Conservation planning for successional landscapes

The systematic conservation planning literature invariably assumes that the biodiversity features being preserved in sites do not change through time. We develop a conservation planning framework for ecosystems where disturbance events and succession drive vegetation dynamics. The framework incorporates three key attributes of disturbance theory: heterogeneity in disturbance rates, spatial correlation between disturbance events and different impacts of disturbance. In our conservation problem we wish to maximise the chance that we represent a certain number of successional types given a cap on the number of sites we can conserve. Correlation between disturbance events dramatically complicates the problem of choosing the optimal suite of sites. However, in our problem we discover that spatial correlation in disturbances affects the optimal reserve network very little. The reason is twofold: (i) through our probabilistic framework we focus on the long-term effectiveness of reserve networks and (ii) in the dynamics considered in our model the state of a site is not only affected by the most recent (correlated) disturbance event but also by the site's long-term stochastic history which blurs the impact of spatial correlation. If successional states are the conservation target rather than individual species then, conserving a site can only contribute to meeting one target. However, given that correlation of disturbance events may be ignored, we show that if the number of candidate reserves is sufficiently large the statistical dependence of different conservation targets may be ignored, too. We conclude that the computational complexity of reserve selection methods for dynamic ecosystems can be much simpler than they first appear.     

Patchy Distribution Fields: Sampling Distance Unit of a Spiral Survey and Reconstruction Adequacy

A mathematical model is used to examine the effects of choosing various units of sampling distance of a spiral acoustic survey on the adequacy of reconstructing patchy distribution fields. The model simulates fish or plankton patches (or gaps) of different shapes and spatial orientations, and an acoustic survey by a spiral of Archimedes along which a unit of sampling distance is set. For comparison, surveys are imitated by parallel transects along which the same unit of sampling distance is set. Adequacy of the reconstructed fields to those originally generated is evaluated by calculating their correlations (r). In the case of a spiral survey, the mathematical experiments conducted show that an immovable field can be reconstructed properly (r ² > 0.70) if the ratio of the units of sampling distance to the autocorrelation radius for the field averaged in various directions d/R _av < 1.0–1.5. Regarding immovable fields, the spiral surveys ensure, practically speaking, the same adequacy of the field reconstruction as do surveys by parallel transects with the same unit of sampling distance. In regard to movable fields, a comparison of the results of spiral surveys with those of surveys by parallel transects indicates that the former may ensure even higher adequacy of the field reconstruction than do the latter, provided that the units of sampling distances in these surveys are equal to each other.     

Patchy distribution fields: A spiral survey design and reconstruction adequacy

A mathematical model was used to examine the effects of a spiral survey design on the adequacy of reconstructing patchy distribution fields. The model simulates fish or plankton patches (or gaps) of different shapes and spatial orientations, and acoustic surveys by a spiral of Archimedes; for comparison, surveys by parallel or zigzag transects are imitated. Adequacy of the reconstructed fields to those originally generated was evaluated by calculating their correlations (r). The mathematical experiments conducted showed that spiral surveys ensure, practically speaking, the same adequacy of field reconstruction (both in cases of immovable or movable patches) as do surveys by parallel or zigzag transects with greater sampling effort (overall path). In the case of a spiral survey, a patchy field can be reconstructed properly (r² = 0.70) if the overall survey path is not less than S/R_av = 20–30, where R_av is the autocorrelation radius averaged for various directions. Thus, the results obtained allow us to conclude that a spiral survey design is expedient in cases that the minimal duration of a survey is a decisive factor for its conduction and there is a priori information that no onshore-offshore gradients of fish density exist in a region under study.