Analysing Ecological Data

Abstract

Which test should I apply?' During the many years of working with ecologists, biologists and other environmental scientists, this is probably the question that the authors of this book hear the most often. The answer is always the same and along the lines of 'What are your underlying questions?', 'What do you want to show?'. The answers to these questions provide the starting point for a detailed discussion on the ecological background and purpose of the study. This then gives the basis for deciding on the most appropriate analytical approach. Therefore, a better starting point for an ecologist is to avoid the phrase 'test' and think in terms of 'analysis'. A test refers to something simple and unified that gives a clear answer in the form of a p-value: something rarely appropriate for ecological data. In practice, one has to apply a data exploration, check assumptions, validate the models, perhaps apply a series of methods, and most importantly, interpret the results in terms of the underlying ecology and the ecological questions being investigated. Ecology is a quantitative science trying to answer difficult questions about the complex world we live in. Most ecologists are aware of these complexities, but few are fully equipped with the statistical sophistication and understanding to deal with them. Even data gathered from apparently simple ecological research can require a level of statistical awareness rarely taught at the undergraduate or even the postgraduate level. There is little enough time to teach the essentials of ecology, let alone finding the time to teach 'advanced' statistics. Hopefully, for post graduates moving into academia there will be some advanced statistical support available, but many ecologist end up working in government, a voluntary organisation or consultancy where statistical support is minimal. Although, the authors of this book believe that a quantitative approach is at the core of being a good ecologist, they also appreciate how challenging many ecologists find statistics. This book is therefore aimed at three levels of reader. At one level it is aimed at making ecologists aware of how important it is to design scientifically robust ecological experiments or monitoring programmes, and the importance of selecting the best analytical technique. For these readers we hope the book, in particular the case studies, will encourage them to develop their personal statistical skills, or convince them they need statistical support. On the next level it is aimed at the statistically literate ecologist, who may not be fully aware of the techniques we discuss, or when to use them. Hopefully, we have explained things well enough for these readers to feel confident enough to use some of the techniques we describe. Often these techniques are presented in a

Contribution of Topography and Incident Solar Radiation to Variation of Soil and Plant Litter at an Area with Heterogeneous Terrain

“…Incident solar radiation and space (spatial filters) were also related to each separate soil and litter property with regressions to determine how much of their variation could be explained by each of these two explanatory factors. Final models were obtained by keeping the spatial filters, which minimized the Akaike Information Criterion (AIC) and increased the homogeneity of residual distribution (Zuur et al, 2007(Zuur et al, , 2009). …”

Overlap in distribution and diets of Atlantic mackerel (Scomber scombrus), Norwegian spring-spawning herring (Clupea harengus) and blue whiting (Micromesistius poutassou) in the Norwegian Sea during late summer

“…To assess co-linearity we used pairwise scatterplots, correlation coefficients, and variance inflation factors (VIF). The highest correlation coefficient of 0.61 (observed between Calanus finmarchicus CIVÁVI and Zooplankton biomass) and highest VIF of 3.95 (Longitude) were considered acceptable and none of the variables were omitted from further analysis (Zuur et al 2007). The statistical significance of the canonical axes was tested by Monte-Carlo permutation test (499 permutations) (ter Braak & Š milauer 2002).…”

Landscape genetics identifies streams and drainage infrastructure as dispersal corridors for an endangered wetland bird

“…This precipitous decline was eventually halted with legal protection, the establishment of National Wildlife Refuges and state protected areas on these two islands, and the advent of habitat management (predator control and vegetation restoration). The implementation of the latter is associated with a slow but consistent recovery of Hawaii's endangered waterbirds over the last 50 years (Reed, Elphick, Ieno, & Zuur, 2011; Reed, Elphick, Zuur, Ieno, & Smith, 2007; Schwartz & Schwartz, 1949; Underwood, Silbernagle, Nishimoto, & Uyehara, 2013). O`ahu's current gallinule population consists of between 250 and 350 individuals scattered among relict and fragmented wetlands, which are isolated by severe wetland loss on the island (van Rees & Reed, 2014; USFWS, 2011).…”