{"refrec":{"BRefID":406680,"RR":"<b>Carrasco De La Cruz, P.M.</b> (2025). Computation of functional diversity from long-term monitoring time series. PhD Thesis. Carl von Ossietzky Universität Oldenburg: Oldenburg. xii, 104 pp.","BEntID":404478,"PublicFlag":1,"CheckedFlag":0,"wosflag":0,"vabbflag":0,"RefStringPartII":". PhD Thesis. Carl von Ossietzky Universität Oldenburg: Oldenburg.  xii, 104 pp.","DocTypID":5,"DocType":"Book/Monograph","MarineFlag":0,"FreshFlag":0,"BrackishFlag":0,"TerrestrialFlag":0,"Authorstring":"Carrasco De La Cruz, P.M.","OrigTitleTranslFlag":0,"Authorstringtrunc":"Carrasco De La Cruz, P.M.","Englishabstract":"Biodiversity was initially concerned with the amount of species; however, its focus has shifted towards considering the influence those species and their interactions have on the functionality of ecosystems. An approach known as functional biodiversity. This new approach requires measurements of species traits, a task which is often complicated and remains underdeveloped. An innovative solution is to inferred those traits from monitoring time series, which gathered data on biomass or abundance of species. Using a method known as Diffusion maps, high-dimensional datasets are turned to a lower, more relevant dimensional space, in which species can be located and assessed according to their similarity or dissimilarity. The result is a functional diversity time series of the monitored ecosystem, and the ecological community. 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