Adjacent Farms Research Articles

Soil P Storage Capacity in Agricultural Treatment Wetlands: Can a System Designed for N Reduction Also Retain P?

Increasing interest focuses on utilizing wetlands to reduce nutrient loading to surface waters. The current study examines soil P storage capacity in three treatment wetlands designed to decrease N loading from an agricultural tile drainage system in Illinois. Adjacent farm field and restored floodplain wetland soils were also evaluated. Results demonstrate that wetland soils sequestered P; however, the magnitude of P retention varied significantly across treatment systems and floodplain wetlands related to differences in soil properties. Soil P storage capacity increased in the direction of water flow, but varied across treatment wetlands; soils ranged from P sinks (5.8 ± 1.5 mg P kg−1) to potential P sources (−17.2 ± 2.0 mg P kg−1). Farm fields displayed the highest water soluble P levels (11.3 ± 1.5 mg P kg−1) and represented the largest potential source of P with a mean storage capacity of −48.6 ± 6.8 mg P kg−1. A phosphorus saturation ratio threshold value of 0.10 differentiated between potential P sources and sinks. Findings suggest wetlands receiving P loadings from tile drainage accumulate soil P over time, but maintaining P removal efficiency in treatment wetlands may require periodic management to decrease soil P concentrations via nutrient removal and/or soil amendments.

Effects of coffee management intensification in natural forests on woody species diversity and structure in Yayo district, south western Ethiopia

This study was conducted to evaluate the difference between woody species diversity, structure and similarity in natural forests and adjacent coffee farms in Yayo district, southwestern Ethiopia. Vegetation data were collected from both land use systems using transects walk lines. The Shannon, Simpson’s, similarity and importance values index were analyzed using SPSS version 20 software. The result revealed 64 woody species belongs to 31 families from both land uses. Moraceae had the most diverse family having each 5 and 8 species in coffee farms and natural forests respectively. The species richness was higher in natural forests (54) than coffee farms (38). Coffea arabica (42.85%) and Celtis africana (21.14%) those frequently occurred had the highest importance value indices in coffee farms and natural forests respectively. Of total species recorded, 28 (43.75%) are common, 26 (40.63%) and 10 (15.62%) were unique to natural forests and coffee farms respectively. The highest number of woody plants per hectare were distributed in diameter at breast height 5-10cm having 1250 ha−1 (64.10%) in natural forests and 471 ha−1 (72.33 %) in coffee farms. The total basal areas were 364.44 and 669.84 m2 ha−1 in coffee farms and natural forests respectively. The result indicated that planting coffee in natural forests with intensified management system causes significant differences on the overall woody species diversity i.e. the structure, composition and regeneration rates of the forest. Therefore, it is recommended to plant coffees in home garden and open lands with planting multipurpose shade trees rather than cultivating it in natural forests.

Very short-term spatial and temporal wind power forecasting: A deep learning approach

In power systems that experience high penetration of wind power generation, very short-term wind power forecast is an important prerequisite for look-ahead power dispatch. Conventional univariate wind power forecasting methods at presentonly utilize individual wind farm historical data. However, studies have shown that forecasting accuracy canbe improved by exploring both spatial and temporal correlations among adjacent wind farms. Current research on spatial-temporal wind power forecasting is based on relatively shallow time series models that, to date, have demonstrated unsatisfactory performance. In this paper, a convolution operation is used to capture the spatial and temporal correlations among multiple wind farms. A novel convolution-based spatial-temporal wind power predictor (CSTWPP) is developed. Due to CSTWPP's high nonlinearity and deep architecture, wind power variation features and regularities included in the historical data can be more effectively extracted. Furthermore, the online training of CSTWPP enables incremental learning, which makes CSTWPP non-stationary and in conformity with real scenarios. Graphics processing units (GPU) is used to speed up the training process, validating the developed CSTWPP for real-time application. Case studies on 28 adjacent wind farms are conducted to show that the proposed model can achieve superior performance on 5-30 minutes ahead wind power forecasts.

Prediction of Spread and Regional Development of Hop Powdery Mildew: A Network Analysis.

Dispersal is a fundamental aspect of epidemic development at multiple spatial scales, including those that extend beyond the borders of individual fields and to the landscape level. In this research, we used the powdery mildew of the hop pathosystem (caused by Podosphaera macularis) to formulate a model of pathogen dispersal during spring (May to June) and early summer (June to July) at the intermediate scale between synoptic weather systems and microclimate (mesoscale) based on a census of commercial hop yards during 2014 to 2017 in a production region in western Oregon. This pathosystem is characterized by a low level of overwintering of the pathogen as a result of absence of the ascigerious stage of the fungus and consequent annual cycles of localized survival via bud perennation and pathogen spread by windborne dispersal. An individual hop yard was considered a node in the model, whose disease status in a given month was expressed as a nonlinear function of disease incidence in the preceding month, susceptibility to two races of the fungus, and disease spread from other nodes as influenced by their disease incidence, area, distance away, and wind run and direction in the preceding month. Parameters were estimated by maximum likelihood over all 4 years but were allowed to vary for time transition periods from May to June and from June to July. The model accounted for 34 to 90% of the observed variation in disease incidence at the field level, depending on the year and season. Network graphs and analyses suggest that dispersal was dominated by relatively localized dispersal events (<2 km) among the network of fields, being mostly restricted to the same or adjacent farms. When formed, predicted disease attributable to dispersal from other hop yards (edges) associated with longer distance dispersal was more frequent in the June to July time transition. Edges with a high probability of disease transmission were formed in instances where yards were in close proximity or where disease incidence was relatively high in large hop yards, as moderated by wind run. The modeling approach provides a flexible and generalizable framework for understanding and predicting pathogen dispersal at the regional level as well as the implications of network connectivity on epidemic development.

On relaxation of the influences of treated sewage effluent on an adjacent seaweed farm in a tidal strait

An Eulerian passive tracer model coupled with a quadruple-nested 3D circulation model was used to assess the coastal dispersal of treated wastewater effluent from a sewage treatment plant and the associated impacts on an adjacent seaweed farm using three different operational scenarios. When the discharged volume and source effluent fluxes were decreased by ~16.7%, the accumulated effluent in the farm was reduced by ~25.4%. A tracer flux budget analysis revealed the apparent predominance of the transient component that accounts for the nonlinear interactions primarily from tidal currents and eddies. The transient flux promoted the effluent influx to impede effluent accumulation in the farm, whereas the mean flux contributed to the outgoing flux. A source flux reduction caused a remarkable decrease in the transient flux and thus an even greater effluent accumulation reduction. In turn, a modified source density scenario without total effluent volume change did not work as expected.

Potential Phosphorus Export in Snowmelt as Influenced by Fertilizer Placement Method in the Canadian Prairies

Placement strategies for P fertilizer can affect P availability to crops and influence the amounts and forms of P removed from soil in runoff, contributing to eutrophication. On the Canadian prairies, most runoff occurs during snowmelt. Two adjacent farm fields in Saskatchewan, Canada, were used to assess the effects of spring P fertilizer placement on crop P uptake, residual soil P, and potential P export in simulated snowmelt. One was in conventional tillage (CT) with no history of P fertilization, and the other was in a no-till (NT) system with multiyear P fertilization at recommended rates. Fertilization (monoammonium phosphate) treatments were no P fertilizer (control); seed placed, deep banded, and broadcast and incorporated at 20 kg PO ha; and broadcast treatments at 20, 40, and 80 kg PO ha. Yield and P uptake were not affected by placement method. Water-extractable P at the soil surface after harvest was unaffected by placement or rate at either site but increased below the 5-cm depth at the NT site in 2016. Broadcast treatments increased P in runoff relative to in-soil P placement for the 20- and 80-kg PO ha treatments at the CT site and for the 80-kg PO ha treatment at the NT site. Thus, in-soil application of P fertilizer appears to be an effective strategy to reduce the risk of P export in snowmelt runoff.

A scenario generation method based on the mixture vine copula and its application in the power system with wind/hydrogen production

The scenario generation method is of great significance to analysis the optimal operation of power system with random variables. However, in case of several wind farms are contained in the power system, it is difficult to precisely generate the scenarios due to the dependence among the wind power output. To solve this problem, a new scenario generation method considering the dependence of multi-wind power output based on the mixture vine copula is proposed in this paper. In this method, the K-means method, C-vine and D-vine copula method are combined to analysis the dependence of the multi-wind power output. Through the proposed method, the precise description of data characteristic of multi-wind power output can be achieved. To verify the accuracy of this method, simulation is conducted by using the measured outputs of three adjacent wind farms. The numerical results show that a better simulation can be obtained by the proposed scenario generation method compared to the existing ways. Further, research on capacity allocation of system with wind/hydrogen production is performed based on the proposed scenario generation method. The result demonstrates the great importance of the proposed scenario generation method to the power system with wind/hydrogen production.

Wake and performance interference between adjacent wind farms: Case study of Xinjiang in China by means of mesoscale simulations

To ameliorate the efficiency of wind farms, except assessing the wake effect between the wind turbines, the wake interference between the wind farms must be considered. Based on the Weather Research and Forecasting (WRF) model, the overall performance and power output characteristics, and wake interference effects between the adjacent wind farms in Hami region of Xinjiang province under real terrain and atmospheric conditions were investigated. The wind turbine drag parameterization (WTDP) scheme was elaborated. The results show that the wake of the whole field generally recovers at downstream 16.5 km under prevailing wind direction and annual average wind speed, and the frequency of power output around the rated power is up to 30%. Moreover, the disturbance induced by the wake effect of a large-scale wind farm on its downstream adjacent farm was quantitatively evaluated. Due to the impact of the upstream farm, the wake distance of the downstream wind farm is doubled. The influence on the power output presented a regularity of day-night alternation, with a higher frequency of great loss at night, dawn and evening. The average relative loss ratio reached 5.8%. This study is expected to provide a theoretical basis and engineering guidance for micrositing of wind farms.

Residual effects of treated effluent diversion on a seaweed farm in a tidal strait using a multi-nested high-resolution 3-D circulation-dispersal model

A high-resolution 3-D model was developed to assess the impact of a diversion outfall at the Tarumi Sewage Treatment Plant (TSTP) on an adjacent seaweed farm in Osaka Bay, Japan. The model was extensively validated to ensure a reasonable agreement with in situ observations. The western part of the farm is largely influenced by tidal currents, whereas the eastern area is mainly affected by subtidal residual currents that are primarily due to surface wind stress. The released effluent is transported by counterclockwise residual circulation formed off the TSTP. The model reveals that the diversion adequately suppresses the influence on the farm. While the instantaneous effluent concentration is diminished by about 50%, the effluent accumulated on the farm decreased from 2.83 × 104 m3 to 2.01 × 104 m3 due to the diversion, demonstrating an approximately 28% reduction of the effluent from the TSTP by the diversion outfall.

Soil Organic Carbon Storage, &lt;i&gt;N&lt;/i&gt; Stock and Base Cations of Shade Coffee, Khat and Sugarcane for Andisols in South Ethiopia

In the Wondo Genet, Ethiopia, the common agricultural land uses include maize, shade coffee, khat and sugarcane. The objective of this study was to examine the impact of perennial land uses on soil organic carbon (SOC), soil N and base cations. Four sites having maize and one or two of perennial land uses and with similar site characteristics were identified for this study. Soils (0 - 30 cm) were sampled at corners of a plot (20 × 20 m2) placed in each land use at each site. Results indicated that the SOC storage of the shade coffee plantations were 86% and 125% higher compared with adjacent maize land uses with the absolute differences being 50.7 and 54.4 Mg&#183ha-1, respectively. The soil N stock was 109% and 126% higher for the shade coffee than the maize land use while the absolute differences were 5.7 and 4.7 Mg&#183ha-1 for the same sites. Among perennials, the higher SOC storage in the shade coffee is attributable to the increased litter input and reduced soil disturbance in the system. While the higher soil N in the shade coffee was attributed to reduction of leaching, N uplift, and the increased litter quality and input. The high relative increase in shade coffee in SOC and soil N at Finance site was ascribed to the finer soil texture and low SOC and soil N at the compared adjacent maize farm. Although not significant, the relative increase in SOC (34%) and soil N (43%) in the sugarcane at the Finance as well as the relative increase in SOC (7%) and soil N (9%) in khat at Gotu as compared to Chaffee site was attributed to mainly the management differences. The shade coffee has the greatest potential for SOC storage and for increasing N stock, while khat and sugarcane have the least potential.

Impact of cover cropping and landscape positions on nitrous oxide emissions in northeastern US agroecosystems

Abstract The environmental benefits of organic farming compared to conventional agriculture are well documented, but relatively few studies have assessed their differences in emissions of nitrous oxide (N 2 O), a potent greenhouse gas (GHG). The objective of the study was to assess the interactive impact of management and landscape positions on soil characteristics and N 2 O emissions. A field-scale experiment was conducted in two adjacent grain farms in upstate New York that have both undergone the same management for 20 years. In the conventional field (CNV), inorganic fertilizer was the only nitrogen (N) source, but in the organic fields (ORG), a legume cover crop, red clover ( Trifolium pratense) , was frost-seeded into a winter grain (spelt, Triticum spelta ), and then incorporated in spring as a N source for the subsequent maize plants ( Zea mays ). Measurements of soil properties and N 2 O emissions were conducted at shoulder and toeslope positions on both CNV and ORG fields in 2012. Based on Principal Component Analysis, landscape position, management regime, and rotation phases explained 67% of the variation in the soil properties; these three major sources of variation in soil properties (principal components) were correlated significantly with seasonal average N 2 O emissions. Comparable N 2 O emissions were found from the clover-maize (ORG Cl-M) phase in the ORG field and the bare fallow-maize phase in the CNV field. The spelt-clover phase in the ORG field had the lowest N 2 O emissions due to low N availability. In the CNV field, seasonal average N 2 O emissions were driven mainly by the elevated gas fluxes after fertilizer application. High soil moisture and inorganic N pools towards the end of the growing season probably resulted in increased denitrification rates. The impact of landscape position on N 2 O emissions was mainly found in the CNV field, probably because greater moisture and pH drove greater rates of complete denitrification at toeslope positions. In the ORG Cl-M phase, the seasonal average N 2 O emissions were dominated by the emission peaks that immediately followed incorporation of clover. Greater clover biomass at shoulder slope positions resulted in greater N 2 O peaks there, but the position effect was not statistically significant. Our study suggests that ecosystem state factors, such as landscape characteristics, interacted with management practices to impact soil properties, crop growth, and microbial communities and, therefore, had interactive effects on N dynamics, including N 2 O emissions.

Effects of hand-hoe tilled conservation farming on soil quality and carbon stocks under on-farm conditions in Zambia

Conservation farming (CF) has been promoted in Zambia since the 1980s. Despite long-term practice of CF in Zambia, its effect on soil fertility, including the storage of soil organic matter (SOM), on smallholder farms are inconclusive. Here, we assess the effect of CF as compared to conventional tillage on soil quality parameters on smallholder farms in the Eastern province (EP, 20 sites, two to six years of CF) and Central province (CP, 20 sites, four to twelve years of CF) in Zambia. Soils under CF (minimum tillage hoe basins, crop rotation and residue retention) were compared with adjacent conventional farms (hoe ridges in EP and overall digging or ridge splitting in CP). Only small differences were observed in the soil quality parameters between the CF basins and adjacent conventional plots after maximum 12 years since CF adoption. The concentration of soil organic carbon (%SOC) and carbon (C) stocks did not differ significantly between management practices, with C stocks in CF basins and conventional plots in EP amounting to 4.41 and 4.63kgm−2, respectively, while this is 3.37 and 3.57kgm−2, in CP. Likewise, the %SOC did not differ significantly between soils in the basins and in-between the basins. Both observations indicate that either the annual net accumulation of SOC is very small, or that on-farm surveys involve significant year-to-year changes in the position of the basins. However, the latter is not supported by plant available phosphorus (Bray P) data, which are significantly greater in CF basins than in-between them (12.7 vs 8.3mgkgsoil−1 in CP and 8.5 vs 5.2mgkgsoil−1 in EP), indicating significant Bray P accumulation in CF basins, due to annual fertilizer addition. Amounts of Bray-P in CF basins did not significantly differ from that under conventional management. Overall, our results show small differences in the soil quality parameters between the CF and conventional practices at smallholder farms after maximum 12 years since adoption of CF.

Biomass Energy Resource of the Highland Bamboo (&amp;lt;i&amp;gt;Yushania alpina&amp;lt;/i&amp;gt;) and Its Potential for Sustainable Exploitation in Southern Aberdares Forest

Yushania alpina is the only bamboo species native to Kenya and covers about 150,000 ha growing in pure or mixed stands in the montane forests. The Aberdare forest is one of the natural habitats for Y. alpine occupying an area of 6419 ha mainly in the water catchment areas. The growing human population and depletion of other forest resources have necessitated the exploration of Y. alpine as a source of energy. This paper assessed the quantity of Y. alpine available for biomass energy and its potential for sustainable exploitation. Plots were laid on area maps to cater for altitude and distance from farms. The study area was stratified into three altitudinal zones: A (2220 - 2330 m), B (2331 - 2440 m) and C (2441 - 2550 m). The initial sampling plot of 10 m × 10 m was located randomly 500 m from the edge of the forest while the subsequent plots were laid out systematically at intervals of 500 m. In each plot, a total enumeration and biomass estimation of bamboo clumps were done using Muchiri and Muga (2013) [1] method. Bamboo samples and those of commonly used biomass energy sources were analysed for calorific value using bomb calorimeter. In addition, data for quantities of biomass energy used by some local industries were used to estimate the amount of bamboo required. The mean stocking was 19,981 (20,000) culms ha-1, and varied significantly among altitude strata and distance from adjacent farms. The mean biomass density and energy content were 86 tons/ha and 380,893 Kca/ha respectively with the higher altitudinal stratum (zone C) having the highest means (114 tons/ha) while the lower stratum (zone A) had the lowest (65 tons/ha). The energy needed by sampled local industries was 416,276,266 Kcal per year against 2.4 billion Kcal available in the bamboo forest. This implies that the bamboo forest in its present stocking can provide biomass energy for these local industries for more than five years. With bamboo maturing with less than five years, the forest can sustainably provide the required energy while still providing its environmental services.

EVALUATION OF SHEEP GRAZING EFFECTS ON NEMATODE COMMUNITY, INSECT INFESTATION AND SOIL FERTILITY IN SWEET CHESTNUT ORCHARDS: A CASE OF STUDY

In sweet chestnut cultivation, important ecosystem in Europe, the moderate sheep grazing practice may have some beneficial effects in organic farming. Its impact, on soil fertility, soil nematode community and level of fruit infested by tortricids and curculionids was evaluated in a case of study in Tuscany (Central Italy). An organic farm with sheep grazing system (SG) based on long-term field application was compared with an adjacent organic farm with poultry manure system (PM). In both managements, no treatment to control pests and diseases was applied and 0.19 kg /plant of nitrogen were distributed. SG increased twice the amount of organic C, total N and available P than PM. Moreover, the salinity effect of uric acid significantly increased the pH values in SG (from 5.0 to 6.2). The greatest accumulation of organic matter under SG provided stability in nematode community structure and the plant parasitic nematodes decreased. The analysis on the nematodes emerged from Galleria mellonella larvae, revealed that the abundance of native entomopathogenic nematodes was low and not effective to control insect pests. The sheep demonstrated to be the effective predators of tortricid and weevil larvae and in November, the total infestation was significantly lower in SG (34.3%) than PM (54.3%).

Development and Validation of Pathogen Environmental Monitoring Programs for Small Cheese Processing Facilities

Pathogen environmental monitoring programs (EMPs) are essential for food processing facilities of all sizes that produce ready-to-eat food products exposed to the processing environment. We developed, implemented, and evaluated EMPs targeting Listeria spp. and Salmonella in nine small cheese processing facilities, including seven farmstead facilities. Individual EMPs with monthly sample collection protocols were designed specifically for each facility. Salmonella was detected in only one facility, with likely introduction from the adjacent farm indicated by pulsed-field gel electrophoresis data. Listeria spp. were isolated from all nine facilities during routine sampling. The overall Listeria spp. (other than Listeria monocytogenes ) and L. monocytogenes prevalences in the 4,430 environmental samples collected were 6.03 and 1.35%, respectively. Molecular characterization and subtyping data suggested persistence of a given Listeria spp. strain in seven facilities and persistence of L. monocytogenes in four facilities. To assess routine sampling plans, validation sampling for Listeria spp. was performed in seven facilities after at least 6 months of routine sampling. This validation sampling was performed by independent individuals and included collection of 50 to 150 samples per facility, based on statistical sample size calculations. Two of the facilities had a significantly higher frequency of detection of Listeria spp. during the validation sampling than during routine sampling, whereas two other facilities had significantly lower frequencies of detection. This study provides a model for a science- and statistics-based approach to developing and validating pathogen EMPs.

Identification and Correction of Outliers in Wind Farm Time Series Power Data

Wind farm time series power data is widely used in wind power integration studies and wind power forecasting. Historical time series wind power data is frequently corrupted by communication errors, wind turbine outages and curtailment, which introduce outliers. The identification and correction of outliers is important in ensuring the integrity of wind power integration studies, wind power forecasts and other analysis employing such data. An outlier identification methodology based on a probabilistic wind farm power curve and typical outlier characteristics is described. Additionally, an outlier correction methodology that exploits the spatial correlation between adjacent wind farms is proposed. These methods are tested on US modelled wind power data and applied to a case study of real operational wind power data from Northwest China. The cost and curtailment benefits of the identification and correction methods are demonstrated through a day-ahead unit commitment example.

Three‐phase probabilistic load flow for power system with correlated wind, photovoltaic and load

In order to evaluate impact of different uncertainty, such as the intermittent behaviour of wind power and photovoltaic (PV) generation and bus load, and adjacent wind farms or PV resources on performance of power system, a new three-phase probabilistic load flow (PLF) algorithm with asymmetric line parameter and unbalanced load of distribution system is proposed. Correlation among input random variables is considered, especially the joint correlation of wind power and PV generation and bus loads is considered, and then joint probabilistic model of wind power, PV generation and bus load is established. Then a joint cumulants method and Gram–Charlier expansion are applied to obtain the cumulative distribution function of desired random variables, and PLF results based on joint cumulants method are compared with the ones of Monte Carlo simulations. Proposed method allows evaluating potential impact of different correlation and renewable energy generation penetration on the PLF of power system. The effectiveness of proposed method is demonstrated with a typical structure of 25-bus distribution system.

An Ecological Paradox: The African Wild Dog (Lycaon Pictus) Is Not Attracted to Water Points When Water Is Scarce in Hwange National Park, Zimbabwe.

In dry biomes, spatio-temporal variation in surface water resource stocks is pervasive, with unknown effects on the ranging behaviour of large predators. This study assessed the effect of spatial variation in surface water resources on the ranging behaviour of the African wild dog (Lycaon pictus). We analyzed data for 1992 (dry year with 20 water points) and 2000 (wet year with 30 water points) against presence-only data for five packs of L. pictus in a part of Hwange National Park and adjacent smallholder communal farming areas in western Zimbabwe. Modelling the potential habitat for L. pictus using Maxent with distance from water points (Dw) and Normalized Difference Vegetation Index (NDVI) as predictor variables was successful for 2000 (AUC = 0.793) but not successful for 1992 (AUC = 0.423), with L. pictus probability of occurrence near water points being more for year 2000 than for year 1992. The predicted L. pictus range was wider in 1992 (~13888.1 km2) than in 2000 (~958.4 km2) (Test of Proportions, χ2 = 124.52, df = 1, P = 0.00). Using the 2nd order Multitype Nearest Neighbour Distance Function (Gcross), we also observed significant attraction between L. pictus and water points within only ~1km radius for 1992 but up to ~8km radius for 2000. Our study reinforced the notion that surface water resources attract wild dogs in the savannahs but paradoxically less so when water resources are scarce. In particular, our study furthers current understanding of the effects of changing water availability regimes on the endangered L. pictus, providing evidence that the endangered predator’s home range encroaches into potential ecological traps (i.e., smallholder communal farming areas) when water resources are scarce.

Wild harvest: distribution and diversity of wild food plants in rice ecosystems of Northeast Thailand

Rice fields provide not only a staple food but are also bio-diverse and multi-functional ecosystems. Wild food plants are important elements of biodiversity in rice fields and are critical components to the subsistence of poor farmers. The spatial and seasonal distribution of wild food plants were analysed across different sub-systems occurring within paddy ecosystems in two adjacent rice farming villages in Kalasin, Northeast Thailand. Data were collected in 102 sampling sites corresponding to seven sub-systems including tree rows, mounds, field margins, shelters, ponds, pond margins and levees. Frequency of occurrence and absolute abundance were quantified for each species in the two seasons of two years, and data on uses of wild food plant species were collected through focus group discussions. A total of 42 species from 28 botanical families were reported, and one third of these have been classified as weeds of rice by other authors. Results show that species abundance, frequency of occurrence and diversity varied seasonally and spatially within paddy rice ecosystems. Higher diversity indexes were observed in the monsoon in most sub-systems. The most diverse sub-systems in the monsoon were shelters, mounds and pond margins, and tree rows and mounds in the dry season. Field margins, ponds and levees presented lower diversity, but are habitat of aquatic species important for the local diet, such as Ipomoea aquatica and Marsilea crenata. The herbs Lobelia sp. and Glinus oppositifolius, classified as rice weeds, were most abundant species in the dry season and frequently consumed. Leucaena leucocephala, of which the roots, leaves and fruits are commonly consumed as vegetable, was the most abundant tree in most sub-systems. More than half of the species were specific to one or two sub-systems due to particular niche requirements. Three quarters of wild food plant species had additional uses besides food; with ten different types of use and multiple use categories occurring in the different sub-systems. This study highlights that the development of more productive lowland rice systems may jeopardize the diversity of wild food plant species in the rice landscape, which is important for the food security of the rural poor.

Effects of shed modifications on ewe reproductive performance and lamb growth rate in Inner Mongolia

The effects of warm sheds on the performance of ewes and their lambs in winter are poorly understood. The aim of the present study was to examine the effects of traditional sheds (TS + grazing) and modified warm sheds (WS, no grazing) on the reproductive performance of ewes (as well as their liveweight) and their lambs during the winter–spring period. Cross-bred ewes (n = 120) were randomly assigned to two treatments, either TS (+ grazing) or WS (no grazing), during the winter–spring period of 2011, 2012 and 2013. This study was conducted on two adjacent farms with the two treatments applied on each. The ewes in the TS treatment were grazed continuously on pasture in the day and housed in traditional sheds each evening, whereas the ewes in the WS treatment were not grazed. The animals in each treatment were fed the same amount of feed. Ewes housed in the WS group had a higher liveweight and lower weight loss than ewes in the TS group (P = 0.004 and 0.005 respectively); over the 3 years, the weight loss of the ewes in both groups was worst in the first 2 months (December–January) compared with the later 2 months, and was significantly alleviated after the first year (2011; P &lt; 0.001). Lamb liveweight and gain were higher in the WS than TS treatment group (P &lt; 0.001) and the growth rates of the lambs increased continuously as shed temperatures increased. Lamb weight gain and birthweight increased significantly with increasing years of the experiment (P &lt; 0.001). There were more lambs born in the WS than in the TS groups (P = 0.020), with higher survival and twinning rates (P &lt; 0.05). As shed temperatures increased, lambing, survival and twinning rates increased continuously. Therefore, keeping livestock in warm sheds during the winter and spring period will lift animal productivity, leading to improved household incomes. Elimination of winter grazing will reduce damage to already degraded grasslands and will assist herders to develop more positive attitudes towards animal production enterprises.