Correlations between weather conditions and common vole (Microtus arvalis) densities identified by regression tree analysis

Exploring the influence of density-dependence and weather on the spatial and temporal variation in common vole (Microtus arvalis) abundance in Castilla y León, NW Spain

BACKGROUND

The common vole has invaded the agroecosystems of northwestern Spain, where outbreaks cause important crop damage and management costs. Little is yet known about the factors causing or modulating vole fluctuations. Here, we used 11 years of vole abundance monitoring data in 40 sites to study density-dependence and weather influence on vole dynamics. Our objective was to identify the population dynamics structure and determine whether there is direct or delayed density-dependence. An evaluation of climatic variables followed, to determine whether they influenced vole population peaks.

RESULTS

First- and second-order outbreak dynamics were detected at 7 and 33 study sites, respectively, together with second-order variability in periodicity (2-3 to 4-5-year cycles). Vole population growth was explained by previous year abundance (mainly numbers in summer and spring) at 21 of the sites (52.5%), by weather variables at 11 sites (27.5%; precipitation or temperature in six and five sites, respectively), and by a combination of previous abundance and weather variables in eight sites (20%).

CONCLUSIONS

We detected variability in vole spatiotemporal abundance dynamics, which differs in cyclicity and period. We also found regional variation in the relative importance of previous abundances and weather as factors modulating vole fluctuations. Most vole populations were cyclical, with variable periodicity across the region. Our study is a first step towards the development of predictive modeling, by disclosing relevant factors that might trigger vole outbreaks. It improves decision-making processes within integrated management dealing with mitigation of the agricultural impacts caused by voles. © 2023 Society of Chemical Industry.

Spatiotemporal and Individual Patterns of Domestic Cat (Felis catus) Hunting Behaviour in France

Domestic cats (Felis catus), one of the most popular pets, are widespread worldwide. This medium-sized carnivore has well-known negative effects on biodiversity, but there is still a need to better understand the approximate causes of their predation. Based on a citizen science project, we assessed the role of spatiotemporal (i.e., latitude, longitude, and seasons), climatic (i.e., rainfall), anthropogenic (i.e., human footprint, HFI), and individual (i.e., sex and age) variables on the number of preys returned home by cats in metropolitan France. Over the 5048 cats monitored between 2015 and 2022, prey from 12 different classes (n = 36,568) were returned home: 68% mammals, 21% birds, and 8% squamates. Shrews brought home by cats peaked during summer, while rodents were recorded during summer-autumn. Birds brought home by cats peaked in spring-summer and in autumn, and lizards peaked in spring and in late summer. Lower HFI was associated with more voles and mice brought home, and the opposite trend was observed for lizards and birds. Younger cats were more prone to bring home shrews, birds, and reptiles. Although environmental factors play a minor role in prey brought home by cats, some geographical characteristics of prey species distribution partly explains the hunting behaviour of cats.

Machine learning identifies straightforward early warning rules for human Puumala hantavirus outbreaks

Human Puumala virus (PUUV) infections in Germany fluctuate multi-annually, following fluctuations of the bank vole population size. We applied a transformation to the annual incidence values and established a heuristic method to develop a straightforward robust model for the binary human infection risk at the district level. The classification model was powered by a machine-learning algorithm and achieved 85% sensitivity and 71% precision, despite using only three weather parameters from the previous years as inputs, namely the soil temperature in April of two years before and in September of the previous year, and the sunshine duration in September of two years before. Moreover, we introduced the PUUV Outbreak Index that quantifies the spatial synchrony of local PUUV-outbreaks, and applied it to the seven reported outbreaks in the period 2006-2021. Finally, we used the classification model to estimate the PUUV Outbreak Index, achieving 20% maximum uncertainty.

The status of fertility control for rodents-recent achievements and future directions

Management of overabundant rodents at a landscape scale is complex but often required to sustainably reduce rodent abundance below damage thresholds. Current conventional techniques such as poisoning are not species specific, with some approaches becoming increasingly unacceptable to the general public. Fertility control, first proposed for vertebrate pest management over 5 decades ago, has gained public acceptance because it is perceived as a potentially more species-specific and humane approach compared with many lethal methods. An ideal fertility control agent needs to induce infertility across one or more breeding seasons, be easily delivered to an appropriate proportion of the population, be species specific with minimal side-effects (behavioral or social structure changes), and be environmentally benign and cost effective. To date, effective fertility control of rodents has not been demonstrated at landscape scales and very few products have achieved registration. Reproductive targets for fertility control include disrupting the hormonal feedback associated with the hypothalamic-pituitary-gonadal axis, gonad function, fertilization, and/or early implantation. We review progress on the oral delivery of various agents for which laboratory studies have demonstrated efficacy in females and/or males and synthesize progress with the development and/or use of synthetic steroids, plant extracts, ovarian specific peptides, and immunocontraceptive vaccines. There are promising results for field application of synthetic steroids (levonorgestrel, quinestrol), chemosterilants (4-vinylcyclohexene diepoxide), and some plant extracts (triptolide). For most fertility control agents, more research is essential to enable their efficient and cost-effective delivery such that rodent impacts at a population level are mitigated and food security is improved.

Spatial and Temporal Dynamics and Molecular Evolution of Tula orthohantavirus in German Vole Populations

Tula orthohantavirus (TULV) is a rodent-borne hantavirus with broad geographical distribution in Europe. Its major reservoir is the common vole (Microtus arvalis), but TULV has also been detected in closely related vole species. Given the large distributional range and high amplitude population dynamics of common voles, this host-pathogen complex presents an ideal system to study the complex mechanisms of pathogen transmission in a wild rodent reservoir. We investigated the dynamics of TULV prevalence and the subsequent potential effects on the molecular evolution of TULV in common voles of the Central evolutionary lineage. Rodents were trapped for three years in four regions of Germany and samples were analyzed for the presence of TULV-reactive antibodies and TULV RNA with subsequent sequence determination. The results show that individual (sex) and population-level factors (abundance) of hosts were significant predictors of local TULV dynamics. At the large geographic scale, different phylogenetic TULV clades and an overall isolation-by-distance pattern in virus sequences were detected, while at the small scale (<4 km) this depended on the study area. In combination with an overall delayed density dependence, our results highlight that frequent, localized bottleneck events for the common vole and TULV do occur and can be offset by local recolonization dynamics.

Weather influences M. arvalis reproduction but not population dynamics in a 17-year time series

Rodent outbreaks have plagued European agriculture for centuries, but continue to elude comprehensive explanation. Modelling and empirical work in some cyclic rodent systems suggests that changes in reproductive parameters are partly responsible for observed population dynamics. Using a 17-year time series of Microtus arvalis population abundance and demographic data, we explored the relationship between meteorological conditions (temperature and rainfall), female reproductive activity, and population growth rates in a non-cyclic population of this grassland vole species. We found strong but complex relationships between female reproduction and climate variables, with spring female reproduction depressed after cold winters. Population growth rates were, however, uncorrelated with either weather conditions (current and up to three months prior) or with female reproduction (number of foetuses per female and/or proportion of females reproductively active in the population). These results, coupled with age-structure data, suggest that mortality, via predation, disease, or a combination of the two, are responsible for the large multi-annual but non-cyclic population dynamics observed in this population of the common vole.

Prioritizing Highway Safety Manual's crash prediction variables using boosted regression trees

The Highway Safety Manual (HSM) recommends using the empirical Bayes (EB) method with locally derived calibration factors to predict an agency's safety performance. However, the data needs for deriving these local calibration factors are significant, requiring very detailed roadway characteristics information. Many of the data variables identified in the HSM are currently unavailable in the states' databases. Moreover, the process of collecting and maintaining all the HSM data variables is cost-prohibitive. Prioritization of the variables based on their impact on crash predictions would, therefore, help to identify influential variables for which data could be collected and maintained for continued updates. This study aims to determine the impact of each independent variable identified in the HSM on crash predictions. A relatively recent data mining approach called boosted regression trees (BRT) is used to investigate the association between the variables and crash predictions. The BRT method can effectively handle different types of predictor variables, identify very complex and non-linear association among variables, and compute variable importance. Five years of crash data from 2008 to 2012 on two urban and suburban facility types, two-lane undivided arterials and four-lane divided arterials, were analyzed for estimating the influence of variables on crash predictions. Variables were found to exhibit non-linear and sometimes complex relationship to predicted crash counts. In addition, only a few variables were found to explain most of the variation in the crash data.

[Monitoring populations of rodent reservoirs of zoonotic diseases. Projects, aims and results]

Rodents can harbor and transmit pathogens that can cause severe disease in humans, companion animals and livestock. Such zoonotic pathogens comprise more than two thirds of the currently known human pathogens. The epidemiology of some zoonotic pathogens, such as hantaviruses, can be linked to the population dynamics of the rodent host. In this case, during an outbreak of the rodent host population many human infections may occur. In other rodent-borne zoonotic diseases such phenomena are not known and in many cases the rodent host specificity of a given pathogen is unclear. The monitoring of relevant rodent populations and of the rodent-borne zoonotic pathogens is essential to (1) understand the distribution and epidemiology of pathogens and (2) develop forecasting tools to predict outbreaks of zoonoses. Presently, there are no systematic long-term monitoring programs in place for zoonoses in Germany. Rodent monitoring activities are largely restricted to the plant protection sector, such as for the common vole (Microtus arvalis) and forest-damaging rodents. However, during the last 10-15 years a number of specific research projects have been initiated and run for a few years and Norway rat (Rattus norvegicus) monitoring has been implemented in Hamburg and Lower Saxony. Based on close cooperation of federal and state authorities and research institutions these efforts could be utilized to gain information about the distribution and importance of rodent-borne zoonoses. Nevertheless, for the integration of rodent population dynamics and zoonotic disease patterns and especially for developing predictive models, long-term monitoring is urgently required. To establish a systematic long-term monitoring program, existing networks and cooperation need to be used, additional collaborators (e.g., pest control operators) should be included and synergetic effects of different scientific fields should be utilized.

Quantifying the past and future impact of climate on outbreak patterns of bank voles (Myodes glareolus)

BACKGROUND

Central European outbreak populations of the bank vole (Myodes glareolus Schreber) are known to cause damage in forestry and to transmit the most common type of Hantavirus (Puumala virus, PUUV) to humans. A sound estimation of potential effects of future climate scenarios on population dynamics is a prerequisite for long-term management strategies. Historic abundance time series were used to identify the key weather conditions associated with bank vole abundance, and were extrapolated to future climate scenarios to derive potential long-term changes in bank vole abundance dynamics.

RESULTS

Classification and regression tree analysis revealed the most relevant weather parameters associated with high and low bank vole abundances. Summer temperatures 2 years prior to trapping had the highest impact on abundance fluctuation. Extrapolation of the identified parameters to future climate conditions revealed an increase in years with high vole abundance.

CONCLUSION

Key weather patterns associated with vole abundance reflect the importance of superabundant food supply through masting to the occurrence of bank vole outbreaks. Owing to changing climate, these outbreaks are predicted potentially to increase in frequency 3-4-fold by the end of this century. This may negatively affect damage patterns in forestry and the risk of human PUUV infection in the long term.