ramesh Shakya ◽  
Bishal K. Sitaula

Land management regimes and forest types play an important role in the productivity and accumulation of terrestrial carbon pools. While it is commonly accepted that forests enhance carbon sequestration and conventional agriculture causes carbon depletion, the effects of agro-forestry are not well documented. This study investigated the carbon stocks in biomass and soil, along with the selected soil properties in agro-forestry plots compared to community forests (CF) and upland farms in Chitwan, Gorkha and Rasuwa districts of Central Nepal during the year 2012-2013. We determined the total above ground biomass carbon, soil organic carbon (SOC) stocks and soil properties (bulk density, organic carbon per cent, pH, total nitrogen (TN), available phosphorus (P), exchangeable potassium (K), and cation exchange capacity (CEC)) on samples taken from four replicates of 500 m2 plots each in community forests, agro-forestry systems and agricultural land. The soil was sampled in two increments at 0-15 cm and 15-30 cm depths and intact cores removed for bulk density and SOC determination, while loose samples were separately collected for the laboratory analysis of other soil properties. The mean SOC percent and corresponding soil carbon stocks to 30 cm depth were generally highest in CF (3.71 and 3.69 per cent, and 74.98 and 76.24 t ha-1, respectively), followed by leasehold forest (LHF) (2.26 and 1.13 per cent and 40.72 and 21.34 t ha-1, respectively) and least in the agricultural land (3.05 and 1.09 per cent, and 63.54 and 19.42 t ha-1, respectively). This trend was not, however, observed in Chitwan, where agriculture (AG) had the highest SOC content (1.98 per cent) and soil carbon stocks (42.5 t ha-1), followed by CF (1.8 per cent and 41.2 t ha-1) and leasehold forests (1.56 per cent and 35.3 t ha-1) although the differences were not statistically significant. Other soil properties were not significantly different among land use types with the exceptions of pH, total N, available P and CEC in the Chitwan plots. Typically, SOC and soil carbon stocks (to 30cm depth) were positively correlated with each other and with TN and CEC. The AGB-C was expectantly highest in Rasuwa district CF (ranging from 107.3 to 260.3 t ha-1) due to dense growth and cool climate, followed by Gorkha (3.1 to 118.4 t ha-1), and least in Chitwan (17.6 to 95.2 t ha-1). The highest C stocks for agro-forestry systems in both above ground and soil were observed in Rasuwa, followed by Chitwan district. Besides forests, agro-forestry systems also hold good potential to store and accumulate carbon, hence they have scope for contributing to climate change mitigation and adaptation with co-benefits.Journal of Forest and Livelihood 13(1) May, 2015, page: 56-68


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