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      Environmental and anthropogenic factors synergistically affect space use of jaguars

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      Current Biology
      Elsevier BV

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          WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas

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            Is Open Access

            Fitting Linear Mixed-Effects Models Using lme4

            Maximum likelihood or restricted maximum likelihood (REML) estimates of the parameters in linear mixed-effects models can be determined using the lmer function in the lme4 package for R. As for most model-fitting functions in R, the model is described in an lmer call by a formula, in this case including both fixed- and random-effects terms. The formula and data together determine a numerical representation of the model from which the profiled deviance or the profiled REML criterion can be evaluated as a function of some of the model parameters. The appropriate criterion is optimized, using one of the constrained optimization functions in R, to provide the parameter estimates. We describe the structure of the model, the steps in evaluating the profiled deviance or REML criterion, and the structure of classes or types that represents such a model. Sufficient detail is included to allow specialization of these structures by users who wish to write functions to fit specialized linear mixed models, such as models incorporating pedigrees or smoothing splines, that are not easily expressible in the formula language used by lmer. Journal of Statistical Software, 67 (1) ISSN:1548-7660
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              High-resolution global maps of 21st-century forest cover change.

              Quantification of global forest change has been lacking despite the recognized importance of forest ecosystem services. In this study, Earth observation satellite data were used to map global forest loss (2.3 million square kilometers) and gain (0.8 million square kilometers) from 2000 to 2012 at a spatial resolution of 30 meters. The tropics were the only climate domain to exhibit a trend, with forest loss increasing by 2101 square kilometers per year. Brazil's well-documented reduction in deforestation was offset by increasing forest loss in Indonesia, Malaysia, Paraguay, Bolivia, Zambia, Angola, and elsewhere. Intensive forestry practiced within subtropical forests resulted in the highest rates of forest change globally. Boreal forest loss due largely to fire and forestry was second to that in the tropics in absolute and proportional terms. These results depict a globally consistent and locally relevant record of forest change.
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                Author and article information

                Journal
                Current Biology
                Current Biology
                Elsevier BV
                09609822
                August 2021
                August 2021
                : 31
                : 15
                : 3457-3466.e4
                Article
                10.1016/j.cub.2021.06.029
                7e45221e-0203-4135-be7a-32c95e33d26c
                © 2021

                https://www.elsevier.com/tdm/userlicense/1.0/

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