Natural regeneration is less expensive than tree planting, but determining what species will arrive and establish to serve as templates for tropical forest restoration remains poorly investigated in eastern Africa. This study summarises seedling recruitment under 29 isolated legacy trees (14 trees comprised of three exotic species and 15 trees comprised of seven native species) in tea plantations in the East Usambara Mountains, Tanzania. Among the findings were that pioneer recruits were very abundant whereas non-pioneers were disproportionately fewer. Importantly, 98% of all recruits were animal-dispersed.  https://www.selleckchem.com/products/azd0156-azd-0156.html  The size of legacy trees, driven mostly by the exotic Grevillea robusta, and to some extent, the native Milicia excelsa, explained abundance of recruits. The distribution of bird-dispersed recruits suggested that some bird species use all types of legacy trees equally in this fragmented landscape. In contrast, the distribution of bat-dispersed recruits provided strong evidence that seedling composition differed under native versus exotic legacy trees likely due to fruit bats showing more preference for native legacy trees. Native, as compared to exotic legacy trees, had almost two times more non-pioneer recruits, with Ficus and Milicia excelsa driving this trend. Implications of our findings regarding restoration in the tropics are numerous for the movement of native animal-dispersed tree species in fragmented and disturbed tropical forests surrounded by farmland. Isolated native trees that bear fleshy fruits can attract more frugivores, resulting not only in high recruitment under them, but depending on the dispersal mode of the legacy trees, also different suites of recruited species. When selecting tree species for plantings, to maximize visitation by different dispersal agents and to enhance seedling recruit diversity, bat-dispersed Milicia excelsa and Ficus species are recommended.The structure of barley varieties were studied, using structured and semi-structured queries, at Legambo, Tenta and Worailu districts of South Wollo, Ethiopia. Eight local barley varieties (Belg, Ginbot, Sene/Nech, Tikur, Holker, Traveler Tegadime and Temezhi) were identified, and got their names found on seed color and planting season. According to farmers, Tegadime is the production leader among all, but the source of seeds and the market chain are the limiting factors for its popularity and this is why it's not famous is because of the low price of the seed. Thus, Sene/Nech found to be popular and shared 46.91% at Tenta, 48.47% at Legambo and 51.55% at Wereilu followed by Tikur and Ginbote. High barley diversity was noted at Tenta (E = 0.773) followed by Wereilu (E = 0.678) and Legambo (E = 0.606). Sene/Nech (0.67), Belg (0.62), Tegadime (0.59), Tikur (0.55) and Ginbote (0.54) were found to be shared, but Traveler, Holker and Temezhi were rarely found. At farm, most farmers were plowing twice before sowing using horse. Biological fertilizer usages were well practice at Tenta, Legambo and Were'ilu, respectively. While, inorganic fertilizer usage was better at Wereilu, but none at Legambo. Pest management was better at Wereilu and hand weeding is a common system, but low at Legambo, and mowing by sickle, threshing by horse and store in Gotera were a shared practice. Farmers use outdated tools for agricultural practice and the yield is losing due to unavailable of update machinery. So, different managing approaches and new harvesting technologies should address.Polar bears are of international conservation concern due to climate change but are difficult to study because of low densities and an expansive, circumpolar distribution. In a collaborative U.S.-Russian effort in spring of 2016, we used aerial surveys to detect and estimate the abundance of polar bears on sea ice in the Chukchi Sea. Our surveys used a combination of thermal imagery, digital photography, and human observations. Using spatio-temporal statistical models that related bear and track densities to physiographic and biological covariates (e.g., sea ice extent, resource selection functions derived from satellite tags), we predicted abundance and spatial distribution throughout our study area. Estimates of 2016 abundance ([Formula see text]) ranged from 3,435 (95% CI 2,300-5,131) to 5,444 (95% CI 3,636-8,152) depending on the proportion of bears assumed to be missed on the transect line during Russian surveys (g(0)). Our point estimates are larger than, but of similar magnitude to, a recent estimate for the period 2008-2016 ([Formula see text]; 95% CI 1,522-5,944) derived from an integrated population model applied to a slightly smaller area. Although a number of factors (e.g., equipment issues, differing platforms, low sample sizes, size of the study area relative to sampling effort) required us to make a number of assumptions to generate estimates, it establishes a useful lower bound for abundance, and suggests high spring polar bear densities on sea ice in Russian waters south of Wrangell Island. With future improvements, we suggest that springtime aerial surveys may represent a plausible avenue for studying abundance and distribution of polar bears and their prey over large, remote areas.This study compared the results of data collected from a longitudinal query analysis of the MEDLINE database hosted on multiple platforms that include PubMed, EBSCOHost, Ovid, ProQuest, and Web of Science. The goal was to identify variations among the search results on the platforms after controlling for search query syntax. We devised twenty-nine cases of search queries comprised of five semantically equivalent queries per case to search against the five MEDLINE database platforms. We ran our queries monthly for a year and collected search result count data to observe changes. We found that search results varied considerably depending on MEDLINE platform. Reasons for variations were due to trends in scholarly publication such as publishing individual papers online first versus complete issues. Some other reasons were metadata differences in bibliographic records; differences in the levels of specificity of search fields provided by the platforms and large fluctuations in monthly search results based on the same query.