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1. Identifying general patterns of how and why survival rates vary across space and time is necessary to truly understand population dynamics of a species. However, this is not an easy task given the complexity and interactions of processes involved, and the interpopulation differences in main survival determinants.
2. Here, using European rabbits (Oryctolagus cuniculus) as a model and information from local studies, we investigated whether we could make inferences about trends and drivers of survival of a species that are generalizable to large spatio-temporal scales. To do this, we first focused on overall survival and then examined cause-specific mortalities, mainly predation and diseases, which may lead to those patterns.
3. Our results show that within the large-scale variability in rabbit survival, there exist general patterns that are explained by the integration of factors previously known to be important at the local level (i.e. age, climate, diseases, predation or density dependence). We found that both inter- and intrastudy survival rates increased in magnitude and decreased in variability as rabbits grow old, although this tendency was less pronounced in populations with epidemic diseases. Some causes leading to these higher mortalities in young rabbits could be the stronger effect of rainfall at those ages, as well as, other death sources like malnutrition or infanticide.
4. Predation is also greater for newborns and juveniles, especially in population without diseases. Apart from the effect of diseases, predation patterns also depended on factors, such as, density, season, and type and density of predators. Finally, we observed that infectious diseases also showed general relationships with climate, breeding (i.e. new susceptible rabbits) and age, although the association type varied between myxomatosis and rabbit haemorrhagic disease.
5. In conclusion, large-scale patterns of spatio-temporal variability in rabbit survival emerge from the combination of different factors that interrelate both directly and through density dependence. This highlights the importance of performing more comprehensive studies to reveal combined effects and complex relationships that help us to better understand the mechanisms underlying population dynamics.
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- Materials and methods
- Supporting Information
The population dynamics of a species is governed by demographic parameters, such as survival rates, which may widely change in time and space (Mazaris & Matsinos 2006; Ozgul et al. 2006). Processes, environmental and intrinsic properties, and interactions determining survival at a specific time and population may differ importantly from those of other areas and years. Thus, it is far from trivial to know to which extent local inferences about drivers of survival can be integrated and generalized over large spatio-temporal scales.
One way of attaining a comprehensive understanding of the key factors affecting species survival, while avoiding casual results, is considering as much variability as possible, and investigating simultaneously all processes and factors that can be involved. The importance of exploring this large-scale demographic variation is increasingly being acknowledged (Lester, Gaines & Kinlan 2007; Moles et al. 2007). Nevertheless, the complexity of mortality processes together with economic and time constrains lead authors to usually focus on single death causes and particular areas, considering greater levels of variability only, in the best cases, at the temporal scale (Ozgul et al. 2006; Baker & Thompson 2007).
In this study, we took European rabbit survival as model system and information published on specific populations as input data to investigate the existence of general patterns in the survival variability of a species and identify the combination of factors explaining that spatio-temporal variation. We first focused on exploring total survival patterns, and then, we examined the mortality causes that may lead to those survival rates.
At local level, rabbit survival has been studied in detail given the need for both controlling and preserving some of the populations (Fenner & Fantini 1999; Virgós, Cabezas-Díaz & Lozano 2007). Predation, two introduced infectious diseases [i.e. myxomatosis and rabbit haemorrhagic disease (RHD)] and to a lesser extent other causes of mortality (e.g. floods) have been found to importantly affect survival in this species (Villafuerte 1994; Calvete et al. 2002; Rodel et al. 2009). However, despite rabbits being one of the most widely distributed mammals in the world (Flux & Fullagar 1992; Thompson & King 1994), no studies had previously investigated variation in rabbit survival and mechanisms controlling it at large spatio-temporal scales.
We expected that global variability in rabbit survival would be explained by factors and processes already identified at the population scale (i.e. age, climate, diseases and predation among others). However, by integrating all information on local studies, we also hoped to disentangle some not always straightforward relationships between the drivers of rabbit morality. Given previous studies showing that at younger age classes predation rates are higher (Villafuerte 1994; Henning et al. 2008), RHD lethality is reduced and there exist maternal antibodies against myxomatosis and RHD (Ross 1972; Robinson et al. 2002), we predicted that the influence of infectious diseases on survival would be higher as age increased as opposed to predation. In addition, since diseases may weaken animals and make them more vulnerable to predation (Dunsmore, Williams & Price 1971; Villafuerte, Lazo & Moreno 1997), we also expected an increase in predation rates in populations where the diseases were present. Finally, we hoped to find general patterns relating climate and reproductive trends to the occurrence of disease outbreaks, as they influence vector abundance, contact rates and number of susceptible rabbits. We believe this type of research is essential to truly understand the determinants of population dynamics of a species and be able to anticipate and extrapolate population trends beyond study areas.
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- Materials and methods
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Our findings, integrating data from local studies, confirmed that there exist variability patterns in rabbit survival that are generalizable over large spatio-temporal scales and that can be explained by the combination of factors already identified as important individually. We observed, both within and among studies, that newborn and juvenile rabbits had not only lower but also more variable survival probabilities than adults. This is most likely due to young rabbits being more affected by environmental variability than adult ones, as shown by the interaction between age and rainfall. A similar pattern was observed, for large herbivores, by Gaillard, Festa-Bianchet & Yoccoz (1998) who suggested that higher survival variability in younger classes was due to their greater sensitivity to mortality factors, independently of whether they are density-dependent or stochastic, and of the taxa involved.
Pairwise correlations between age-specific survival rates, although not significant, probably a cause of the small sample sizes available, seem to show a positive association between juvenile and adult survival implying that both groups are usually affected by similar death sources (Reed & Slade 2006; Baker & Thompson 2007). Conversely, the negative apparent correlation between newborn and juvenile rates (i.e. low newborn survival leads to relatively high juvenile survival and vice versa) suggests that, regardless of the proximate mortality causes, younger ages are more sensitive to density dependence, as stated by Gaillard, Festa-Bianchet & Yoccoz (1998).
The age effect was corroborated by our GLMM, which showed that the positive influence of age on survival appears to have been attenuated with the arrival of myxomatosis and RHD to populations through a decrease in adult survival, while overall mortality of younger rabbit remains similar. This agrees with Henning et al. (2008) who found that predation was more important than diseases for young rabbits, as opposed to adults. Therefore, the well-known negative influence of these diseases on rabbit population trends (Angulo & Cooke 2002; Henning et al. 2008) may result from their impact on the oldest ages, both directly and possibly also through increased vulnerability to predation (Fig. 4).
Figure 4. Conceptual scheme of age-specific determinants of rabbit survival. Size of objects and arrows represents the effect strength. Direct impacts of climate on diseases are represented with dashed arrows, while continuous lines symbolize effects generalized to both diseases and predator types. Δd corresponds to intra-annual variations in rabbit density (i.e. breeding season stage), and Δp refers to intra-annual variations in predator pressure.
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Our results also show that annual rainfall has a general negative influence on rabbit survival. Wet areas are detrimental for rabbits owing to warren flooding/collapse, hypothermia, and increased transmission of endoparasites such as coccidia (Bull 1958; Robson 1993; Palomares 2003; Rodel et al. 2004). These would, at least partially, explain why precipitation has a greater impact on younger age classes than on older ones. Improved pasture growth in regions with abundant rainfall may also lead to denser/less digestible vegetation, and thus, rabbit body condition and survival may worsen (Williams et al. 1995; Dekker 2007).
The positive relationship between myxomatosis and annual precipitation could also be partially responsible for this decrease in rabbit survival with increased rainfall (Fig. 4). This is also consistent with the lower effect of rainfall on older rabbits, which may have antibodies from previous myxomatosis epidemics. Although some authors have shown an association between low survival and cold temperatures (Marshall 1959; Rodel et al. 2004), we did not find a significant relationship in our study, probably owing to not having enough temperature variation.
We could not either demonstrate the influence of density on survival. This may be partly due to the small sample sizes available for some analyses, which reduce the power to detect effects, and also to the overriding effect of environmental variability over density (i.e. the latter can be more easily detected under similar environmental conditions). However, the apparent negative trends observed in Lombardi et al. (2003) and Parer (1977) agree with results of Rodel et al. (2004) who found a decrease in subadult survival as population density increased. Also, as seen later, density appeared to have direct effects on specific mortality causes, like predation or disease activity (Fig. 4).
When closely examining the different causes of rabbit mortality, we observed that the increase in survival with age could be partially driven by predation patterns, which are also significantly affected by age, with adults being less predated than younger rabbits. As predicted, disease presence was found to influence predation rates through its interaction with rabbit age. Unfortunately, we did not have enough predation data on populations without diseases, but we found that predation decreased more abruptly with age in populations with only myxomatosis than where both myxomatosis and RHD were present, probably because older animals that would usually escape predation become easy targets when weakened by the additional disease (Fig. 4). This effect is especially noticeable in adult rabbits under 12 months, since beyond that age animals are more likely to have been previously exposed and immunized against the disease (Fenner & Fantini 1999; Calvete et al. 2002).
This pattern of interaction could be, in part, responsible for the similar trends observed in overall survival. However, unfortunately, from the bibliography we cannot distinguish how much of this extra predation corresponds to rabbits eaten as carrion after dying from the disease. In a separate analysis, predation rates also appeared to be positively associated with seasonal increases in predator numbers and with rabbit density (Fig. 4). The latter agrees with previous studies indicating that predation is density-dependent (Erlinge et al. 1984; Sinclair & Pech 1996).
Food habit analyses showed that rabbits are consumed more often in spring and summer, which coincides with density peaks at the end of the breeding season in most regions (Myers et al. 1994; Tablado, Revilla & Palomares 2009). Higher disease activity during these seasons could also contribute to this pattern. Indeed, the greater probability of sick rabbits to be predated or eaten as carrion (Rogers, Arthur & Soriguer 1994; Cabezas 2005) is reflected by the increased rabbit frequency in diet samples of populations with myxomatosis and RHD (Fig. 4). With data on rabbit biomass in diet, we found that those seasonal variations are mainly caused by generalist predators as opposed to specialists that depend on rabbits and consume it in high amounts without important temporal variations. These findings agree with Calzada (2000) and Revilla & Palomares (2002), which examined diets of single predator species separately.
This coincides also with the type of functional response expected for this two predator categories. Specialist predators are usually associated with type II functional responses, where the increase in prey consumption with prey density is limited by a constant search rate, generating a simple convex curve (Holling 1959; Davey et al. 2006). Generalists, however, show a sigmoid response (type III) owing to increased search rate as prey density increases (Holling 1959; Turchin & Hanski 1997). The latter allows faster and greater functional responses, and could explain the strong variations of rabbit consumption across seasons, as could represent prey switching in generalist predators according to rabbit availability (Andersson & Erlinge 1977; Pech et al. 1992).
With further analyses, we also observed that rabbit age classes are differently preyed upon depending on the season and thus, on their relative availability. The proportion of juveniles in diet is high year-round, but newborns are consumed mainly in winter and spring, which generally corresponds to main breeding seasons (Myers et al. 1994; Tablado, Revilla & Palomares 2009). For the rest of the year, when newborn availability is lower, the relative importance of adults in diet increases. This coincides also with the decrease in rabbit consumption by generalists, who feed mainly on younger classes, and thus, specialist species may account for the relative increase in adult predation (Figs 2 and 4). Nonetheless, we should be careful when interpreting predator food habits. They help us to understand the system, but the actual impact of predation on rabbit populations cannot be derived from diet data without additional information on predator abundance, rabbit density and attack rates.
Apart from predation, other main sources of rabbit mortality are infectious diseases (Appendix S3), that is, myxomatosis and RHD (Fig. 4; Ross et al. 1989; Calvete 2006). These became enzootic lingering in, for example, remnant susceptible rabbits not immunized during epidemics or infected vectors (Chapple & Lewis 1965; Ross 1972) and breaking out annually or biennially owing to the input of new susceptible hosts during reproductive pulses (Altizer et al. 2006; Begon et al. 2009). Mortality due to myxomatosis or RHD depends on, first, the occurrence of an outbreak that infects rabbits, and secondly, the dying probability of those sick rabbits. Thus, we examined these two epidemic components (i.e. phenology and lethality), even though we acknowledge that this is not enough to capture all the epidemiological complexity concerning these two infectious diseases.
Our phenological analyses showed that, as expected, there exist general trends in disease occurrence determined by reproduction and climate, although the type of relationships differs between myxomatosis and RHD. The period in which myxomatosis is more active goes from the end of a breeding season to the beginning of the next one (i.e. from spring to autumn in most locations). These are months when high numbers of susceptible rabbits (Fig. 4) coincide with abundant insects, which are the main vector of myxomatosis transmission (Appendix S3), even though direct contact might also apply (Parer & Korn 1989; Merchant et al. 2003).
We could not demonstrate the influence of monthly temperature and rainfall on myxomatosis phenology, but we found a negative quadratic effect of annual precipitation (Fig. 4). Wet areas have higher abundance and activity of insect vectors, and thus, greater myxomatosis incidence than drier areas (Soriguer 1981; Parer & Korn 1989; Ross et al. 1989; Simón et al. 1998). However, in locations with extremely high precipitations, the occurrence of myxomatosis decreases again. Greater mortalities caused by warren flooding in these populations (Copson, Brothers & Skira 1981) may reduce the availability of susceptible rabbits necessary to sustain myxomatosis outbreaks.
As for RHD, neither monthly nor annual precipitation showed a significant effect on phenology. However, temperature seemed to affect RHD occurrence, which is more likely in milder months (Fig. 4). High temperatures decrease virus survival (e.g. in infected carcasses), and thus, RHD transmission and activity during hot months (Xu & Chen 1989; McColl et al. 2002). Additionally, extreme temperatures, both hot and cold, may prevent RHD outbreaks by reducing reproduction, and thus contact rates and also vector abundance. Despite the latter not being as important as direct transmission (Appendix S3), vectors might also help spreading the disease, mainly between locations (Asgari et al. 1998; Cooke & Berman 2000).
The probability of finding rabbits infected with RHD is also affected by the population reproductive stage, even though standard significance levels were not reached. However, contrarily to myxomatosis, it increases during the main breeding season (Fig. 4). This may be because of greater numbers of sick-to-susceptible contacts during reproduction (Cooke 1999; Calvete et al. 2002; Mutze et al. 2002).
Here, we also showed differences in case-fatality between diseases (Appendix S3). The high case-fatality of RHD seems to be modified by rabbit age. This effect was already showed by Robinson et al. (2002), who found that young rabbits under 4 weeks might get infected but usually do not die from RHD, this survival decreases importantly with age especially when maternal antibodies are not present, and by 3 months of age the disease kills around 90% of sick rabbits. Some authors have suggested that genetic resistance to RHD could develop in European rabbits (Cooke 1999; White et al. 2001); however, more time might be necessary, as we did not encounter any significant effect of time since disease arrival on resulting case-fatalities.
In contrast, myxomatosis lethality has considerably decreased since the disease introduction. Shortly after virus release, new strains with lower virulence but enhanced transmission started to establish in rabbit populations (Fenner 1983; Kerr & Best 1998), allowing for the selection of genetically resistant animals (Marshall & Douglas 1961; Fenner 1983), which in turn might have promoted the selection again of strains slightly more virulent (Fenner & Fantini 1999; Aparicio, Solari & Bonino 2006). As a result, strain attenuation together with genetic resistance has led to the relatively low myxomatosis case-fatalities in current populations (i.e. average 33%; Appendix S3).
Although several authors have shown an increase in survival to myxomatosis infection with age (Fenner & Ratcliffe 1965; Parer et al. 1994), we were not able to demonstrate it when pooling data across studies. This may be attributed to confounding factors increasing young survival that could not be controlled in this study (e.g. genetic resistance or sire effects). The latter is a mechanism, not well understood yet, which protects kittens born within 9 months of paternal infection with myxomatosis (Parer et al. 1995; Appendix S3). Maternal antibodies, however, could be ruled out because rabbits used in all survival experiments were previously tested for antibody presence and excluded if positive.
The low variability in age data could also explain the lack of significant correlation between age and myxomatosis case-fatality, as most studies used rabbits older than 3–4 months. It has also been suggested that Grade I strains could behave in an opposite way to the others (Sobey et al. 1970; Parer et al. 1994), thus contributing to obscure the overall influence of age. Unfortunately, available data did not allow to further examine this interaction.
Finally, rabbits may also die from other causes (e.g. malnutrition, flooding, collapse, coccidiosis or infanticide), which despite being anecdotally highlighted as important at local level (Copson, Brothers & Skira 1981; Palomares 2003; Rodel et al. 2008), are not generally considered relevant at larger scales. These death sources seem especially important for newborns (i.e. within warrens) and juveniles (Gibb & Fitzgerald 1998; Rodel et al. 2009), agreeing with the interaction between rainfall and rabbit age in our survival analyses (Fig. 4). Sometimes these mortality types may be underestimated through their assignment to predation or infectious diseases (e.g. dead rabbits eaten as carrion; Tyndale-Biscoe & Williams 1955; Webb 1993) or not detected globally because of the lack of adequate data. However, some studies like Rodel et al. (2009) emphasize their importance, as they found a loss of around 40% of newborns after eliminating myxomatosis, RHD and most predation from their enclosed population. This similarly low survival probabilities found in younger rabbits even without epidemic diseases or predation suggests that, to some extent, mortality causes might be compensatory at those ages.
There are other factors whose global effect we could not consider or demonstrate, but that may be still relevant at local scale. For example, hunting, type of insects transmitting diseases and ‘ecological interference’ between diseases (Rohani et al. 2003). However, this does not invalidate the generalized patterns found here, which conclude that large-scale variability in European rabbit survival results from the complex combination of different factors and processes (i.e. age, predation, myxomatosis, RHD and climate), which at the same time interact directly, and through density-dependent and compensatory effects. Further research should focus on the potential interactions and compensation between different mortality causes (e.g. climate and diseases), and on the derived population’s reproductive response. Only then, will we be able to understand current and future population trends of a given species.