Efektivitas Metode Sq4r (Survey, Question, Read, Reflect, Recite, Review) Dalam Pembelajaran Memahami Teks Feature Kelas VII SMP Negeri 1 Sidikalang Tahun Pembelajaran 2012/2013

This study aims to determine the effectiveness of the method SQ4R(Survey, Question, Read, Reflect, Recite, Review) in learning to understand thetext feature class VII SMP Negeri 1 Sidikalang many as 253 people. Samplestaken as many as 74 people from the two classes, class of 37 people to 37 peoplefor the experiment and the control class.The method used in this study is an experimental method, which is todetermine the effectiveness of the teaching methods used. Data collection tool wasa written test in the form of multiple choices (multiple-choice).Learning outcomes using SQ4R (Survey, Question, Read, Reflect, Recite,Review) is in both categories with an average value of 72.97. When compared tolearning by teaching methods directly in the category of simply average value of55.10.Analysis of data management in this study using the test "t". Furthermore,the hypothesis derived from the test calculations thitung = 3.37 and TTable at 5%significance level = 1.67 and at 1% significance level = 2.39, with db = 74-2 = 72,used db closest to 72 . Hypothesis is accepted if to> TTable (1.67 2.39).Thus, the hypothesis is accepted. It states that the method SQ4R (Survey,Question, Read, Reflect, Recite, Review) is more effective to apply in learning tounderstand the text feature class VII SMP Negeri 1 Sidikalang learning year2012/2013

BioTIME:a database of biodiversity time series for the Anthropocene

Abstract Motivation: The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community‐led open‐source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene. Main types of variables included: The database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record. Spatial location and grain: BioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km² (158 cm²) to 100 km² (1,000,000,000,000 cm²). Time period and grain: BioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year. Major taxa and level of measurement: BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates. Software format: .csv and .SQL

BioTIME:a database of biodiversity time series for the Anthropocene

Motivation: The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community led open-source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene.Main types of variables included: The database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of two, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology andcontextual information about each record.Spatial location and grain: BioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km2 (158 cm2) to 100 km2 (1 000 000 000 000 cm2).Time period and grain: BioTIME records span from 1874 to 2016. The minimum temporal grain across all datasets in BioTIME is year.Major taxa and level of measurement: BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton, and terrestrial invertebrates to small and large vertebrates.Software format: .csv and .SQ

Are rare species useful species? Obstacles to the conservation of tree diversity in the dry forest zone agro-ecosystems of Mesoamerica

Aim To test the potential to conserve rare dry forest tree and shrub species circa situm.Location Oaxaca, Mexico and Southern Honduras.Methods Local uses (timber, posts and firewood) of species were determined principally through semistructured interviews with 20 rural householders in each of four communities in Honduras and four in Oaxaca. Tree and shrub diversity inventories were carried out in a total of 227 forest patches and parcels of farmland in those eight communities. Species’ conservation priorities were determined using the star system of Hawthorne (1996) and IUCN listings.Results Despite a large number of useful species, remarkably few were also conservation priorities. Useful species were found to be substitutable as is illustrated by Bombacopsis quinata, Cordia alliodora, Guaiacum sanctum and G. coulteri.Conclusions In these areas, circa situm conservation is inhibited by the lack of species that are both rare and useful. Usefulness must be interpreted as a function of substitutability. Natural regeneration provides an abundance of diversity, farmers are unlikely to invest in the management of a species when suitable substitutes are freely available. The key to conserving rare species may be in maintaining or enhancing the value of the landscape elements in which they are found