A novel method for quantifying overdispersion in count data and its application to farmland birds

The statistical modelling of count data permeates the discipline of ecology. Such data often exhibit overdispersion compared with a standard Poisson distribution, so that the variance of the counts is greater than that of the mean. Whereas modelling to reveal the effects of explanatory variables on the mean is commonplace, overdispersion is generally regarded as a nuisance parameter to be accounted for and subsequently ignored. Instead, we propose a method that models the overdispersion as a biologically interesting property of a data set and show how novel inference is provided as a result. We adapted the double hierarchical generalized linear model approach to create an easily extendible model structure that quantifies the influence of explanatory variables on the overdispersion of count data, and apply it to farmland birds. These data were from a study within Irish agricultural ecosystems, in which total bird species abundance and the abundance of farmland indicator species were compared on dairy and non‐dairy farms in the winter and breeding seasons. In general, overdispersion in bird counts was greater on dairy farms than on non‐dairy farms, and for total bird numbers, overdispersion was greatest on dairy farms in winter. Our code is fitted using the Bayesian package Rstan, and we make all code and data available in a GitHub repository. Within a Bayesian framework, this approach facilitates a meaningful quantification of the effects of categorical explanatory variables on any response variable with a tendency to overdispersion that has a meaningful biological or ecological explanation.     

Dietary self‐selection and rules of compromise by fifth‐instar Vanessa cardui

We examined dietary self‐selection and rules of compromise for protein (P) and digestible carbohydrate (C) intake by fifth‐instar Vanessa cardui L. (Lepidoptera: Nymphalidae: Nymphalini). We presented six fat‐free diet pairs to larvae in a choice trial to determine the ‘intake target’. In addition, we fed larvae seven fat‐free single diets differing in dietary nutrient ratio in no‐choice trials to determine the rules of compromise they exhibit when constrained to a singular, sub‐optimal dietary source. In choice trials, caterpillars regulated nutrient intake to a ratio of 1 protein to 1.09 carbohydrate (1P:1.09C), exhibiting tighter regulation of protein than of carbohydrate. Furthermore, larvae from different diet pair treatments did not differ in pupal mass or stadium duration. In no‐choice experiments, larvae reduced consumption on increasingly protein‐biased diets and increased consumption on increasingly carbohydrate‐biased diets, relative to a 1P:1C ratio diet. Differences in carbohydrate consumption were much greater between no‐choice treatments than differences in protein consumption. Dietary nutrient ratio affected pupal mass when accounting for initial larval mass. Pupal mass decreased as nutrient ratio was shifted off of 1P:1C, but to a greater extent when the ratio was skewed toward carbohydrate. Stadium duration increased as nutrient ratio diverged from 1P:1C, being more pronounced when shifted toward carbohydrate than toward protein. Regulation to near 1P:1C is consistent with results found for other Lepidoptera, and the rule of compromise exhibited by V. cardui is consistent with that expected for a generalist herbivore.     

Beta diversity of stream fish assemblages: partitioning variation between spatial and environmental factors

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Spatiotemporal assessment of rainstorm hazard risk in Qinling mountains of China

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Explaining Industrial Symbiosis Emergence,Development, and Disruption: A Multilevel Analytical Framework

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Improved retrieval of Secchi depth for optically-complex waters using remote sensing data

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A Risk Assessment Framework for Waterborne Pathogens and Requirements for Producing a Complete Protocol

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