On Ecosystem Dynamics for the Conservation of Wetlands and Forest

The chapter provides statistical backgrounds, based on recent research on ecosystem dynamics, for why we should be interested in forest conservation in general and, in particular, why in Chile it can play a tremendously important role. The authors show how a dynamical system (DS) given by a t-score function for some class of monotonic data transformations generates consistent extreme value estimators. The variation of their values increases the uncertainty of a proper assessment of climate change. We experience singular learning of the transitions in ecosystems, and as complexity measures, we will consider both entropy and fractal dimension. The chapter shows applications to wetlands, which are a poster example of biodiversity, endemism, and conservation challenges. It also provides an analysis of the dynamics of methane emissions from Czech wetlands in South Bohemia, as a comparing example. Together, these cases illustrate the complexity of the conservation process (The results obtained will be an integral part of the Chilean project FONDECYT 2015–2019, N1151441: Statistical and mathematical modelling as a knowledge bridge between Society and Ecology Sustainability,” in synergy with the Linz Institute of Technology Project LIT-2016-1-SEE-023: Modeling complex dependencies: how to make strategic multicriterial decisions?)

[1]  E. Odum.  The strategy of ecosystem development. , 1969, Science.

[2]  A. Tansley.  The Use and Abuse of Vegetational Concepts and Terms , 1935 .

[3]  J. Dušek,et al.  Extreme precipitation and long-term precipitation changes in a Central European sedge-grass marsh in the context of flood occurrence , 2017 .

[4]  Jürgen Kurths,et al.  Recurrence plots for the analysis of complex systems , 2009 .

[5]  Baofeng Cai,et al.  An Optimization Model for a Wetland Restoration Project under Uncertainty , 2018, International journal of environmental research and public health.

[6]  J. Zbilut,et al.  Embeddings and delays as derived from quantification of recurrence plots , 1992 .

[7]  Milan Stehlík,et al.  On ecosystems dynamics , 2017 .

[8]  A. Muñoz-Pedreros,et al.  Legal protection assessment of different inland wetlands in Chile , 2014, Revista Chilena de Historia Natural.

[9]  Timo Kuuluvainen,et al.  Conceptual models of forest dynamics in environmental education and management: keep it as simple as possible, but no simpler , 2016, Forest Ecosystems.

[10]  D. Ruelle,et al.  Recurrence Plots of Dynamical Systems , 1987 .

[11]  Milan Stehlík,et al.  Missing chaos in global climate change data interpreting , 2016 .

[12]  Frederic E. Clements,et al.  Research methods in ecology , 1905 .

[13]  Li He,et al.  Ecological vulnerability assessment for ecological conservation and environmental management. , 2018, Journal of environmental management.

[14]  J. Kurths,et al.  Recurrence-plot-based measures of complexity and their application to heart-rate-variability data. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[15]  K. P. Reese,et al.  LANDSCAPE CHANGES WITHIN THE HISTORICAL DISTRIBUTION OF COLUMBIAN SHARP-TAILED GROUSE IN EASTERN WASHINGTON : IS THERE HOPE? , 1998 .

[16]  J. Dušek,et al.  Long‐term air temperature changes in a Central European sedge‐grass marsh , 2013 .

[17]  Zdeněk Fabián,et al.  INDUCED CORES AND THEIR USE IN ROBUST PARAMETRIC ESTIMATION , 2001 .

[18]  Joseph P. Zbilut,et al.  Use of Recurrence Quantification Analysis in Economic Time Series , 2005 .

[19]  A. Huth,et al.  The importance of forest structure to biodiversity–productivity relationships , 2017, Royal Society Open Science.

[20]  D. White,et al.  Modeling the suitability of wetland restoration potential at the watershed scale , 2005 .

[21]  Milan Stehlík,et al.  On the favorable estimation for fitting heavy tailed data , 2010, Comput. Stat..