Tropical vegetationTropical vegetation is any vegetation in tropical latitudes. Plant life that occurs in climates that are warm year-round is in general more biologically diverse that in other latitudes. Some tropical areas may receive abundant rain the whole year round, but others have long dry seasons which last several months and may vary in length and intensity with geographic location. These seasonal droughts have great impact on the vegetation, such as in the Madagascar spiny forests. Rainforest vegetation is categorized by five layers.
Biodiversity lossBiodiversity loss includes the worldwide extinction of different species, as well as the local reduction or loss of species in a certain habitat, resulting in a loss of biological diversity. The latter phenomenon can be temporary or permanent, depending on whether the environmental degradation that leads to the loss is reversible through ecological restoration/ecological resilience or effectively permanent (e.g. through land loss).
Biodiversity hotspotA biodiversity hotspot is a biogeographic region with significant levels of biodiversity that is threatened by human habitation. Norman Myers wrote about the concept in two articles in The Environmentalist in 1988 and 1990, after which the concept was revised following thorough analysis by Myers and others into “Hotspots: Earth’s Biologically Richest and Most Endangered Terrestrial Ecoregions” and a paper published in the journal Nature, both in 2000.
Tropical and subtropical dry broadleaf forestsThe tropical and subtropical dry broadleaf forest is a habitat type defined by the World Wide Fund for Nature and is located at tropical and subtropical latitudes. Though these forests occur in climates that are warm year-round, and may receive several hundred centimeters of rain per year, they have long dry seasons that last several months and vary with geographic location. These seasonal droughts have great impact on all living things in the forest.
Standard deviationIn statistics, the standard deviation is a measure of the amount of variation or dispersion of a set of values. A low standard deviation indicates that the values tend to be close to the mean (also called the expected value) of the set, while a high standard deviation indicates that the values are spread out over a wider range. Standard deviation may be abbreviated SD, and is most commonly represented in mathematical texts and equations by the lower case Greek letter σ (sigma), for the population standard deviation, or the Latin letter s, for the sample standard deviation.
Regression analysisIn statistical modeling, regression analysis is a set of statistical processes for estimating the relationships between a dependent variable (often called the 'outcome' or 'response' variable, or a 'label' in machine learning parlance) and one or more independent variables (often called 'predictors', 'covariates', 'explanatory variables' or 'features'). The most common form of regression analysis is linear regression, in which one finds the line (or a more complex linear combination) that most closely fits the data according to a specific mathematical criterion.
Old-growth forestAn old-growth forest, sometimes synonymous with primary forest, virgin forest, late seral forest, primeval forest, first-growth forest, or mature forestis a forest that has attained great age without significant disturbance, and thereby exhibits unique ecological features, and might be classified as a climax community. The Food and Agriculture Organization of the United Nations defines primary forests as naturally regenerated forests of native tree species where there are no clearly visible indications of human activity and the ecological processes are not significantly disturbed.
Logistic regressionIn statistics, the logistic model (or logit model) is a statistical model that models the probability of an event taking place by having the log-odds for the event be a linear combination of one or more independent variables. In regression analysis, logistic regression (or logit regression) is estimating the parameters of a logistic model (the coefficients in the linear combination).
Linear regressionIn statistics, linear regression is a linear approach for modelling the relationship between a scalar response and one or more explanatory variables (also known as dependent and independent variables). The case of one explanatory variable is called simple linear regression; for more than one, the process is called multiple linear regression. This term is distinct from multivariate linear regression, where multiple correlated dependent variables are predicted, rather than a single scalar variable.
Alpha diversityIn ecology, alpha diversity (α-diversity) is the mean species diversity in a site at a local scale. The term was introduced by R. H. Whittaker together with the terms beta diversity (β-diversity) and gamma diversity (γ-diversity). Whittaker's idea was that the total species diversity in a landscape (gamma diversity) is determined by two different things, the mean species diversity in sites at a more local scale (alpha diversity) and the differentiation among those sites (beta diversity).
