Determining the underlying structure of insular isolation measures

Aim: Island isolation is measured in many ways. We seek to determine what the underlying latent factors characterizing these measures are, in order to understand how they mechanistically drive island biogeographical patterns and in order to recommend the most parsimonious measures. We then test the discriminatory power of the identified components against hypotheses generated from the biogeographical patterns of invasive rats. Location: The 890 offshore islands (≥1 hectare area) of the New Zealand archipelago (latitude: 34.1–47.3°S, longitude: 166.2–178.4°E). Taxon: Mammals. Methods: We identified 16 measures that have been frequently used to characterize isolation in the past, including Euclidean-based distance metrics, landscape connectivity metrics derived from least-cost and circuit theory modelling, landscape buffers, stepping stones and insular area. We used principal components analysis (PCA) to synthesize the underlying structure of insular isolation with respect to terrestrial mammal dispersal. Finally, we tested the discriminatory power of retained principal components (PCs) using permutational multivariate analyses of variance (PERMANOVA). Tests include comparison of historical rat distributions, islands targeted for rat eradication and islands reinvaded by rats. Results: The underlying structure of island isolation as characterized in the 16 metrics was described by three independent PCA components. Variable clustering suggests that PC1 captured distance from the mainland source to the focal island (PC1 Distance), PC2 described stepping stones available along the dispersal pathway (PC2 Stepping Stones) and PC3 described the focal island's position in the landscape (PC3 Insular Network). Each discriminatory test affirmed its respective biogeographical pattern hypothesis. Main conclusions: The three underlying components we identify form the basis of a robust description of insular isolation that is of broad importance to understanding island biogeography dynamics. Moreover, these components can be applied across taxa without extensive structural or functional assumptions because the highest loading variables are not biologically informed.</p

Incorporating management action suitability in conservation plans

Conservation decision makers must negotiate social and technical complexities to achieve desired biodiversity outcomes. Quantitative models can inform decision making, by evaluating and predicting management outcomes, so that comparisons can be made between alternative courses of action. However, whether a proposed action is appropriate for implementation, regardless of its contribution to management outcomes, also requires consideration. Existing quantitative models have yet to fully incorporate the suitability of proposed management actions, which hinders their ability to inform decision making. We used gradient boosted decision trees – a machine-learning technique – to determine the suitability of alternative management actions available to a biodiversity conservation programme. We demonstrate our approach using the Predator Free 2050 programme – a large and complex conservation initiative that seeks to eradicate selected invasive vertebrates from the entirety of New Zealand by 2050. We created a nationally contiguous network of management tools to suppress populations of invasive species across the entire country. We then used our suitability predictions to explore three scenarios for selecting invasive species management tools, based on maximising (a) implementation probability, (b) humaneness and (c) cost-savings. Our models highlighted that an interplay of factors influence where management tools can potentially be implemented. Our management scenarios revealed what different contiguous management networks could look like for New Zealand over the next 10–15 years as an interim step to achieving Predator Free 2050. Each scenario differed in the tools selected for implementation in different places and in the overall economic costs associated with creating a contiguous management network. Some locations were identified as unsuitable for any existing management tools, indicating that future transformative technologies may be required to create a contiguous network. Synthesis and applications. Conservation decision making must not only consider biodiversity outcomes but also whether selected management actions are appropriate in the first place. Here, we used machine-learning techniques to determine the suitability of competing managements actions that are proposed to meet biodiversity objectives. Our approach provides an objective, transparent and reproducible framework to determine the suitability of actions at sites across large spatial extents, under complex social and technical constraints.</p

Identification of isochromatic fringes - Simple guidelines are presented to number isochromatic fringes in static- and dynamic-photoelastic problems

In simple cases of static-photoelastic analysis, the numbering of the isochromatic fringes does not present unusual difficulties. In more complex cases, in particular wave propagation, the problem may be so difficult that few investigators attempt the analysis. In this paper guidelines to number the isochromatic fringes are presented. Advantage is taken of some topological properties as well as of the time and space derivatives of these isochromatic fringes. Several examples are discussed to illustrate the use of the guidelines. It is observed that under most conditions the guidelines are sufficient to number the whole field of isochromatics on photographs taken with the commonly used monochromatic light. © 1983 Society for Experimental Mechanics, Inc