Ecologists have identified several kinds of pattern in the distribution of species among sites, including a) nested subsets, b) checkerboards, c) Clementsian gradients, d) Gleasonian gradients, and e) evenly spaced gradients. Most past efforts to diagnose such patterns have focused on only one at a time, often contrasted with a sixth type of pattern, f) “randomness”. While there are statistical tests to distinguish each of the first five patterns from randomness, there are currently no established methods for discriminating among these first five patterns in a given data set. Here we propose a method that will identify which of these possibilities is most prevalent in a site‐by‐species incidence matrix based on three basic aspects of meta‐community structure. Our method is based on first ordinating the incidence matrix to identify the dominant axis of variation and identifying three aspects variation along this dominant axis. The first aspect, “coherence”, is the degree to which pattern can be collapsed into a single dimension. The second, “species turnover”, describes the number of species replacements along this dimension. The third aspect, “boundary clumping”, has to do with how the edges of species boundaries are distributed along this dimension. We present methods for analyzing these three aspects of meta‐community structure, use them to identify the six different patterns, and illustrate them with a representative set of cases drawn from previously published data.
Human activity is causing high rates of biodiversity loss. Yet, surprisingly little is known about the extent to which socioeconomic factors exacerbate or ameliorate our impacts on biological diversity. One such factor, economic inequality, has been shown to affect public health, and has been linked to environmental problems in general. We tested how strongly economic inequality is related to biodiversity loss in particular. We found that among countries, and among US states, the number of species that are threatened or declining increases substantially with the Gini ratio of income inequality. At both levels of analysis, the connection between income inequality and biodiversity loss persists after controlling for biophysical conditions, human population size, and per capita GDP or income. Future research should explore potential mechanisms behind this equality-biodiversity relationship. Our results suggest that economic reforms would go hand in hand with, if not serving as a prerequisite for, effective conservation.
Ecologists typically invoke ''law-like'' generalizations, ranging over ''structural'' and/or ''functional'' kinds, in order to explain generalizations about ''historical'' kinds (such as biological taxa)-rather than vice versa. This practice is justified, since structural and functional kinds tend to correlate better with important ecological phenomena than do historical kinds. I support these contentions with three recent case studies. In one sense, therefore, ecology is, and should be, more nomothetic, or law-oriented, than idiographic, or historically oriented. This conclusion challenges several recent philosophical claims about the nature of ecological science.
This study examines changes in some key indicators among 66 countries on six continents over a 56-year period, to compare the power of economic growth to improve human health and income distribution with its tendency to degrade the natural environment. The results indicate that growth depletes and pollutes nature far more than it benefits society. This suggests that public policy should shift toward enhancement of individual and social well-being in ways more direct and effective, and less ecologically damaging, than reliance on overall growth in gross domestic product. I illustrate this implication with a degrowth scenario for the United States to 2050 that draws on the empirical results for the period 1961 to 2016. And I consider certain reforms in the management and governance of organizations to implement such a scenario.
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