Occurrence data on beetles (Coleoptera) collected in Dutch coastal dunes between 1953 and 1960

Background

Historical field data in ecology are exceedingly rare and, therefore, their preservation and publication is of high importance, especially as these data can function as a point of reference for present day biodiversity research. Therefore, we digitised a 65-year-old dataset on ground-dwelling beetles caught with pitfall traps in the coastal dune area "Meijendel", situated in the western part of the Netherlands.

New information

The data presented in this paper has never been published in a systematic way before and has had a long journey from moment of capture to the current digitisation. From 1953 through to 1960, 100 pitfalls were active and catches were collected once a week. A total of 36,400 samples were aggregated with approximately 90,000 occurrences recorded. All captures were identified up to species level and counted and sex determined where possible. The database has been registered in the Global Biodiversity Information Facility (GBIF) and can be found under: https://www.gbif.org/dataset/9d02b439-aa5c-4c22-b1d9-d27fbde9e3ee.

Pest kill rate as aggregate evaluation criterion to rank biological control agents: a case study with Neotropical predators of Tuta absoluta on tomato

Tuta absoluta (Meyrick), a key pest of tomato, is quickly spreading over the world and biological control is considered as one of the control options. Worldwide more than 160 species of natural enemies are associated with this pest, and an important challenge is to quickly find an effective biocontrol agent from this pool of candidate species. Evaluation criteria for control agents are presented, with the advantages they offer for separating potentially useful natural enemies from less promising ones. Next, an aggregate parameter for ranking agents is proposed: the pest kill rate km. We explain why the predator's intrinsic rate of increase cannot be used for comparing the control potential of predators or parasitoids, while km can be used to compare both types of natural enemies. As an example, kill rates for males, females and both sexes combined of three Neotropical mirid species (Campyloneuropsis infumatus (Carvalho), Engytatus varians (Distant) and Macrolophus basicornis (Stål)) were determined, taking all life-history data (developmental times, survival rates, total nymphal and adult predation, sex ratios and adult lifespan) into account. Based on the value for the intrinsic rate of increase (rm) for T. absoluta and for the kill rate km of the predators, we predict that all three predators are potentially able to control the pest, because their km values are all higher than the rm of the pest. Using only km values, we conclude that E. varians is the best candidate for control of T. absoluta on tomato, with C. infumatus ranking second and M. basicornis last.

R0: Host Longevity Matters

The basic reproduction ratio, R₀, is a fundamental concept in epidemiology. It is defined as the total number of secondary infections brought on by a single primary infection, in a totally susceptible population. The value of R₀ indicates whether a starting epidemic reaches a considerable part of the population and causes a lot of damage, or whether it remains restricted to a relatively small number of individuals. To calculate R₀ one has to evaluate an integral that ranges over the duration of the infection of the host. This duration is, of course, limited by remaining host longevity. So, R₀ depends on remaining host longevity and in this paper we show that for long-lived hosts this aspect may not be ignored for long-lasting infections. We investigate in particular how this epidemiological measure of pathogen fitness depends on host longevity. For our analyses we adopt and combine a generic within- and between-host model from the literature. To find the optimal strategy for a pathogen from an evolutionary point of view, we focus on the indicator \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R_0^{{opt}}$$\end{document}R0opt, i.e., the optimum of R₀ as a function of its replication and mutation rates. These are the within-host parameters that the pathogen has at its disposal to optimize its strategy. We show that \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R_0^{{opt}}$$\end{document}R0opt is highly influenced by remaining host longevity in combination with the contact rate between hosts in a susceptible population. In addition, these two parameters determine whether a killer-like or a milker-like strategy is optimal for a given pathogen. In the killer-like strategy the pathogen has a high rate of reproduction within the host in a short time span causing a relatively short disease, whereas in the milker-like strategy the pathogen multiplies relatively slowly, producing a continuous small amount of offspring over time with a small effect on host health. The present research allows for the determination of a bifurcation line in the plane of host longevity versus contact rate that forms the boundary between the milker-like and killer-like regions. This plot shows that for short remaining host longevities the killer-like strategy is optimal, whereas for very long remaining host longevities the milker-like strategy is advantageous. For in-between values of host longevity, the contact rate determines which of both strategies is optimal.

Development of a pathway model to assess the exposure of European pine trees to pine wood nematode via the trade of wood

Pine wood nematode (PWN), Bursaphelenchus xylophilus, is a threat for pine species (Pinus spp.) throughout the world. The nematode is native to North America, and invaded Japan, China, Korea, and Taiwan, and more recently Portugal and Spain. PWN enters new areas through trade in wood products. Once established, eradication is not practically feasible. Therefore, preventing entry of PWN into new areas is crucial. Entry risk analysis can assist in targeting management to reduce the probability of entry. Assessing the entry of PWN is challenging due to the complexity of the wood trade and the wood processing chain. In this paper, we develop a pathway model that describes the wood trade and wood processing chain to determine the structure of the entry process. We consider entry of PWN through imported coniferous wood from China, a possible origin of Portuguese populations, to Europe. We show that exposure increased over years due to an increase in imports of sawn wood. From 2000 to 2012, Europe received an estimated 84 PWN propagules from China, 88% of which arose from imported sawn wood and 12% from round wood. The region in Portugal where the PWN was first reported is among those with the highest PWN transfer per unit of imported wood due to a high host cover and vector activity. An estimated 62% of PWN is expected to enter in countries where PWN is not expected to cause the wilt of pine trees because of low summer temperatures (e.g., Belgium, Sweden, Norway). In these countries, PWN is not easily detected, and such countries can thus serve as potential reservoirs of PWN. The model identifies ports and regions with high exposure, which helps targeting monitoring and surveillance, even in areas where wilt disease is not expected to occur. In addition, we show that exposure is most efficiently reduced by additional treatments in the country of origin, and/or import wood from PWN-free zones. Pathway modelling assists plant health managers in analyzing risks along the pathway and planning measures for enhancing biosecurity.

Quantification of motility of carabid beetles in farmland

Quantification of the movement of insects at field and landscape levels helps us to understand their ecology and ecological functions. We conducted a meta-analysis on movement of carabid beetles (Coleoptera: Carabidae), to identify key factors affecting movement and population redistribution. We characterize the rate of redistribution using motility μ (L2 T-1), which is a measure for diffusion of a population in space and time that is consistent with ecological diffusion theory and which can be used for upscaling short-term data to longer time frames. Formulas are provided to calculate motility from literature data on movement distances. A field experiment was conducted to measure the redistribution of mass-released carabid, Pterostichus melanarius in a crop field, and derive motility by fitting a Fokker-Planck diffusion model using inverse modelling. Bias in estimates of motility from literature data is elucidated using the data from the field experiment as a case study. The meta-analysis showed that motility is 5.6 times as high in farmland as in woody habitat. Species associated with forested habitats had greater motility than species associated with open field habitats, both in arable land and woody habitat. The meta-analysis did not identify consistent differences in motility at the species level, or between clusters of larger and smaller beetles. The results presented here provide a basis for calculating time-varying distribution patterns of carabids in farmland and woody habitat. The formulas for calculating motility can be used for other taxa.

Modelling the impact of HIV on the populations of South Africa and Botswana

We develop and use mathematical models that describe changes in the South African population over the last decades, brought on by HIV and AIDS. We do not model all the phases in HIV progression but rather, we show that a relatively simple model is sufficient to represent the data and allows us to investigate important aspects of HIV infection: firstly, we are able to investigate the effect of awareness on the prevalence of HIV and secondly, it enables us to make a comparison between South Africa and Botswana. A comparison is made between two models: a model that does not reflect awareness of the devastating impact of HIV and AIDS, and a model with an added psychological awareness factor. Both models are fitted to data that reflects the incidence of HIV and AIDS within South Africa. This allows us to examine the impact of psychological awareness. We show that inclusion of the effect of awareness is absolutely necessary to arrive at a model description that satisfactorily fits the available HIV and AIDS data for South Africa. We also show that a relatively simple modelling of awareness (as opposed to more complex mathematical techniques that have been used in past studies) is sufficient to accurately describe the observed patterns in the data. Even though awareness alone is not sufficient to eradicate any disease and other control strategies should be explored and implemented concurrently with educational campaigns, we are able to conclude (through thorough model analyses procedures) that the current level of awareness in South Africa is far below the level that is effectively required to eradicate HIV from the South African population. The awareness model is also fitted to HIV-related data for Botswana and we compare the results with the South African case. Though the effect of awareness is currently estimated at a much higher level in Botswana, other factors such as poorer health care and cultural differences may play a role in limiting the ability of awareness to combat HIV in Botswana.

Quantifying abortion rates of reproductive organs and effects of contributing factors using time-to-event analysis

Time-to-event analysis, or survival analysis, is a method to analyse the timing of events and to quantify the effects of contributing factors. We apply this method to data on the timing of abortion of reproductive organs. This abortion often depends on source and sink strength. We hypothesise that the effect of source and sink strength on abortion rate can be quantified with a statistical model, obtained via survival analysis. Flower and fruit abortion in Capsicum annuum L., observed in temperature and planting density experiments, were analysed. Increasing the source strength as well as decreasing the sink strength decreased the abortion rate. The effect was non-linear, e.g. source strengths above 6g CH2O per plant per d did not decrease abortion rates further. The maximum abortion rate occurred around 100 degree-days after anthesis. Analyses in which sink strength was replaced with the number of fruits in a specified age category had an equal or better fit to the data. We discuss the advantages and disadvantages of using survival analyses for this kind of data. The technique can also be used for other crops showing reproductive organ abortion (e.g. soybean (Glycine max L.), cucumber (Cucumis sativus L.)), but also on other event types like bud break or germination.

Empirical and theoretical challenges in aboveground-belowground ecology

A growing body of evidence shows that aboveground and belowground communities and processes are intrinsically linked, and that feedbacks between these subsystems have important implications for community structure and ecosystem functioning. Almost all studies on this topic have been carried out from an empirical perspective and in specific ecological settings or contexts. Belowground interactions operate at different spatial and temporal scales. Due to the relatively low mobility and high survival of organisms in the soil, plants have longer lasting legacy effects belowground than aboveground. Our current challenge is to understand how aboveground-belowground biotic interactions operate across spatial and temporal scales, and how they depend on, as well as influence, the abiotic environment. Because empirical capacities are too limited to explore all possible combinations of interactions and environmental settings, we explore where and how they can be supported by theoretical approaches to develop testable predictions and to generalise empirical results. We review four key areas where a combined aboveground-belowground approach offers perspectives for enhancing ecological understanding, namely succession, agro-ecosystems, biological invasions and global change impacts on ecosystems. In plant succession, differences in scales between aboveground and belowground biota, as well as between species interactions and ecosystem processes, have important implications for the rate and direction of community change. Aboveground as well as belowground interactions either enhance or reduce rates of plant species replacement. Moreover, the outcomes of the interactions depend on abiotic conditions and plant life history characteristics, which may vary with successional position. We exemplify where translation of the current conceptual succession models into more predictive models can help targeting empirical studies and generalising their results. Then, we discuss how understanding succession may help to enhance managing arable crops, grasslands and invasive plants, as well as provide insights into the effects of global change on community re-organisation and ecosystem processes.

Empirical and theoretical challenges in aboveground-belowground ecology

A growing body of evidence shows that aboveground and belowground communities and processes are intrinsically linked, and that feedbacks between these subsystems have important implications for community structure and ecosystem functioning. Almost all studies on this topic have been carried out from an empirical perspective and in specific ecological settings or contexts. Belowground interactions operate at different spatial and temporal scales. Due to the relatively low mobility and high survival of organisms in the soil, plants have longer lasting legacy effects belowground than aboveground. Our current challenge is to understand how aboveground-belowground biotic interactions operate across spatial and temporal scales, and how they depend on, as well as influence, the abiotic environment. Because empirical capacities are too limited to explore all possible combinations of interactions and environmental settings, we explore where and how they can be supported by theoretical approaches to develop testable predictions and to generalise empirical results. We review four key areas where a combined aboveground-belowground approach offers perspectives for enhancing ecological understanding, namely succession, agro-ecosystems, biological invasions and global change impacts on ecosystems. In plant succession, differences in scales between aboveground and belowground biota, as well as between species interactions and ecosystem processes, have important implications for the rate and direction of community change. Aboveground as well as belowground interactions either enhance or reduce rates of plant species replacement. Moreover, the outcomes of the interactions depend on abiotic conditions and plant life history characteristics, which may vary with successional position. We exemplify where translation of the current conceptual succession models into more predictive models can help targeting empirical studies and generalising their results. Then, we discuss how understanding succession may help to enhance managing arable crops, grasslands and invasive plants, as well as provide insights into the effects of global change on community re-organisation and ecosystem processes.

Evaluation of surveillance strategies for bovine tuberculosis (Mycobacterium bovis) using an individual based epidemiological model

The Netherlands holds the bovine tuberculosis-free (BTB-free) status according to European Union standards, but in recent years small outbreaks of the infection have occurred. After the last outbreak in 1999 with 10 infected herds the question raised if the current surveillance system, visual inspection of carcasses at the slaughterhouse, is efficient enough to detect infected cattle in time and to maintain the official BTB-free status. Through epidemiological modelling, the risk of a major outbreak is quantified, using one of six surveillance strategies. These are the currently used visual inspection of carcasses at the slaughterhouse (SL), the ELISA test on blood samples of carcasses at the slaughterhouse (ELISA-B), the gamma-interferon test on blood samples of carcasses at the slaughterhouse (GAMMA-B), comparative tuberculination of the herd (CT), the combined method of single and comparative tuberculination of the herd (ST+CT) and the ELISA test on samples of bulk milk (ELISA-M). Test frequency of the last three methods was varied as well. A stochastic individual based model (IBM) was developed to simulate a chain of infected herds, where each individual animal is followed in time. The model mimics the nation-wide situation after the introduction of one infected animal into one herd. BTB-transmission is simulated with an S-E(1)-E(2)-I state transition model. Output is time until detection of the infection, prevalence in the detected herd and the number of infected herds at the time of detection. For the assessment 500 simulations were used, representing 500 BTB-introductions. Model robustness to parameter values was analysed with Monte Carlo elasticity analysis, for which 1000 simulations were used. Results of median time until detection and median number of infected farms at detection for SL (302 weeks and seven farms) were in agreement with estimates from an outbreak in the Netherlands in 1999. ELISA-B and GAMMA-B performed better than SL with a much lower median time until detection (189 and 97 weeks, respectively). The results for the tuberculination methods (ST+CT and CT) and ELISA-M depended heavily on the frequency in which the tests were performed. The tuberculination methods ST+CT and CT yield comparable results and detect the infection sooner than SL, also at the lowest tested frequency of once in 5 years. ELISA-M is comparable with SL at frequencies of once in 4 or 5 years, and this test works well at frequencies of once a year or higher. Our study results are used for an economical optimisation analysis of the six surveillance strategies.

A two-component model of host-parasitoid interactions: determination of the size of inundative releases of parasitoids in biological pest control

A two-component differential equation model is formulated for a host-parasitoid interaction. Transient dynamics and population crashes of this system are analysed using differential inequalities. Two different cases can be distinguished: either the intrinsic growth rate of the host population is smaller than the maximum growth rate of the parasitoid or vice versa. In the latter case, the initial ratio of parasitoids to hosts should exceed a given threshold, in order to (temporarily) halt the growth of the host population. When not only oviposition but also host-feeding occurs the dynamics do not change qualitatively. In the case that the maximum growth rate of the parasitoid population is smaller than the intrinsic growth rate of the host, a threshold still exists for the number of parasitoids in an inundative release in order to limit the growth of the host population. The size of an inundative release of parasitoids, which is necessary to keep the host population below a certain level, can be determined from the two-component model. When parameter values for hosts and parasitoids are known, an effective control of pests can be found. First it is determined whether the parasitoids are able to suppress their hosts fully. Moreover, using our simple rule of thumb it can be assessed whether suppression is also possible when the relative growth rate of the host population exceeds that of the parasitoid population. With a numerical investigation of our simple system the design of parasitoid release strategies for specific situations can be computed.

Superparasitism as an ESS: to reject or not to reject, that is the question

A stochastic model is formulated to determine the optimal strategy for a solitary parasitoid which has discovered an already parasitized host. The model assumes that the parasitoid can count both the number of eggs already present in a host and the number of conspecifics searching in the same patch. The survival probability of an egg is assumed to depend on the total number of eggs in a host. The decision to (super)parasitize depends both on the degree to which the discovered host already is parasitized and on the number of conspecific females searching in the same patch. We consider both the case that egg laying does not involve any costs for the parasitoid and the case that it involves some marginal costs. Uniform behaviour of all the conspecific parasitoids in a patch, i.e. laying one additional egg in all encountered larvae containing a particular number of eggs, appears to be a pure evolutionary stable strategy (ESS). If either the probability that a parasitoid emerges from a host decreases with an increasing degree of parasitism, at least from a particular number of eggs onwards, or if parasitism involves marginal costs, the maximum number of eggs for which it is still profitable to superparasitize a host once more is limited. This number increases with the number of conspecifics searching in the patch. Large marginal costs (i.e. the expected gain of not parasitizing now) decrease the profit of superparasitism. For newly emerged parasitoids the rejection of an already parasitized host is not advantageous as long as the marginal costs of parasitism are small, because the host can never contain an egg of its own.