ABSTRACT
We develop a generalized linear mixed model (GLMM) for bivariate count responses for statistically analyzing dragonfly population data from the Northern Netherlands. The populations of the threatened dragonfly species Aeshna viridis were counted in the years 2015-2018 at 17 different locations (ponds and ditches). Two different widely applied population size measures were used to quantify the population sizes, namely the number of found exoskeletons ('exuviae') and the number of spotted egg-laying females were counted. Since both measures (responses) led to many zero counts but also feature very large counts, our GLMM model builds on a zero-inflated bivariate geometric (ZIBGe) distribution, for which we show that it can be easily parameterized in terms of a correlation parameter and its two marginal medians. We model the medians with linear combinations of fixed (environmental covariates) and random (location-specific intercepts) effects. Modeling the medians yields a decreased sensitivity to overly large counts; in particular, in light of growing marginal zero inflation rates. Because of the relatively small sample size (n = 114) we follow a Bayesian modeling approach and use Metropolis-Hastings Markov Chain Monte Carlo (MCMC) simulations for generating posterior samples.
ABSTRACT
Both sexes of Onychogomphus boudoti sp. nov. Ferreira (Odonata: Anisoptera: Gomphidae) and exuviae are described and illustrated from a single locality in Morocco. This newly discovered species differs markedly from other Onychogomphus species by the morphology of the male epiproct and the female vulvar scale. It is genetically distinct in the mitochondrial DNA and the nuclear PRMT gene from all other Western Palaearctic Onychogomphus species. The known distribution of the new species is confined to a small stream with unusual habitat characteristics in the vicinity of Khenifra, in the Middle Atlas, where it experiences low population size and limited genetic diversity. We suggest listing this species both locally and globally as "Critically Endangered" [CR (B1, B2 + abiii)] following the IUCN Red List Categories and Criteria.