Dying like rabbits: general determinants of spatio-temporal variability in survival

Down a Rabbit Hole: Burrowing Behaviour and Larger Home Ranges are Related to Larger Brains in Leporids

Studies on the evolution of brain size variation usually focus on large clades encompassing broad phylogenetic groups. This risks introducing ‘noise’ in the results, often obscuring effects that might be detected in less inclusive clades. Here, we focus on a sample of endocranial volumes (endocasts) of 18 species of rabbits and hares (Lagomorpha: Leporidae), which are a discrete radiation of mammals with a suitably large range of body sizes. Using 60 individuals, we test five popular hypotheses on brain size and olfactory bulb evolution in mammals. We also address the pervasive issue of missing data, using multiple phylogenetic imputations as to conserve the full sample size for all analyses. Our analyses show that home range and burrowing behaviour are the only predictors of leporid brain size variation. Litter size, which is one of the most widely reported constraints on brain size, was unexpectedly not associated with brain size. However, a constraining effect may be masked by a strong association of litter size with temperature seasonality, warranting further study. Lastly, we show that unreasonable estimations of phylogenetic signal (Pagel’s lamba) warrant additional caution when using small sample sizes, such as ours, in comparative studies.

A Simplified Population-Level Landscape Model Identifying Ecological Risk Drivers of Pesticide Applications, Part One: Case Study for Large Herbivorous Mammals

Environmental risk assessment is a key process for the authorization of pesticides, and is subjected to continuous challenges and updates. Current approaches are based on standard scenarios and independent substance-crop assessments. This arrangement does not address the complexity of agricultural ecosystems with mammals feeding on different crops. This work presents a simplified model for regulatory use addressing landscape variability, co-exposure to several pesticides, and predicting the effect on population abundance. The focus is on terrestrial vertebrates and the aim is the identification of the key risk drivers impacting on mid-term population dynamics. The model is parameterized for EU assessments according to the European Food Safety Authority (EFSA) Guidance Document, but can be adapted to other regulatory schemes. The conceptual approach includes two modules: (a) the species population dynamics, and (b) the population impact of pesticide exposure. Population dynamics is modelled through daily survival and seasonal reproductions rates; which are modified in case of pesticide exposure. All variables, parameters, and functions can be modified. The model has been calibrated with ecological data for wild rabbits and brown hares and tested for two herbicides, glyphosate and bromoxynil, using validated toxicity data extracted from EFSA assessments. Results demonstrate that the information available for a regulatory assessment, according to current EU information requirements, is sufficient for predicting the impact and possible consequences at population dynamic levels. The model confirms that agroecological parameters play a key role when assessing the effect of pesticide exposure on population abundance. The integration of laboratory toxicity studies with this simplified landscape model allows for the identification of conditions leading to population vulnerability or resilience. An Annex includes a detailed assessment of the model characteristics according to the EFSA scheme on Good Modelling Practice.

Forecast increase in invasive rabbit spread into ecosystems of an oceanic island (Tenerife) under climate change

The European rabbit (Oryctolagus cuniculus) is a pest and a conservation problem on many islands, where its heavy grazing pressure threatens many endemic plants with extinction. Previous studies in its native and introduced range have highlighted the high spatial variability of rabbit abundance at local and landscape scales, depending on many factors such as the existence of different habitats. Modeling of the species can be useful to better understand spatial patterns and to prioritize actions, especially in those regions in which rabbits have become invasive. Here, we investigate the distribution of the European rabbit in Tenerife (Canary Islands, Spain), where the species was introduced during the 15th century and has subsequently changed vegetation composition. Added to the direct effects of rabbits on vegetation, climate change could also have implications for rabbit populations, especially in the alpine ecosystem. To evaluate that, we estimated rabbit abundance in 216 plots randomly distributed on Tenerife island (61 in the alpine ecosystem), modeled the potential current spatial abundance of the species and considered how it might vary under different climate change scenarios. We associated rabbit abundance to a wide selection of abiotic, biotic, and human variables expected to influence rabbit abundance on the island. We found a positive correlation between rabbit abundance and temperature and a negative correlation in the case of precipitation. Hence, according to the models' projections, climate change is expected to enhance rabbit populations in the future. Current higher densities were related to land disturbance and open areas, and a remarkable increase is expected to occur in the alpine ecosystem. Overall, we consider that this study provides valuable information for land managers in the Canary archipelago as it reveals how global warming could indirectly exacerbate the conservation problems of the endemic flora in oceanic islands.

Use of artificial neural network to model reproductive performance and mortality of non-descript rabbits

This study was carried out to predict average number of kits per birth and mortality number of non-descript rabbits in Plateau State, Nigeria using artificial neural network (ANN). Data were obtained from a total of 100 rabbit farmers. The predicted mean value for number of kits per birth using ANN (6.60) was similar to the observed value (6.52). As regards mortality, the predicted mean value using ANN (17.75) was also similar to the observed value (17.80). Primary occupation, experience in rabbit keeping, flock size and credit type were the parameters of utmost importance in predicting number of kits per birth. The fairly high coefficient of determination (R2) (55.7%) and low root mean square error (RMSE) value of 1.22 conferred reliability on the ANN model. The R2 value obtained in the prediction of mortality using ANN implies that 61.1% of the variation in the number of mortality can be largely explained by the explanatory variables such as flock size, age of farmers, experience in rabbit keeping and average number of kits per birth. The low RMSE value of 3.82 also gave credence to the regression model. The present information may be exploited in taking appropriate management decisions to boost production.

Kill rates by rabbit hunters before and 16 years after introduction of rabbit haemorrhagic disease in the southern South Island, New Zealand

Context European rabbits (Oryctolagus cuniculus) are serious economic and environmental pests in Australia and New Zealand. Since the illegal introduction of rabbit haemorrhagic disease virus (RHDV) in New Zealand in 1997, the disease has persisted in most rabbit populations, with major epizootics occurring usually each autumn. Aims We evaluated the efficacy of the virus as a biological control agent in the southern South Island. Methods We used an index of rabbit abundance (kills per hunter) based on a region-wide annual rabbit-hunting competition to evaluate rabbit population trends 7 years before and 16 years after the first outbreak of RHD. We also evaluated the influence of rainfall and temperature in the preceding year on post-RHD trends in the index. Key results Kill rates declined by 60% following the initial epizootic. They remained low for the following 3 years and then increased steadily to intermediate levels punctuated by occasional declines. The instantaneous rate of increase in kill rates during the increase phase was low, but above zero (0.04 per year). No relationship between kill rates and rainfall was apparent, but there was a negative relationship between kill rates and winter temperature in the preceding season. Conclusions The kill-rate data obtained from this hunting competition suggest that RHD still appears to be killing rabbits. Every 2–3 years over the past decade, kill rates have been as low as they were when government rabbit-control programs were in place before RHD arrived, but the efficacy of RHD as a biological control agent is waning compared with the first outbreaks of the disease. This concurs with findings based on spotlight counts. Implications The data collected from this hunting competition are a good example of how ‘citizen science’ can be used to capture large volumes of pest-monitoring data from a wide geographic region for very little cost. The information is a valuable addition to understanding the effects of a major wildlife disease.

Proximate weather patterns and spring green-up phenology effect Eurasian beaver (Castor fiber) body mass and reproductive success: the implications of climate change and topography

Low spring temperatures have been found to benefit mobile herbivores by reducing the rate of spring-flush, whereas high rainfall increases forage availability. Cold winters prove detrimental, by increasing herbivore thermoregulatory burdens. Here we examine the effects of temperature and rainfall variability on a temperate sedentary herbivore, the Eurasian beaver, Castor fiber, in terms of inter-annual variation in mean body weight and per territory offspring production. Data pertain to 198 individuals, over 11 years, using capture-mark-recapture. We use plant growth (tree cores) and fAPAR (a satellite-derived plant productivity index) to examine potential mechanisms through which weather conditions affect the availability and the seasonal phenology of beaver forage. Juvenile body weights were lighter after colder winters, whereas warmer spring temperatures were associated with lighter adult body weights, mediated by enhanced green-up phenology rates. Counter-intuitively, we observed a negative association between rainfall and body weight in juveniles and adults, and also with reproductive success. Alder, Alnus incana, (n = 68) growth rings (principal beaver food in the study area) exhibited a positive relationship with rainfall for trees growing at elevations >2 m above water level, but a negative relationship for trees growing <0.5 m. We deduce that temperature influences beavers at the landscape scale via effects on spring green-up phenology and winter thermoregulation. Rainfall influences beavers at finer spatial scales through topographical interactions with plant growth, where trees near water level, prone to water logging, producing poorer forage in wetter years. Unlike most other herbivores, beavers are an obligate aquatic species that utilize a restricted 'central-place' foraging range, limiting their ability to take advantage of better forage growth further from water during wetter years. With respect to anthropogenic climate change, interactions between weather variables, plant phenology and topography on forage growth are instructive, and consequently warrant examination when developing conservation management strategies for populations of medium to large herbivores.

Contrasting effects of climate change on rabbit populations through reproduction

BACKGROUND

Climate change is affecting many physical and biological processes worldwide. Anticipating its effects at the level of populations and species is imperative, especially for organisms of conservation or management concern. Previous studies have focused on estimating future species distributions and extinction probabilities directly from current climatic conditions within their geographical ranges. However, relationships between climate and population parameters may be so complex that to make these high-level predictions we need first to understand the underlying biological processes driving population size, as well as their individual response to climatic alterations. Therefore, the objective of this study is to investigate the influence that climate change may have on species population dynamics through altering breeding season.

METHODOLOGY/PRINCIPAL FINDINGS

We used a mechanistic model based on drivers of rabbit reproductive physiology together with demographic simulations to show how future climate-driven changes in breeding season result in contrasting rabbit population trends across Europe. In the Iberian Peninsula, where rabbits are a native species of high ecological and economic value, breeding seasons will shorten and become more variable leading to population declines, higher extinction risk, and lower resilience to perturbations. Whereas towards north-eastern countries, rabbit numbers are expected to increase through longer and more stable reproductive periods, which augment the probability of new rabbit invasions in those areas.

CONCLUSIONS/SIGNIFICANCE

Our study reveals the type of mechanisms through which climate will cause alterations at the species level and emphasizes the need to focus on them in order to better foresee large-scale complex population trends. This is especially important in species like the European rabbit whose future responses may aggravate even further its dual keystone/pest problematic. Moreover, this approach allows us to predict not only distribution shifts but also future population status and growth, and to identify the demographic parameters on which to focus to mitigate global change effects.