Radar studies of the vertical distribution of insects migrating over southern Britain: the influence of temperature inversions on nocturnal layer concentrations

Insects migrating over two sites in southern UK (Malvern in Worcestershire, and Harpenden in Hertfordshire) have been monitored continuously with nutating vertical-looking radars (VLRs) equipped with powerful control and analysis software. These observations make possible, for the first time, a systematic investigation of the vertical distribution of insect aerial density in the atmosphere, over temporal scales ranging from the short (instantaneous vertical profiles updated every 15 min) to the very long (profiles aggregated over whole seasons or even years). In the present paper, an outline is given of some general features of insect stratification as revealed by the radars, followed by a description of occasions during warm nights in the summer months when intense insect layers developed. Some of these nocturnal layers were due to the insects flying preferentially at the top of strong surface temperature inversions, and in other cases, layering was associated with higher-altitude temperature maxima, such as those due to subsidence inversions. The layers were formed from insects of a great variety of sizes, but peaks in the mass distributions pointed to a preponderance of medium-sized noctuid moths on certain occasions

Species abundance dynamics under neutral assumptions: a Bayesian approach to the controversy

1. Hubbell's 'Unified Neutral Theory of Biodiversity and Biogeography' (UNTB) has generated much controversy about both the realism of its assumptions and how well it describes the species abundance dynamics in real communities. 2. We fit a discrete-time version of Hubbell's neutral model to long-term macro-moth (Lepidoptera) community data from the Rothamsted Insect Survey (RIS) light-traps network in the United Kingdom. 3. We relax the assumption of constant community size and use a hierarchical Bayesian approach to show that the model does not fit the data well as it would need parameter values that are impossible. 4. This is because the ecological communities fluctuate more than expected under neutrality. 5. The model, as presented here, can be extended to include environmental stochasticity, density-dependence, or changes in population sizes that are correlated between different species

What drives community dynamics?

The search for general mechanisms of community assembly is a major focus of community ecology. The common practice so far has been to examine alternative assembly theories using dichotomist approaches of the form neutrality versus niche, or compensatory dynamics versus environmental forcing. In reality, all these mechanisms will be operating, albeit with different strengths. While there have been different approaches to community structure and dynamics, including neutrality and niche differentiation, less work has gone into separating out the temporal variation in species abundances into relative contributions from different components. Here we use a refined statistical machinery to decompose temporal fluctuations in species abundances into contributions from environmental stochasticity and inter-/intraspecific interactions, to see which ones dominate. We apply the methodology to community data from a range of taxa. Our results show that communities are largely driven by environmental fluctuations, and that member populations are, to different extents, regulated through intraspecific interactions, the effects of interspecific interactions remaining broadly minor. By decomposing the temporal variation in this way, we have been able to show directly what has been previously inferred indirectly: compensatory dynamics are in fact largely outweighed by environmental forcing, and the latter tends to synchronize the population dynamics

Flight periodicity and the vertical distribution of high-altitude moth migration over southern Britain

The continuous operation of insect-monitoring radars in the UK has permitted, for the first time, the characterization of various phenomena associated with high-altitude migration of large insects over this part of northern Europe. Previous studies have taken a case-study approach, concentrating on a small number of nights of particular interest. Here, combining data from two radars, and from an extensive suction- and light-trapping network, we have undertaken a more systematic, longer-term study of diel flight periodicity and vertical distribution of macro-insects in the atmosphere. Firstly, we identify general features of insect abundance and stratification, occurring during the 24-hour cycle, which emerge from four years' aggregated radar data for the summer months in southern Britain. These features include mass emigrations at dusk and, to a lesser extent, at dawn and daytime concentrations associated with thermal convection. We then focus our attention on the well-defined layers of large nocturnal migrants that form in the early evening, usually at heights of 200–500 m above ground. We present evidence from both radar and trap data that these nocturnal layers are composed mainly of noctuid moths, with species such as Noctua pronuba, Autographa gamma, Agrotis exclamationis, A. segetum, Xestia c-nigrum and Phlogophora meticulosa predominating

Providing the evidence base for environmental risk assessments of novel farm management practices

An environmental risk assessment of a new agricultural management practice depends upon the provision of empirical evidence of cause and effect. This will invariably be derived from comparative experiments testing the null hypothesis that a change in management will have no effect on an assessment endpoint (the metric on which policy decisions will be based). Crucial to the design of these experiments is the answer to the question of 'what to measure?'. The selection of these measurement endpoints and the design of sampling protocols will be determined by the properties of the environmental stressors associated with the change in management practice and the taxa that are exposed to their effects, as well as logistic and financial considerations. The rationale for deciding what to measure in the context of these various criteria is reviewed. For a measurement endpoint to be a valid indicator of the risk of a negative impact of management on the assessment endpoint, a predictable and quantifiable link must be made between the two. It should also be recorded at the appropriate taxonomic resolution to safely assume that all the constituent parts will both respond in a similar way to the management stressor and have a similar effect on the assessment endpoint. Protocols must be designed with the spatial and temporal properties of the management stressor and the measurement endpoint in mind and a consideration of the statistical power of the experiment to detect changes. Where there is a lag in the response time of a measurement endpoint to a stressor due to inertia in the system, an accurate measurement of the effect of the novel management may require experiments running over several years. Throughout, care must be taken that the statistical and biological validity of a sampling regime is not compromised in the face of logistic and financial pressures. The Farm Scale Evaluations of the management of Genetically Modified Herbicide Tolerant crops are presented as a case study to illustrate the concepts discusse

Detection of delayed density dependence in an orchid population

1 Annual censuses of Orchis morio (green-winged orchid) flowering spikes have been taken over a 27-year period in a replicated factorial experiment on the effects of fertilizer application. Census data, combined by block or treatment, were used in time-series analyses to test for density dependence. 2 Partial autocorrelation functions revealed the importance of positive correlations at lag 1 and negative correlations at lag 5. Stepwise multiple regressions provided evidence of delayed density dependence, again with a delay of about 5 years, with no evidence of direct (first-order) density dependence. 3 First-order autocorrelations and delayed density dependence were considered in the light of the known stage structure and generation time of the plant and the possibility of density dependence at different points in the life history. 4 Model structure affects the detection of density dependence, increasing the propensity for type I errors