Distribution of commensal rodents in rain-fed and irrigated areas of Swat district, Khyber Pakhtunkhwa, Pakistan

Distribution pattern and relative abundance of the agricultural rodent pests of rain-fed and irrigated areas of district Swat Khyber Pakhtunkhwa, Pakistan were recorded from April 2011 to November 2013 using wire mesh live traps. A total of 350 rodents (269 Rattus rattus and 81 Mus musculus) were captured under 2268 trap nights (trap success: 0.15). Regression of daily captures on cumulative captures revealed an estimate of 350 rodents from all the sampled structures with an average of 21.8 rodents per crop field. House rats (R. rattus; 76.8% of captures) were numerically dominant in almost all types of agricultural fields, and were significantly different from the mice (Mus musculus; 23.1% of captures). Both species were found together in some fields. The sex ratio revealed that males outnumbered the females in both of the reported species.

Farmers’ Perception towards Transformation of Rice-based Cropping System intoTea Garden

Transformation of agricultural lands into non-farm lands or plantations has got tremendousecological chaos and ripples. Northern part of West Bengal is undergoing rapid changes inrural areas where new opportunities are emerging in the form of demand-driven and market-driven agriculture. Due to persistent low returns from traditional rice cultivation, thetransformation of paddy fields into tea gardens has been a recent trend for this part ofWest Bengal. The present study has been conducted by selecting purposively three blocksfrom Alipurduar district and sixty respondents through random sampling, those who havealready transformed their crop field into tea gardens from these blocks. The farmers’perception towards transformation is taken as dependent variable along with a score offourteen independent variables. The responses are collected through a structured interviewschedule. The study envisaged that the farmers’ education level, number of family membersengaged in the garden, their economic motivation, sources of information, risk orientationbehaviour and distance from the tea processing factory showed significant contributiontowards the transformation behaviour. The future impact of such transformation on theecological dynamics in terms of livelihood, biodiversity restoration and ecological resiliencecan be brought under policy frameworks.

Estimating potato crop wetness duration from agrometeorological data

Hourly meteorological observations over a potato crop field were used to validate a biophysical model and different thresholds of relative humidity (RH) to simulate the onset. cessation and total wetness duration (WD). The model showed the capability to simulate multiple wet and dry conditions as well as prolonged moist conditions with a mean absolute error of less than an hour. The deviation between measured and estimated onset and total WD was more pronounced when only RH was used. However, under the prevailing agroclimatic conditions of potato growing regions in India, 80% RH threshold may adequately be accurate to estimate WD for many weather-based disease management advisories.

Crop Field Classification using Data Fusion of Unmanned Aerial Vehicle (UAV) and Sentinel 2A satellite: the case of Oda Dhawata Kebele Cluster farmland, Oromia Region, Ethiopia

Accurate crop classification using remote sensing based satellite imageries approach remains challenging due to mix in spectral signatures. Employing Unmanned Aerial Vehicle (UAV) together with satellite imageries is believed in improving crop classification at field. Accordingly, this study aims to evaluate the potential of UAV images by blending with Sentinel 2A satellite images for crop field classification in Ethiopian agricultural context. The main purpose of the blending is to upgrade and or improve the lower resolution of the data source that is the sentinel 2A data which was 10m resolution. In the study, UAV data was used and preprocessed. The preprocessing includes camera calibration, photo alignment, dense point cloud generation based on the estimated camera positioning of scouting crop types. Then, orthomosaic UAV image was generated from single dense point cloud. Then, the processed UAV data was fused with Sentinel 2A (medium resolution) satellite data using Gram Schmidt pan sharpening method.this method is the most approach that it can run large data sets of spatial resultions. For crop classification, the Random forest (RF) machine-learning algorithm and Maximum likelihood methods were applied. Apart from the UAV and S2A data, field data was collected for training the crop classification. The point field data was collected from Teff, Wheat, Faba bean, Barley and Sorghum crop fields The results show that RF classifier algorithm classifies the crop types with 94% overall accuracy whereas the Maximum likelihood classifier with 90% overall accuracy. This implies that fused image has a potential to be used for crop type classification together with relatively better classification technique with high accuracy level

Factors affecting crop field use by Blackbuck in Krishnasaar Conservation Area, Nepal.

Reducing crop damage caused by wildlife in forest-agricultural land interface requires an understanding of the spatial pattern of crop field use and its drivers. We assessed factors influencing the spatial pattern of crop-field use by a generalist wild herbivore, blackbuck (Antilope cervicapra), in the agriculture-dominated landscape of Krishnasaar Conservation Area (KrCA) in low land Nepal. We systematically selected 103 crop fields distributed over the entire KrCA (within both core area and community development zone) and surveyed them three times over three months, resulting in 309 sampling occasions. We found that crop use by blackbuck was highly localized inside core area (only 15% of the sampled crop fields were used) even though crop fields outside the core area were accessible and had limited mitigation measures applied. The linear mixed effect modeling showed that probability of crop field use by blackbuck increased with size of the crop field, implying the magnitude of foraging benefits affects blackbuck crop-use decisions. The presence of current mitigation measures (e.g., scare crow, vegetative fencing) did not have discernible influence on probability of crop field use, so did the types of the crops, and distance of crop fields from the center of the core area. Overall, our results suggest that generalist herbivore, blackbuck, employs low gain-low risk strategy when using crop fields in natural habitat-agricultural. Minimizing current level of crop damage by blackbuck will require working closely with farmers who owns lands close to the natural habitat (core area) to apply appropriate mitigation measures.