![]() Next we predict the Species Area Relationship and Endemics Area Relationship (SAR and EAR). In addition to returning the inputs (in analogy, e.g., to common model fitting functions such as lm), it returns the Lagrange multipliers from entropy maximization as well as information about the fitting procedure. The returned object (of class meteESF) contains useful information. This is necessary for the underlying mathematics as discussed in Harte (2011). Without loss of generality, metabolic rates are re-scaled by this minimum such that the minimum possible observable metabolic rate is 1. Further, note that we specified the minimum value for the metabolic rate, but that the minimum observed value will be taken by default. Note that we use the terms ‘power’ and ‘metabolic rate’ interchangeably (units of power are energy/time and thus an energetic rate). $ mesage : chr "x-values within tolerance 'xtol'" METE computes this distribution by maximizing information entropy relative to the constraints of \(N_0/S_0\) and \(E_0/S_0\) using the method of Lagrange multipliers. \(R(n, e)\) describes the joint probability of observing a species with \(n\) individuals and a randomly chosen member of that species having metabolic rate \(e\). If data are not provided, the values for the state variables can be directly specified by the user (see Case Study 3).Īnalysis begins by building the ecosystem structure function (ESF \(R(n,e)\)) from which all non-spatial macroecological metrics can be derived. There are two main reasons to provide data to meteR: (1) meteR will calculate the state variables \(N_0\) (number of individuals), \(S_0\) (number of species), \(E_0\) (total metabolic rate) and relevant summary statistics automatically (2) these data are used by meter to compare against predictions. ![]() For an example of such formatting see the data set anbo, included with meteR, discussed in the next section. If multiple individuals of the same size from the same species are observed (and lumped into one record), these can be specified as well, i.e., by letting arth$count be something other than 1. This data set illustrates one data format used by meteR each row represents an individual, with an observation of its metabolic rate (note that we convert mass to metabolic rate using the usual relationship of Metabolic Scaling Theory such that metabolic rate \(M \propto mass^\)).
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