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A robust scientific conclusion is the result of a rigorous scientific process. In observational ecology, this process involves making inferences about a population from 20 a sample. The sample is crucial, and is the result of implementing a survey design. A good survey design ensures that the data from the survey is capable of answering the research question. An even better design, such as spatially balanced designs, will also aim to reduce uncertainty as far as budgets will allow.
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In many study areas, there are `legacy sites', that already have a time-series observed, and return visits to these sites are beneficial to enhance examination of temporal variability. We propose a method to incorporate these legacy sites into the survey effort whilst also maintaining spatial balance. This is the first formal method to perform this task.
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Simulation experiments indicate that incorporating the spatial location of legacy sites increases spatial balance and decreases uncertainty in inferences (smaller standard errors in mean estimates). We illustrate the process using a proposed survey of a large marine reserve in South-Eastern Australia, where quantification of the reserve's biodiversity is required.
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Our approach allows for integration of legacy sites into a new spatially-balanced 35 design, increasing efficiency. Scientists, managers and funders alike will benefit from this methodology { it provides a tool to provide efficient survey designs around established ones. In this way, it can aid integrated monitoring programs. An R-package that implements these methods, called MBHdesign, is available from CRAN.
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&lt;b&gt;Citation:&lt;/b&gt; Foster, S.D., Hosack, G.R., Lawrence, E., Przeslawski, R., Hedge, P., Caley, M.J., Barrett, N.S., Williams, A., Li, J., Lynch, T., Dambacher, J.M., Sweatman, H.P.A. and Hayes, K.R. (2017), Spatially balanced designs that incorporate legacy sites. &lt;i&gt;Methods Ecol Evol&lt;/i&gt;, 8: 1433-1442. https://doi.org/10.1111/2041-210X.12782</gco:CharacterString>
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