Comparing forest governance models against invasive biological threats. (English) Zbl 1406.92657

Dragicevic, Arnaud Z.

J. Theor. Biol. 462, 270-282 (2019).

Summary: In order to take account of the negative effects of invasive species and pathogens on networked forest areas, we study the dynamics of stochastic closed-loop input-output systems faced with the risk of external random perturbations. The extension of previous works on robustness is carried out by introducing a negative feedback mechanism, such that the output from an element contained in the system behaves as a negative input toward elements to which it is connected. Through the study of an overall network divided into compartments barely connected to one another, we first consider the pathway pertaining to monofunctional zoning. By looking at a single aggregated structure, we then move our focus to the pathway proper to multifunctionality. Our results show that, at significant time scales, the monofunctional-zoning mode of forest governance, generally applied in Australasia, performs robustly against invasive biological threats at all levels of outbreak probability. The multifunctional mode of forest governance, further practiced in Western Europe, is mainly sturdy when the probability of invasion verges into certainty. Should this not be the case, robustness is ensured would disturbers and perturbations be uncorrelated. Accordingly, the monofunctional pathway can afford adopting control strategies for outbreak avoidance, which is only acceptable in case the expected invasion can be halted. For the sake of maintaining low likelihood of invasion, the multifunctional pathway is compelled to applying preventive strategies.

MSC:

92D40	Ecology
92C80	Plant biology
92C42	Systems biology, networks
93D25	Input-output approaches in control theory
93B52	Feedback control
91B76	Environmental economics (natural resource models, harvesting, pollution, etc.)

Keywords:

bioeconomics; invasive species; pathogens; forest governance; input-output systems; negative feedback; networks; robustness; sustainability

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