TY - JOUR
T1 - Erratum to
T2 - Design of optimal ecosystem monitoring networks: hotspot detection and biodiversity patterns (Stoch Environ Res Risk Assess, (2015), 29, (1085–1101), 10.1007/s00477-014-0999-8)
AU - Convertino, Matteo
AU - Muñoz-Carpena, Rafael
AU - Kiker, Gregory A.
AU - Perz, Stephen G.
PY - 2017/7/1
Y1 - 2017/7/1
N2 - Unfortunately Fig. 2 caption of this article is incompletely published and the updated caption with the missing citation is given below. Figure 2 Conceptual framework considering biodiversity predicted on a set of networked nodes and its variability in time. In this paper the year-scale predictions are about a and species turnover bt for all the 2028 communities of the MAP subregion (in Fig. 1 within the blue region) as a function of all possible networks of monitored communities. a and bt are predicted for every year t. These can be averaged across space (time series along the t axis), but a richer information is shown by their probability distribution functions (pdfs) that is likely a function of the sub-year environmental variability for ti B t (e.g. local rainfall and climate teleconnections (Davidson et al. 2012), and human disturbances (Perz et al. 2012a). The representation of the conceptual framework is inspired by and created on Fig. 2 of Botter et al. (2011); permission for using such figure is granted by the AGU usage permission policy..
AB - Unfortunately Fig. 2 caption of this article is incompletely published and the updated caption with the missing citation is given below. Figure 2 Conceptual framework considering biodiversity predicted on a set of networked nodes and its variability in time. In this paper the year-scale predictions are about a and species turnover bt for all the 2028 communities of the MAP subregion (in Fig. 1 within the blue region) as a function of all possible networks of monitored communities. a and bt are predicted for every year t. These can be averaged across space (time series along the t axis), but a richer information is shown by their probability distribution functions (pdfs) that is likely a function of the sub-year environmental variability for ti B t (e.g. local rainfall and climate teleconnections (Davidson et al. 2012), and human disturbances (Perz et al. 2012a). The representation of the conceptual framework is inspired by and created on Fig. 2 of Botter et al. (2011); permission for using such figure is granted by the AGU usage permission policy..
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U2 - 10.1007/s00477-017-1422-z
DO - 10.1007/s00477-017-1422-z
M3 - Comment/debate
AN - SCOPUS:85018725741
SN - 1436-3240
VL - 31
JO - Stochastic Environmental Research and Risk Assessment
JF - Stochastic Environmental Research and Risk Assessment
IS - 5
ER -