mean value from 8 samples, while analysis of the other soil characteristics was done for the composite samples only. Carbon and nitrogen content was determined by means of dry combustion using an automated C & N analyzer (Heraeus vario EL, Hanau, Germany). The light fraction (LF) organic matter was isolated by suspending the soil in a dense liquid and extracting the LF from the surface (Gregorich and Ellert 1993). Texture of composite samples was determined with the pipette method, distinguishing the three fractions clay (particle size < 0.002 mm), loam (particle size between 0.002 mm and 0.063 mm) and sand (particle size between 0.063 mm and 2 mm). Mineralogy of composite samples was examined through acid-oxalate extractions of aluminium (Alo), iron (Feo) and silica (Sio) and with pyrophosphate extractions of aluminium (Alp), iron (Fep) and Carbon (Cp), see for details de Koning et al. (2003). Oxalate extractions of Al, Fe and Si indicate all active components of Al, Fe and Si, dissolving non-crystalline minerals such as allophane, imogolite, amorphous and poorly crystalline oxides like ferrihydrite as well as organo- mineral Al- and Fe- humus complexes (Mizota and Van Reeuwijk 1989). Pyrophosphate extractions of Al, Fe and C indicate all Al, Fe, and C present in organo-mineral humus complexes (Shoji 1993). The ratio of Alp/Alo is indicative of the contents of allophane versus Al-humus complexes in volcanic soils. Alp/Alo values near 0 suggest that allophane is dominant while Alp/Alo values near 1 indicate the predominance of Al-humus complexes (Mizota and van Reeuwijk 1989). Similarly, Alo minus Alp is an indication for non- crystalline minerals, with high values indicating high contents of these components. Oxalate extracted iron (Feo) minus pyrophosphate extracted iron (Fep) is an indication of the content of ferrihydrite.
The differentland-uses in Kaituna catchment provide different functions and services. Land-use such as dairy, plantation forestry, and sheep and beef raising provide production ES functions. The forests and scrub also provide climate, water, and soil regulation functions. As well the catchment contributes to cultural and habitat functions as there are about 374 hectares of land protected by DOC. The Mount Herbert Scenic Reserve and Kaituna Spur Reserve provide walking tracks for recreationists. Further, Pack Horse Stone Hut which is just at the outer edge of north of catchment carries historic values. This hut was built in 1971 from local stones and people can buy tickets from DOC to stay in the hut and gain an outdoor recreation experience. As the catchment provides diverse functions, the beneficiaries of these services are local landowners, farm stay providers, recreationists, and global population due to carbon sink benefits from forests and scrubs. The stakeholders in the catchment include local landowners who grow food and timber in their farms, DOC and other conservation agencies such as Banks Peninsula Conservation Trust who are involved in the protection of indigenous species, and trampers and holiday seekers who want to stay in the historic stone house. As it is difficult to estimate historic values, this research only focused on the quantification of roundwood and carbon benefits, nutrient load, sediments load, annual water yield, and conservation goal for which indicators are available and biophysical models have been developed for the New Zealand context. These are some of the indicators used to measure benefits people derive from ES in the catchment.
Full progression toward catchment prioritization based on multiple ecosystemservices (Figure 1) is currently con- strained by the difficulty of linking land- use activities to their effects on waterbodies (Moss 2008), resolving con- flicts between achieving differenttypes of services, and uncertainties over the beneficiaries and governance of these services (Bennett et al. 2015). Despite equally impor- tant legal, ethical, and social issues surrounding the prioritization of catchments, accurate assessment of the economic trade- offs required to deliver ecosystemservices will be a key driver in determining the balance between future agricultural and environmental targets in catch- ments (Dodds et al. 2013). Withers et al. (2014) noted unsustainable runoff P concentrations at two UK sites that contained agronomic optimum soil P levels and that were farmed according to soil fertility BMPs. In such cases, a lower critical threshold for soil P – which would poten- tially compromise agronomic production – may be required to protect water quality. Progress in resolving these trade- offs and managing the pressure–impact relationships that exist between catchment ecosystemservices is vital in order to identify locations in catchments where sustainable intensification can be achieved. This requires a flexible conceptual framework that can account for catchment sensitivity to multiple anthropogenic pressures.
However, concerns have been raised regarding the eco- hydrological effects of these artificial forests and shrubs that have induced unwanted environmental problems. Large- scale vegetation restoration has also aggravated water scarcity, gradually leading to soil desiccation (Shangguan and Zheng, 2006; Chen et al., 2008a). Low forest produc- tivity and growth efficiency resulted in “small aged trees” with heights of 3–5 m, a common scene in the region (Chen et al., 2008b). Vegetation-soil moisture feedback may lead to pattern formation (D’Odorico et al., 2007; Fu et al., 2011). Thus, understanding the interactions between these artificial vegetation types and soil moisture is urgently required as ba- sis for adjusting landuse structures and ensuring sustainable provisions of desired ecosystemservices in this area.
The multiple ecosystemservices provided by healthy soil are well known and include soil carbon sequestration to mitigate climate change, a medium for plant and agricultural production and regulating the hydrologic cycle. Despite the wide recognition of the importance of these services, drivers of soil organic carbon (SOC) dynamics across various land uses in East Africa are poorly understood. The objectives of this study were threefold: to quan- tify SOC stocks across Tanzania; assess the effect of land cover and erosion on SOC; and investigate the relation- ship between inherent and dynamic soil properties under diverse land uses. The Land Degradation Surveillance Framework (LDSF) was used to assess the variability of ecological metrics at different spatial scales. SOC was quantiﬁed within and between differentland cover types (forest, woodland, shrubland, grassland and cropland) in Tanzania. A total of 2052 soil samples from 1082 –1000 m 2 plots were collected from seven 100-km 2 sentinel sites in 2010. Composite soil samples were collected at each plot from two depths (0–20 and 20–50 cm) and cu- mulative soil mass samples were collected to 100 cm. Soil samples were analyzed using a combination of tradi- tional analytical laboratory methods and mid-infrared spectroscopy (MIR). Model performance of MIR spectral predictions for carbon was good, with an R 2 of N0.95 and RMSEP of 4.3 g kg −1 , when using an independent validation datasets. Woodland and cropland were the most frequently occurring vegetation structure types in the sampled sites, with 388 and 246 plots, respectively. Average topsoil OC (and range) was 12.4 (1.5–81.4) g C kg −1 (n = 1082) and average subsoil OC (and range) was 7.3 (0.64–53.8) g C kg −1 (n = 970) for the seven sites. Forested plots had the highest mean topsoil organic carbon concentrations (17.3 g C kg −1 ) followed by cropland (13.3 g C kg −1 ), for all sites included in the study, but with high levels of variability between sites. Soil mass at 30 cm was measured and these data were used to calculate carbon stocks for the differentland cover types. An approach based on remote sensing was explored for the mapping of SOC stocks at 30 cm for Tanzania using Moderate Resolution Imaging Spectroradiometer (MODIS) imagery from 2012. Results indicate that the use of image reﬂectance for the mapping of SOC stocks has promising potential, with R 2 values ranging from 0.77 to 0.81 and RMSEP values from 0.90 to 1.03 kg m −2 for the three validation datasets. There is high utility of these maps for strategic land management interventions that prioritize ecosystemservices.
To complement the data contained in tax assessor databases, county GIS offices from Charleston, Berkeley, and Georgetown were contacted to provide snapshots of the coun- ties’ most recent parcel layer and for each time period matching the years of the National Land Cover Database products. 17 These GIS and NLCD layers were used in ArcGIS to create multiple time–invariant variables, as well as time–varying proxies represent- ing different physical properties of each parcel. Among the time invariant variables are various measures of distance, such as distance to flood hazard boundaries, distance to water bodies offering recreational opportunities (i.e., big lakes), distance to the nearest public beach access point, distance to downtown Charleston, distance to the shoreline, and distance to the nearest primary or secondary road. Other variables are percentage cover in the parcel and around it of various habitats, such as crops, forests, and wetlands. Finally, all price data in the tax assessor datasets (i.e., sales prices and assessed values) were adjusted for inflation and expressed in 2016 USD using the Housing Price Index for the Charleston market available from the Federal Reserve Bank.
Soils from four differentlandusetypes were sampled in four geographically different regions where the same four landusetypes were present, within and out of the Paute watershed in the southern Ecuadorian Andes (Figure 1). The four landusetypes were: 1) second growth native forest (Nf), 2) pasture (Pa), 3) Pinus patula Schlecht. plantation (Pp), and 4) Eucalyptus globulus Labill. plantation (Eg). Landusetypes from all regions were located at an average elevation of 3135 m, and ranged between 2950 m to 3450 m. Regions 1 and 2 (Figure 1) are located in the central mountain chain and receive the influence of rain-laden air from the Amazon basin. In these regions, large differences in elevation cause higher orographic precipitation than in the rest of the watershed. The total annual rainfall averages between 1050 mm and 1700 mm . Regions 3 and 4 are located in the south of the Paute watershed. Here, total annual rainfall ranges between 660 mm and 1100 mm  (Figure 1). According to Buytaert et al.  the soils in the northern part of the Paute watershed are classified as Histic Andosols (Regions 1 and 2), and as Dystric Histosols in the southern part of the watershed (Regions 3 and 4) because of lower soil Al and Fe content (Figure 1). Buytaert et al.  described these soils as very darkly colored humic soils, due to the effect of a cold wet climate, and the formation of organometallic com- plexes driven by a stronger effect of Holocenic volcanic ash (from the Quaternary volcanic activity in the north- ern Andes of Ecuador). The influence of volcanic ash diminishes towards the south of the Paute watershed, where climate alone is probably responsible for the accumulation of organic soil matter. Organic matter accu- mulation also determines the high porosity and water retention capacity of these soils. These highland soils have developed on Cretaceous and early Tertiary sediments on the western mountain chain. On the eastern mountain chain, soils have developed on volcanic deposits and on Palaeozoic metamorphic rocks   .
Soils perform a range of synchronous ecosystemservices or ‘soil functions’ such as food, fibre and fuel production, water purification, carbon sequestration, nutrient cycling and the provision of habitats for biodiversity. Soils differ in their relative capacity to perform each of these functions, as determined by landuse and soil properties. The global twin challenges of food security and environmental sustainability require that the supply of soil functions is maximised to meet future demand for each of these functions, at local, national and supranational scales. In this paper, we presented a conceptual framework for the quantification of the supply of, and demand for soil functions, using proxy-indicators. Using Ireland as a case-study, we demonstrated that – in principle, it is possible to meet agronomic as well as environmental policy targets simultaneously through optimisation of soil functions at local and national scale. However, realisation of this potential will require proactive and targeted incentivisation of landuse in relation to soiltypes, to ensure that each soil ‘performs the functions that it is best at’. In addition, it will require careful incentivisation and management of scenarios towards increased agricultural production, i.e. ‘intensifica- tion’, ‘expansion’ and ‘increased resource efficiency’. The resulting concept of ‘Functional Land Management’ is closely aligned to the original EU Thematic Strategy on soils, which was broadly supported by key-stakeholder groups, and provides a logical step for the sustainable intensification of European agriculture.
tion of biodiversity and ecosystemservices under a range of land-use and climate future scenarios? (2) What is the mag- nitude of the uncertainties associated with the projections ob- tained from different scenarios and models? Although inde- pendent of the ISI-MIP, the BES-SIM has been inspired by ISI-MIP and other intercomparison projects and was initiated to address the needs of the global assessment of IPBES. We brought together 10 biodiversity models and six ecosystem functions and services models to assess impacts of land-use and climate change scenarios in the coming decades (up to 2070) and to hindcast changes to the last century (to 1900). The modeling approaches differ in several respects concern- ing how they treat biodiversity and ecosystemservices re- sponses to land-use and climate changes, including the use of correlative, deductive, and process-based approaches, and in how they treat spatial-scale and temporal dynamics. We assessed different classes of essential biodiversity variables (EBVs), including species populations, community compo- sition, and ecosystem function, as well as a range of mea- sures on ecosystemservices such as food production, pol- lination, water quantity and quality, climate regulation, soil protection, and pest control (Pereira et al., 2010; Akçakaya et al., 2015). This paper provides an overview of the scenarios, models and metrics used in this intercomparison, and thus a roadmap for further analyses that is envisaged to be inte- grated into the first global assessment of the IPBES (Fig. 1).
Heuristics uses past experience to make educated guesses about the present. Using rules and decisions based on analysis of past network or email traffic, heuristic scanning in antivirus software can self-learn and use artificial intelligence to attempt to block viruses or worms that are not yet known about and for which the antivirus software does not yet have a filter to detect or block.
For evaluating the global ecosystem value, Costanza et al. (1997) defined the theory and methodology of eco- system service evaluation clearly from scientific purport. However, it was controversial in China, with some eco- system services poorly valued or ignored (Zhang et al. 2013). When it was applied to concrete area, the methods would produce biggish warp due to (1) the value of ecosystemservices reflected the economic level of developed countries such as the United States and European countries, rather than developing countries such as China; (2) although wetland ecosystems provide significant functions, their value per unit area was over- valued (Zhang et al. 2013). So, to adjust Costanza et al.’s (1997) value coefficients, Xie et al. (2003) constituted the equivalent value per unit area of ecosystemservices for Chinese terrestrial ecosystem based on questionnaire investigation from about 200 ecological scholars and some achievements (Table 1).
This study was aimed at assessing the status of soil properties under Enset (Enset ventricosum) farm, grazing and cultivated land from upper, middle and lower slope positions (15-25%, 8-15% and 3-8% slope) in Delta sub- watershed of Southwestern Ethiopia. Split block design was employed. A total of 54 soil samples, from 3 slope positions x 3 landusetypes (treatments) x 2 depths (0-20 and 20-40cm) x 3 replications, were collected and used to test for soil chemical properties. For soil physical properties assessment, 27 soil samples were collected from 0-20cm soil depth by using simple random sampling technique. The result from several soil chemical parameters revealed that OC, TN, C/N, AvP, CEC, exchangeable bases (K + , Mg +2 , Ca +2 and Na + ), ESP, PBS were significantly lower (p<0.001) in both depths of cultivated land and upper slope position than in respective slope positions of the other two landusetypes. However, average soil EC and pH did not show variation with both slope positions and landusetypes. The result also showed that soil physical property parameters such as soil bulk density, soil moisture and clay content in grazing lands were significantly higher (p<0.001). In contrast, total porosity and silt content were relatively lower in grazing land. From this finding, it can be concluded that there needs to be a look into not only landusetypes but also slope positions in developing landuse planning and soil management strategies in this region.
Grasses were used for construction by 174 (88.8%) of respondents, of whom the majority collected them person- ally apart from seven (4%) households who bought them and two households (1.1%) who employed people to cut grasses for them. Timber was used by 31 (15.8%) house- holds, of whom 19 (61.3%) bought it locally and one bought it ‘ from town ’ . One household bought both poles and timber from Mbeya. One household used mountain bamboo for building poles. All other poles, timber, and grasses were harvested by the household. Cut poles and timbers were recorded on transects, however it is dif ﬁ cult to differentiate between that harvested for construction use and that harvested for use in tobacco burners. Nine pitsaw sites, eight incidents of logging, and six incidents of dis- carded timber were recorded during ecological surveys. District Of ﬁ cer 3 said that “ there are many illegal loggers ” . Medicinal plants and trees were used by 58 (29.6%) households. Woodland walks with forest users and tradi- tional healers provided an insight into the uses of miombo products, as listed in Supplementary Material Table A. Mushrooms, fruit, and vegetables are used by most house- holds; these are seasonal produce, which is harvested annu- ally. Wild meat was used by 11 (5.6%) households, of whom eight (72.7%) bought it from local hunters. Hunting is illegal without a licence, so this may have affected response rates. However, both Village A Of ﬁ cer 3 and Vil- lage D Of ﬁ cer 3 said that there was “ very little ” poaching in the area. Village A Of ﬁ cer 3 went on to say that occa- sionally eland, buffalo, and hartebeest are poached for food, and that occasionally this is sold locally, but it hap- pens rarely. This may vary from village to village — in Village C, the research team was offered eland meat, and during ecological surveys at the adjacent site there were
Sampling was conducted in May and November 2014. We selected 40 plots of 10 m × 10 m, 10 plots each from primary forest, teak plantation bordered by primary forest, teak plantation bor- dered by agroforest and agroforest. The plots were placed randomly within the differentlanduse areas. A combination of visual search- ing and sorting a standardized volume of litter and soil is the most efﬁcient method for land snail inventories if repeated visits are not possible ( Emberton et al., 1996; Cameron and Pokryszko, 2005; Schilthuizen, 2011 ). Thus, all living slugs and snails as well as their empty shells were collected by two researchers for one hour at each plot. In addition, 5L of leaf litter and surface soil were sampled at each plot. Later, the litter samples were dried, fractioned by sieving and sorted. Several environmental variables were recorded at each plot, i.e. habitat type, altitude, percentage of canopy cover, density of herbaceous layer, presence of deadwood, stones and bare rock, amount of leaf litter, and degree of human impact (cultivation or removal of plants, presence of livestock, human trails, information from locals) (Supplementary Table S1).
The deciduous miombo woodlands of sub-Saharan Africa extend for approximately 2.4 million km 2 (Frost et al., 2003) and support the livelihoods of at least 100 mil- lion people (Syampungani et al., 2009, Dewees et al., 2011) through a range of goods and services, leading them to be described as “ a pharmacy, a supermarket, a building supply store, and a grazing resource ” (Dewees et al., 2010: 61). They are also of global importance as a carbon store (Ribeiro et al., 2015). Rapid landuse change in these woodlands is occurring and is anticipated to continue (Ryan et al., 2016), leading to degradation with potentially devastating consequences for the livelihoods that they sup- port. Tobacco cultivation is a leading cause of landuse change and is common within miombo woodlands due to the suitability of the sandy soils and plentiful wood, which are needed to cure the leaves for storage (Geist, 1999). However, tobacco is nutrient hungry (Baris et al., 2000) and miombo soils are poor (Frost et al., 2003), therefore woodland is constantly cleared to continue to grow or expand cultivation (Sauer and Abdallah, 2007). This leads to deforestation, degradation (Lecours et al., 2012), and expansion of the agricultural frontier. Furthermore, eco- nomic incentives from tobacco cultivation drives in- migration and increases the demand for forest products and ES, yet access to miombo woodland is rarely regulated and the capacity to restrict overuse is weak (Luoga et al., 2005). Several studies on ES provision and use within miombo woodlands have found that the use of provisioning ES is extensive and that they are disproportionately used by the rural poor (Syampungani et al., 2009; Dewees et al., 2011; Njana et al., 2013). However, it is not known how environmental changes resulting from landuse will affect this relationship in the future (Ryan et al., 2016) particu- larly in remote areas, and what impact this loss will have on local communities. Consequently, this paper examines: (1) the types of provisioning ES used and by which house- holds to determine who will be vulnerable to future changes; (2) the perceived changes in the availability of these services in areas where landuse change is occurring; and (3) what this may mean for the future management of miombo woodlands.
SOC pool in ecosystems and regions that have so far been heavily under-represented. Whereas the SOC pool has been studied at global, continental (Eswaran et al., 1993; Liski et al., 2002; Smith, 2004) or regional scales in humid forest systems (Batjes and Dijkshoorn, 1999; Schwartz and Namri, 2002), there is a lack of information on Mediterranean sys- tems. In addition, estimates of SOC stocks may be partic- ularly inaccurate in areas with diverse landuse patterns, such as Mediterranean landscapes. In Spain, for example, Rodr´ıguez-Murillo (2001) assessed organic C contents under differenttypes of landuse and soil. Nevertheless, there are few studies providing accurate regional SOC estimates based on combined studies of soilland cover data. In general, there is a lack of national-scale studies on soil spatial variability in Spain (Ib´a˜nez et al., 2005) and therefore detailed studies on SOC distribution in soils are necessary (Flores et al., 2007). Future studies on SOC pools need to be carried out in a com- parable way, and the access to data sets needs to be facilitated (Bahn et al., 2009). This study comes to fill a gap in SOC as- sessment in Mediterranean soils.
As crop prices rise across the nation, and financial incentives for enrolling land in CRP stagnate, land-use conversion from CRP to crop production is increasing. Understanding the relationships between land choice factors in Cass County, ND is the intent of this study. As CRP contracts expire in Cass County, many of these acres will likely not be re-enrolled, but rather converted into cropland. By examining how decision factors influence farmers’ land-use choices, this study aims to predict how the acreage will be allocated and the potential repercussions it will have. While there have been similar studies done incorporating land-use change and CRP, the inclusion of satellite imagery and economic factors has been limited. This research converts the USDA NASS Cropland Data Layer (CDL) into field plots to limit the computational workload on performing a logistic regression on land-use choice parameters. The regression uses operating revenue and weather data as decision factors with the land-use of the parcel as the dependent variable. The relative effect of operating revenue and previous land-use was consistent across both CATMOD and MDC procedures in SAS. Previous years’ land-use was of far greater importance in determining subsequent land-use than operating revenue or weather variables.
weathering with associated erosion. Most of stabilization has to be undertaken in soft soils (silty, clayey peat or organic soils) in order to achieve desirable engineering properties. According to Sherwood fine-grained granular materials are the easiest to stabilize due to their large surface area in relation to their particle diameter. A clay soil compared to others has a large surface area due to flat and elongated particle shapes . On the other hand, silty materials can be sensitive to small change in moisture and, therefore, may prove difficult during stabilization . Peat soils and organic soils are rich in water content of up to about 2000%, high porosity and high organic content. The consistency of peat soil can vary from muddy to fibrous, and in most cases, the deposit is shallow, but in worst cases, it can extend to several meters below the surface [6, 8]. Organic soils have high exchange capacity; it can hinder the hydration process by retaining the calcium ions liberated during the hydration of calcium silicate and calcium aluminate in the cement to satisfy the exchange capacity. In such soils, successful stabilization has to depend on the proper selection of binder and amount of binder added .