D
David L. Miller
Researcher at University of St Andrews
Publications - 36
Citations - 1297
David L. Miller is an academic researcher from University of St Andrews. The author has contributed to research in topics: Distance sampling & Population. The author has an hindex of 14, co-authored 30 publications receiving 791 citations. Previous affiliations of David L. Miller include University of Lisbon & University of Rhode Island.
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Hierarchical generalized additive models in ecology: an introduction with mgcv
TL;DR: An extension to two popular approaches to modeling complex structures in ecological data: the generalized additive model (GAM) and the hierarchical model (HGLM), which allows modeling of nonlinear functional relationships between covariates and outcomes where the shape of the function itself varies between different grouping levels.
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Spatial models for distance sampling data: recent developments and future directions
TL;DR: This work considers spatial modelling techniques that may be advantageous to applied ecologists such as quantification of uncertainty in a two-stage model and smoothing in areas with complex boundaries and considers a popular approach based on generalized additive models.
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Distance sampling in R
TL;DR: This work introduces the R package Distance that implements distance sampling methods to estimate abundance and describes how users can obtain estimates of abundance using the package as well as documenting the links it provides with other more specialized R packages.
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Extrapolating cetacean densities to quantitatively assess human impacts on populations in the high seas.
TL;DR: P plausible density estimates can inform management needs in the high seas, such as the quantification of potential cetacean interactions with military training exercises, shipping, fisheries, and deep‐sea mining and be used to delineate areas of special biological significance in international waters.
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A spatial conservation prioritization approach for protecting marine birds given proposed offshore wind energy development
TL;DR: In this paper, the authors developed spatial distribution models of marine birds from aerial surveys that were conducted from 2010 to 2012 throughout a 3800 km 2 area off the coast of Rhode Island, and integrated their spatial models, along with uncertainty, using spatial conservation prioritization (SCP) software.