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Cuckoos vs. top predators as prime bioindicators of biodiversity in disturbed environments
Journal of Environmental Radioactivity 177 (2017) 158e164
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Cuckoos vs. top predators as prime bioindicators of biodiversity in disturbed environments Federico Morelli a, b, *, Timothy A. Mousseau c, Anders Pape Møller d ra, Prof. Szafrana St. 1, PL 65e516 Zielona Go ra, Poland Faculty of Biological Sciences, University of Zielona Go 129, Czech University of Life Sciences Prague, Faculty of Environmental Sciences, Department of Applied Geoinformatics and Spatial Planning, Kamýcka 165 00 Prague 6, Czech Republic c Department of Biological Sciences, University of South Carolina, Columbia SC 29208, USA d Ecologie Syst ematique Evolution, Universit e Paris-Sud, CNRS, AgroParisTech, Universit e Paris-Saclay, F-91405 Orsay Cedex, France a
b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 1 February 2017 Received in revised form 23 April 2017 Accepted 28 June 2017
We studied the abundance of the common cuckoo Cuculus canorus L. little cuckoo Cuculus poliocephalus L. and Asian cuckoo Cuculus saturatus L. and avian top predators as indicators of bird species richness (surrogate of biodiversity) in disturbed environments caused by radioactive contamination in Chernobyl, Ukraine and Fukushima, Japan, comparing their efficiency as indicators of local biodiversity hotspots. Bird species richness and birds abundance were quantified in each sample site during the breeding seasons between 2006 and 2015 and the level of background radiation was measured at every site. The correlation between number of cuckoos, top predators, land use composition and level of background radiation with bird species richness as response variable were examined using Generalized Linear Mixed Models. The strength of correlation between species richness and abundance and the covariates obtained from the model outputs were used as measure of the efficiency of each predictor, as well as the AIC of each model. Background radiation was negatively correlated with bird species richness and bird abundance in both countries, while number of top predators and cuckoos were both positively correlated with bird species richness and abundance. However, model with number of cuckoos was more performant than model with number of avian top predators. These differences in performance supports the hypothesis that cuckoos are a largely superior bioindicator than top predators. © 2017 Elsevier Ltd. All rights reserved.
Keywords: Background radiation Bioindicator Cuculus spp. Species richness hotspots Top predators
1. Introduction The loss of biodiversity is of critical concern, and an increasing number of studies indicates that biodiversity plays a central role in long-term ecosystem functioning (Groombridge and Jenkins, 2002; Pereira et al., 2012). For this reason, research focused on the spatial distribution of biodiversity is necessary. Species richness provides one of the simplest univariate measures of community diversity (Magurran, 2004). However, the study of biodiversity is difficult, time consuming and costly. In many situations, the study of biodiversity can also be further complicated, as for example in areas with high levels of radiation. For this reason, considering that data on biodiversity are hard to acquire, the use of surrogates for
* Corresponding author. Czech University of Life Sciences Prague, Faculty of Environmental Sciences, Department of Applied Geoinformatics and Spatial Plan 129, 165 00 Prague 6, Czech Republic. ning, Kamýcka E-mail address: [email protected] (F. Morelli). http://dx.doi.org/10.1016/j.jenvrad.2017.06.029 0265-931X/© 2017 Elsevier Ltd. All rights reserved.
estimates can be advantageous in ecological planning. A suitable strategy is to measure the biodiversity indirectly, using measurable €nninen, 2015; attributes, as surrogates or proxies (Armon and Ha Burger, 2006; Lindenmayer et al., 2014; Magurran, 2004; Mellin et al., 2011; Noss, 1990). However, studies on efficiency of such surrogates of biodiversity produce contrasting and conflicting results (Grantham et al., 2010). One of the most emblematic examples is the case of avian top predators used as indicators of biodiversity. In fact, raptors are considered suitable bioindicators because they are umbrella species, and their distribution can mirror hotspots of biodiversity (Sergio et al., 2008b, 2006). The central ecological rationale is clear: The presence and the abundance of raptors would be spatiotemporally correlated with biodiversity, and could be assessed by ecologist as the guarantee of the occurrence of all other species positioned below the trophic level occupied by the top predator. The main reasons can be listed as follows: trophic cascade connections, facilitation of resources, dependence on ecosystem
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productivity, occurrence of raptors mainly in areas characterized by higher landscape heterogeneity due to niche occupation and links to multiple ecosystem components (Sergio et al., 2008a, b). However, the efficiency of top predators as biodiversity indicators is far from being demonstrated. The debate has been intense during the last decades (Cabeza et al., 2007; Roth and Weber, 2008; Sergio et al., 2008a, 2006). The use of avian top predators was strongly promoted because they are very charismatic species and thus easy to use in order to involve people in conservation projects (Sergio et al., 2008a). However, much criticism has been directed against these surrogates. The criticisms included methodological biases introduced in the sampling design that could result in overlooking a huge proportion of potential bird species present in the study area during sampling, but also other ry et al., 2007; Roth and Weber, 2008). Cabeza et al. issues (Ke (2007) highlighted how the occurrence of top predators could be more related to fragmented landscapes (as anthropized environments) than to areas characterized by high biodiversity. Other reasons for suspecting the lack of accuracy of raptors as biodiversity indicators are that these birds are often generalist species, and, therefore, they can hardly be associated with areas characterized by communities composed of both generalist and specialist species, as are areas of higher diversity (Ozaki et al., 2006). Finally, we can argue that species with so large home-ranges as raptors (Newton, 2010), using feeding areas maybe far away from the breeding areas, are scarcely linked to particular sites in a territory. Thus, the extent to which top predators constitutes a valid surrogate of local biodiversity hotspots is still a question under debate. Another bird species recently proposed as a surrogate for identifying hotspots of bird species richness is the common cuckoo Cuculus canorus, shown to be a reliable indicator of taxonomic and functional diversity in bird communities (Morelli et al., 2015; Tryjanowski and Morelli, 2015). The species was also found to be a good proxy for environmental characteristics in disturbed landscapes (Møller et al., 2016). The reasons behind the surrogacy of the cuckoo are completely different from the reasons behind toppredator surrogacy. While again top-predators are hypothesized indicators mainly because they are at the top of the food web, they can indicate the health of the entire trophic cascade. In contrast, cuckoo surrocagy is related to more complex and co-evolutionary mechanisms. The occurrence of this brood parasite would be related to the presence and the abundance of host species. However, the distribution of host species would be related to environmental characteristics, and also to the occurrence of other species that are not hosts of cuckoos through biotic interactions and shared niches. All these characteristics could result in areas with a greater overall number of species in a community (Møller et al., 2016; Morelli et al., 2015). In this study, we assessed the efficiency of the abundance of cuckoos as indicator of bird species richness and bird abundance in two areas in which a major nuclear disaster has occurred recently (Fukushima, Japan and Chernobyl, Ukraine) (Møller and Mousseau, 2016), comparing the efficiency of cuckoos with the efficiency of avian top predators and radiation level in the field (a measure of environmental disturbance) as indicators of bird species richness and bird abundance in the same areas. The rationale for conducting these studies in radioactively contaminated areas is that such sites suffer from reduced abundance of many species of birds (Møller et al., 2015; Møller and Mousseau, 2007a, 2007b), and hence we should expect that such reductions in species richness and abundance should be reflected in a reduction in the number of cuckoos, if cuckoos were reliable indicators of species richness and abundance of birds. We also analyzed the relationship between background radiation and the abundance of butterflies and cuckoos, respectively, in an attempt to test if cuckoo abundance was a
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consequence of the abundance of butterflies that constitute the main diet of cuckoos. 2. Materials and methods 2.1. Study area and bird data collection The breeding bird census were performed using point counts selected randomly, located at ca. 100-m intervals in forested areas west of the exclusion zone around the Fukushima Daiichi power plants in 2011e2016 (Møller et al., 2015) or in forested areas within the Chernobyl Exclusion Zone or adjacent areas, or in areas in southern Belarus around Gomel during the breeding seasons 2006e2015 (Møller et al., 2015). At least one local ornithologist participated in the censuses in Japan to confirm the identity of some bird species. The number of butterflies was assessed in the same point counts, during the bird surveys. Point count census method was adopted because provides reliable information on relative abundance of birds (Bibby et al., 2005; Blondel et al., 1970; Møller, 1983; Vorísek et al., 2010) and insects like butterflies (Møller et al., 2015). The method is based on an observer recording for a period of 5 min all birds and other animals seen and heard. Extensive national monitoring programs for breeding and wintering birds based on point counts take place in many different countries, and this effort is part of environmental monitoring by the European Union (Vorísek et al., 2010). This method has provided highly repeatable results for birds and other animals at Chernobyl and Fukushima (Møller and Mousseau, 2011). A.P.M. conducted these standard point counts during 29 Maye11 June 2006e2015 in the surroundings of Chernobyl (898 census points) and during 11e19 July 2011e2015 at Fukushima (1500 census points). Thus, one single 5-min count was recorded at each observation point in each of the study years. The fact that one person made all counts eliminates any variance in results due to inter-observer variability. There are no bird census data from Chernobyl or Fukushima before the accidents, nor to the best of our knowledge have other scientists conducted bird censuses comparable to ours in the years following the accidents (Møller et al., 2013). We directly tested the reliability of our counts by letting two persons independently perform counts, and the degree of consistency was high for both species richness, total abundance and abundance of individual species (details reported by Møller and Mousseau, 2007a for Chernobyl; similar results exist for Fukushima: A. P. Møller and I. Nishiumi, unpublished data). 2.2. Bird species richness and environmental variables We used a measure of biodiversity related to biological diversity of bird species in the communities and a measure related to environmental composition and disturbance in each sample site. Bird species richness was used as a biodiversity measure, because it is a basic surrogate for the more complex concept of ecological diversity (Magurran, 2004; Morelli, 2013), and because it is the most ski et al., 2011; Young popular diversity index in ecology (Wuczyn et al., 2013). At each site sampled, species richness was calculated as the number of bird species recorded. Furthermore, the number of cuckoos was calculated as the number of cuckoo individuals (none or common cuckoo in Chernobyl and none, little cuckoo or Asian cuckoo in Fukushima). The abundance of top predators was calculated as the total number of individuals of the following raptor species: goshawk Accipiter gentilis, white-tailed sea eagle Haliaeetus albicilla, lesser spotted eagle Aquila pomarina, buzzard Buteo buteo and kestrel Falco tinnunculus) for Chernobyl and the total number of individuals or species of raptors (sparrowhawk Accipiter nisus,
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goshawk Accipiter gentilis, black kite Milvus migrans, buzzard Buteo buteo, grey-faced buzzard Butastur indicus, kestrel Falco tinnunculus and peregrine falcon Falco peregrinus) for Fukushima. For each sampled site, we recorded the percentage of land use type, grouping the following categories: farmland, deciduous, coniferous, bush and grass. These variables were used in order to describe the land use composition in each environment. We measured radiation in the field at each census point, and we cross-validated these measurements with those reported by the Ukrainian Ministry of Emergencies. Once having finished the 5-min census, we measured a and b radiation levels at ground level directly in the field at each point where were censused invertebrates using a hand-held dosimeter (Model: Inspector; SE International, Summertown, TN, USA). We measured levels twoethree times at each site and averaged the results. We crossvalidated our measurements in Ukraine against data from those published by Shestopalov (1996), estimated as the mid-point of the ranges published in the Chernobyl atlas. This analysis revealed a very strong positive relationship [linear regression on logelog transformed data: F ¼ 1546.49, df ¼ 1, 252, r2 ¼ 0.86, P < 0.0001, slope (SE) ¼ 1.28 (0.10)], suggesting that our field estimates of radiation provided reliable measurements of levels of radiation among sites. At Fukushima, we used the same dosimeters, and the measurements were cross-validated with readings with a dosimeter that had been recently calibrated and certified to be accurate by the factory (International Medcom, Sebastopol, CA, USA). We crossvalidated tests at Fukushima by comparing our own measurements with those obtained at the same locations with a TCS 171ALOKA used by the Japanese authorities. Again, there was a very strong positive relationship [linear regression on logelog transformed data: F ¼ 2427.97, df ¼ 1, 20, r2 ¼ 0.99, P < 0.0001, slope (SE) ¼ 1.120 (0.023)]. We have made extensive measurements of internal dose with a gamma spectrometer in hundreds of birds at Chernobyl during 2010e2012 and found very strong positive correlations between internal dose and background radiation level (A. P. Møller & T. A. Mousseau, unpublished). Analysis of this extensive dataset will be published in an accompanying paper. Finally, even if internal and external doses were not strongly positively correlated, we could still not escape the conclusion that the abundance and the diversity of birds is strongly negatively correlated with background radiation. 2.3. Statistical analyses We log10-transformed background radiation level. The nature and strength of correlations between number of bird species and number of birds (bird abundance) with number of top predators (abundance of raptors), number of cuckoos (abundance of cuckoos), environmental variables and radiation level in each sample site, were assessed using Generalized Linear Mixed Models (GLM) (Bates et al., 2015; McCullagh and Nelder, 1989). We used Mantel tests to test for spatial autocorrelation in the data (Legendre and Fortin, 2010; Mantel, 1967), based on the geographic distance matrix and the matrix of differences in bird species richness among sites, applying Monte Carlo permutations with 999 randomizations to test for significance (Oksanen et al., 2016). Sampled sites were treated as statistically dependent observations because the spatial autocorrelation in both studied countries was slight but significant (rM ¼ 0.12, 999 randomizations p < 0.05). Country, year and site were included as random effects to account for possible consistent differences among these groups. We ran three series of models: 1) in the first model, bird species richness was used as a response variable assuming a poisson distribution for this count variable, while the predictors were number
of top predators, number of cuckoos, percentage of farmland, coniferous and bush, radiation level and geographic coordinates of sample sites. Multicollinearity of predictors was avoided introducing in each model only predictors not strongly correlated, considering variance inflation factors (VIF) below 2 amongst these explanatory variables (Neter et al., 1996). The inclusion of geographic coordinates as additional covariates in the models was used in order to alleviate the spatial autocorrelation of datasets (Hu and Lo, 2007). 2) In the second model, bird abundance was used as a response variable assuming a poisson distribution, while the predictors were the same than in the first model. 3) Finally, in a third model, we assessed the association between number of butterflies and number of cuckoos and radiation level. The confidence intervals for the significant variables selected in the models were calculated by the Wald method (Bates et al., 2014). The efficiency of number of avian top predators and cuckoos as surrogates of bird species richness and bird abundance was compared using the outputs of the respective models. The values and signs of estimates, as well as the range of confidence intervals for each predictor in the best model were compared. Furthermore, Akaike Information Criterion (AIC) was used to determine the models that ‘best’ explained variation in the data (Burnham and Anderson, 2002). The multimodel inference was performed using the package ‘AICcmodavg’ in R (Mazerolle, 2016), and comparing a models of bird species richness excluding as predictor alternatively the number of cuckoos or the number of avian raptors. The best model was selected considering lowest AIC, because this model had the strongest support for data (Mazerolle, 2016). All statistical tests were performed with R software (R Development Core Team, 2017). 3. Results 3.1. Correlation between bird species richness, number of cuckoos, raptors, land use composition and background radiation Bird species richness in Fukushima ranged between 0 and 10 species, with a mean of 3.83 species (0.05), N ¼ 1500 (Fig. 1). The number of cuckoos ranged between 0 and 2, mean (SE) ¼ 0.20 (0.01) in Fukushima, N ¼ 1500, while the number of raptors ranged between 0 and 3, mean (SE) ¼ 0.012 (0.010) in Fukushima, N ¼ 1500 (Fig. 1). Bird species richness in Chernobyl ranged between 1 and 13, mean (SE) ¼ 5.57 (0.07), N ¼ 981 (Fig. 1). The number of cuckoos ranged between 0 and 4, mean (SE) ¼ 0.60 (0.02) in Chernobyl, N ¼ 1500, while the number of raptors ranged between 0 and 3, mean (SE) ¼ 0.049 (0.008) in Chernobyl, N ¼ 981 (Fig. 1). Radiation level ranged from 0.02 to 38.11 mSv/h, mean (SE) ¼ 6.26 (0.19), N ¼ 1500 in Fukushima, and from 0.01 to 379.7 mSv/h, mean (SE) ¼ 17.65 (1.54), N ¼ 981 in Chernobyl (Fig. 1). The bird species richness decreased with level of ionizing radiation in both countries, increasing with number of raptors and with number of cuckoos (Table 1, Fig. 1). The bird species richness was also slightly but positively correlated with farmlands and negatively correlated with bush (Table 1). Bird species richness was most strongly correlated with the number of cuckoos than avian top predators (Fig. 2). The best model selection confirmed also that number of cuckoos was largely most important than number of avian top predators explaining the bird species richness (Table 2). 3.2. Correlation between bird abundance, number of cuckoos, raptors, land use composition and background radiation Bird abundance per census point in Fukushima ranged between 0 and 51 individuals per point on average 5.82, SE ¼ 0.11, N ¼ 1500. Bird abundance in Chernobyl ranged between 0 and 32 individuals
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Fig. 1. Box plots of the distribution of data on raptor abundance, cuckoo abundance and background radiation for Fukushima, Japan (above) and Chernobyl, Ukraine (below). Box plots show medians, quartiles, 5- and 95-percentiles and extreme values.
Table 1 Fixed-effect parameters in a Generalized Linear Mixed Model, accounting for bird species richness in relation to number of avian top predators, number of cuckoos, land use composition and background radiation level in Fukushima and Chernobyl. Random effects: Country (groups ¼ 2), year (groups ¼ 28) and sites (groups ¼ 27). The table shows estimates, 95% confidence intervals (CI), SE, c2 and p values. Only significant variables are shown in the table. Predictors
Estimate
CI
SE
c2
p
Intercept No. raptors No. cuckoos Log radiation Farmland Bush
1.493 0.129 0.207 0.190 0.001 0.003
1.402/1.585 0.084/0.182 0.713/0.240 0.237/0.143 0.000/0.003 0.005/0.002
0.047 0.025 0.017 0.024 4.7e-4 6.5e-4
31.9 5.3 12.1 7.9 2.5 5.6
<0.05 <0.05 <0.05 <0.05 <0.05 <0.05
per census point, mean (SE) ¼ 6.70 (0.12), N ¼ 981. The sample sites without birds (0 individuals) represented less than 0.8% of the total recorded (19 cases from 2481). The best model showed that the number of avian raptors, number of cuckoos, bush percentage and background radiation were significant predictors of bird abundance in both countries (Table 3). The bird abundance decreased with level of ionizing radiation in both countries, increasing with number of raptors and with number of cuckoos (Table 3, Fig. 3). The bird abundance was also slightly but negatively correlated with bush (Table 3). Finally, the number of butterflies decreased with increasing level of ionizing radiation in Chernobyl, and that was also the case in Fukushima, however these differences were not statistically significant (Z ¼ 0.625, p ¼ 0.532, estimate (SE) ¼ 0.002 (0.002)).
There was no significant association between abundance of cuckoos and abundance of butterflies (Z ¼ 0.672, p ¼ 0.502, estimate (SE) ¼ 0.029 (0.043)).
4. Discussion We found significant associations between bird species richness and the abundance of cuckoos and avian top predators in Chernobyl and Fukushima. These effects were still present after inclusion of the degree of ionizing radiation as a covariate, implying that other mechanisms than the presence of cuckoos are at work. Furthermore, some characteristics of land use composition contributed to the variation in bird species richness (farmland and bush) and bird abundance (bush). The slight but positive association with farmland coverage can be explained by the fact that cultivated areas often support more different species than forestal areas, being more heterogeneous mosaics (Morelli et al., 2013). The negative effect of bush coverage in bird diversity, instead, it is less easy to be interpreted, and could be simply related to an opposite association between farmland and bush coverage. However, here we focused our effort on understanding the associations among birds, cuckoo abundance and raptors abundance and radiation level. Large-scale environmental perturbations like those in Chernobyl and Fukushima are interesting because they allow for tests of predictions derived from ecological and conservation biological theory across large spatial scales. The common cuckoo has been shown to be an efficient bioindicator of biodiversity in many European countries (Morelli et al., 2015; Tryjanowski and Morelli,
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Fig. 2. Associations between the number of avian top predators, number of cuckoos, background radiation and species richness of birds in Fukushima, Japan (above) and Chernobyl, Ukraine (below). The lines are estimates and 95% confidence intervals.
Table 2 List of GLMMs performed in this study, accounting for variation in bird species richness in relation to number of avian top predators, number of cuckoos, land use composition and background radiation level in Fukushima and Chernobyl. Random effects: Country (groups ¼ 2), year (groups ¼ 28) and sites (groups ¼ 27). The choice of the best model was performed using the model selection and multimodel inference based on Akaike's information criterion (AIC) in the package AICcmodavg from R (Mazerolle, 2016). Model
AIC
DAIC
Full model Cuckoos model (excluding raptors) Raptors model (excluding cuckoos)
9609.7 9634.1 9748.7
0.0 24.4 139.0
2015). In this study we extended our previous exploration of bioindicator capacities, to three different cuckoo species, using the number of cuckoos as proxy for overall species richness or abundance of birds in the community. Cuckoos are well-known for their obligate parasitism of other bird species (Davies, 2000; Erritzøe et al., 2012). We have previously shown that the bioindicator efficiency of common cuckoo is not only due to their close relationship with their hosts (Morelli et al., 2015). In fact, cuckoos are as efficient bioindicators for hosts as for non-hosts (Morelli et al. unpublished data). This suggests that other mechanisms are involved. Cuckoos have a main diet of large lepidopteran caterpillars (Erritzøe et al., 2012), which are characteristic herbivores of a range of different plant species (Dyer et al., 2007). Here we tested the possibility that at least part of the bioindicator ability of the abundance of cuckoos is due to links to butterfly caterpillars. However, here we could show that this was not the case.
Table 3 Fixed-effect parameters in a Generalized Linear Mixed Model, accounting for number of birds (bird abundance) in relation to number of avian top predators, number of cuckoos, land use composition and background radiation level in Fukushima and Chernobyl. Random effects: Country (groups ¼ 2), year (groups ¼ 28) and sites (groups ¼ 27). The table shows estimates, 95% confidence intervals (CI), SE, c2 and p values. Only significant variables are showed in the table. Predictors
Estimate
CI
SE
c2
p
Intercept No. raptors No. cuckoos Log radiation Bush
1.882 0.136 0.199 0.202 0.007
1.663/2.101 0.096/0.176 0.170/0.229 0.252/0.152 0.008/0.005
0.111 0.020 0.015 0.026 0.001
16.9 6.7 13.3 7.8 10.9
<0.05 <0.05 <0.05 <0.05 <0.05
Superficially, we might conclude that the reduction in number of birds of prey and cuckoos arose as a consequence of a reduction in the abundance of prey and hosts, respectively, However, that is not the case given that the abundance of cuckoos is as strong a predictor of species richness and abundance of hosts as on nonhosts (Morelli et al. unpublished data). Thus cuckoos are bioindicators of hosts and non-hosts alike, suggesting that their abundance reflects environmental conditions rather than the abundance of other bird species such as prey and hosts. The findings reported here may be explained as consequences of ecological traps or competive voids. Ecological traps arise from organisms moving into ecological settings where their fitness is reduced compared to what it might have been had they behaved differently (Dwernychuk and Boag, 1972; Gates and Gysel, 1978).
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Fig. 3. Associations between the number of avian top predators, number of cuckoos, background radiation and abundance of birds in Fukushima, Japan (above) and Chernobyl, Ukraine (below). The lines are estimates and 95% confidence intervals.
We have already published a study of barn swallows Hirundo rustica showing evidence consistent with ecological traps (Møller et al., 2006). We have additional census data of birds consistent with ecological traps. In contrast, competitive voids that may arise from the reduction in abundance or diversity of competitors due to radiation effects. We have no evidence consistent with this hypotheses. Finally, we consider it uniquely that this mechanism may account for the findings on cuckoos, because cuckoos are specialist consumers of large social butterfly caterpillars. The present study has additional implications. We have shown elsewhere that extreme environmental perturbations of the level of ionizing radiation affect the abundance and diversity of birds (Møller et al., 2015; Møller and Mousseau, 2007a, 2007b). Because both cuckoos and other birds are negatively affected by radioactive contamination, we hypothesize that it is partly ionizing radiation that is causing covariation between abundance and diversity of cuckoos on the one hand, and abundance and diversity of other species on the other. Similar explanations might also apply to other components of environmental change such as climate change and intensification of agriculture and forestry that are likely to impact many different species including the diversity and abundance of cuckoos. Clearly, this does not explain why cuckoos rather than raptors are prime bioindicators of species richness of birds. Here, we are providing new evidence on the old debate about the efficiency of avian top predators as potential indicators of hotspots of biodiversity (Cabeza et al., 2007; Roth and Weber, 2008). We demonstrated how the abundance of cuckoos is much more reliable than the abundance of raptor species as indicator of overall bird species richness and abundance even in highly disturbed
environments. Probably co-evolutionary interactions linking parasites to hosts are the main causes of the efficiency of cuckoos as indicators of species richness and abundance. We emphasize that similar arguments about coevolution between predators and prey cannot account for the patterns. This suggests that more tight ecological links than those caused by predators at the top position in a trophic food chain are required for them being suitable as more efficient bioindicators than brood parasites. In conclusion, we have shown that number of cuckoos is a reliable indicator of species richness and abundance of birds around Chernobyl and Fukushima, suggesting that even large scale environmental perturbation is reflected in the abundance of cuckoos, while that is the case to a much smaller extent for raptors. Appendix A. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.jenvrad.2017.06.029. References Armon, R.H., H€ anninen, O., 2015. Environmental Indicators. Springer, Netherlands doi:978-94-017-9498-5. Bates, D., Maechler, M., Bolker, B., Walker, S., 2015. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1e48. http://dx.doi.org/10.18637/ jss.v067.i01. Bates, D., Maechler, M., Bolker, B., Walker, S., 2014. lme4: Linear Mixed-Effects Models using Eigen and S4-R Package. Bibby, C.J., Hill, D.A., Burgess, N.D., Mustoe, S., 2005. Bird Census Techniques. Academic Press, London, UK. thode des indices ponctuels Blondel, J., Ferry, C., Frochot, B., 1970. La me
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under field conditions. Ecol. Indic. 11, 424e430. http://dx.doi.org/10.1016/ j.ecolind.2010.06.013. Møller, A.P., Mousseau, T.A., 2007a. Species richness and abundance of birds in relation to radiation at. Chernobyl. Biol. Lett. 3, 483e486. http://dx.doi.org/ 10.1098/rsbl.2007.0226. Møller, A.P., Mousseau, T.A., 2007b. Determinants of interspecific variation in population declines of birds from exposure to radiation at Chernobyl. J. Appl. Ecol. 44, 909e919. http://dx.doi.org/10.1111/j.1365-2664.2007.01353.x. Møller, A.P., Nishiumi, I., Suzuki, H., Ueda, K., Mousseau, T.A., 2013. Differences in effects of radiation on abundance of animals in Fukushima and Chernobyl. Ecol. Indic. 24, 75e81. http://dx.doi.org/10.1016/j.ecolind.2012.06.001. Morelli, F., 2013. Quantifying effects of spatial heterogeneity of farmlands on bird species richness by means of similarity index pairwise. Int. J. Biodivers. 2013, 1e9. http://dx.doi.org/10.1155/2013/914837. , P., Morelli, F., Jiguet, F., Reif, J., Plexida, S., Valli, A.S., Indykiewicz, P., Símov a Tichit, M., Moretti, M., Tryjanowski, P., 2015. Cuckoo and biodiversity: testing the correlation between species occurrence and bird species richness in Europe. Biol. Conserv. 190, 123e132. http://dx.doi.org/10.1016/j.biocon.2015.06.003. Morelli, F., Pruscini, F., Santolini, R., Perna, P., Benedetti, Y., Sisti, D., 2013. Landscape heterogeneity metrics as indicators of bird diversity: determining the optimal spatial scales in different landscapes. Ecol. Indic. 34, 372e379. http://dx.doi.org/ 10.1016/j.ecolind.2013.05.021. Neter, J., Kutner, M.H., Nachtsheim, C.J., Wasserman, W., 1996. Applied Linear Statistical Models, fourth ed. McGraw-Hill/Irwin, Chicago, Illinois, USA. Newton, I., 2010. Population Ecology of Raptors. Poyser, Berkhamsted, UK. Noss, R.F., 1990. Indicators for monitoring biodiversity: a hierarchical approach. Conserv. Biol. 4, 355e364. http://dx.doi.org/10.1111/j.1523-1739.1990.tb0 0309.x. Oksanen, J., Guillaume Blanchet, F., Kindt, R., Legendre, P., Minchin, P.R., O'Hara, B.R., Simpson, G.L., Solymos, P., Stevens, M.H.H., Wagner, H., 2016. Vegan: Community Ecology Package. R package version 2.3-4. Ozaki, K., Isono, M., Kawahara, T., Iida, S., Kudo, T., Fukuyama, K., 2006. A mechanistic approach to evaluation of umbrella species as conservation surrogates. Conserv. Biol. 20, 1507e1515. http://dx.doi.org/10.1111/j.15231739.2006.00444.x. Pereira, H.M., Navarro, L.M., Martins, I.S., 2012. Global biodiversity change: the bad, the good, and the unknown. Annu. Rev. Environ. Resour. 37, 25e50. http:// dx.doi.org/10.1146/annurev-environ-042911-093511. R Development Core Team, 2017. R: a Language and Environment for Statistical Computing. Roth, T., Weber, D., 2008. Top predators as indicators for species richness? Prey species are just as useful. J. Appl. Ecol. 45, 987e991. http://dx.doi.org/10.1111/ j.1365-2664.2007.0. Sergio, F., Caro, T., Brown, D., Clucas, B., Hunter, J., Ketchum, J., Mchugh, K., Hiraldo, F., 2008a. Top Predators as conservation tools: ecological rationale, assumptions and efficacy. Annu. Rev. Ecol. Evol. Syst. 39, 1e19. http://dx.doi.org/ 10.1146/annurev.ecolsys.39.110707.173545. Sergio, F., Newton, I., Marchesi, L., 2008b. Top predators and biodiversity: much debate, few data. J. Appl. Ecol. 45, 992e999. http://dx.doi.org/10.1111/j.13652664.2007.0. Sergio, F., Newton, I., Marchesi, L., Pedrini, P., 2006. Ecologically justified charisma: preservation of top predators delivers biodiversity conservation. J. Appl. Ecol. 43, 1049e1055. Shestopalov, V.M., 1996. Atlas of Chernobyl Exclusion Zone. Ukrainian Academy of Science, Kiev, Ukraine. Tryjanowski, P., Morelli, F., 2015. Presence of Cuckoo reliably indicates high bird diversity: a case study in a farmland area. Ecol. Indic. 55, 52e58. http:// dx.doi.org/10.1016/j.ecolind.2015.03.012. ova , A., Wotton, S., Gregory, R.D., 2010. A Best Practice Guide for Vorísek, P., Klvan Wild Bird Monitoring Schemes. Pan-European Common Bird Monitoring Scheme (PECMBS), Bruxelles, Belgium. ski, A., Kujawa, K., Dajdok, Z., Grzesiak, W., 2011. Species richness and Wuczyn composition of bird communities in various field margins of Poland. Agric. Ecosyst. Environ. 141, 202e209. http://dx.doi.org/10.1016/j.agee.2011.02.031. Young, J.S., Ammon, E.M., Weisberg, P.J., Dilts, T.E., Newton, W.E., Wong-Kone, D.C., Heki, L.G., 2013. Comparison of bird community indices for riparian restoration planning and monitoring. Ecol. Indic. 34, 159e167. http://dx.doi.org/10.1016/ j.ecolind.2013.05.004.
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Cuckoos vs. top predators as prime bioindicators of biodiversity in disturbed environments Federico Morelli a, b, *, Timothy A. Mousseau c, Anders Pape Møller d ra, Prof. Szafrana St. 1, PL 65e516 Zielona Go ra, Poland Faculty of Biological Sciences, University of Zielona Go 129, Czech University of Life Sciences Prague, Faculty of Environmental Sciences, Department of Applied Geoinformatics and Spatial Planning, Kamýcka 165 00 Prague 6, Czech Republic c Department of Biological Sciences, University of South Carolina, Columbia SC 29208, USA d Ecologie Syst ematique Evolution, Universit e Paris-Sud, CNRS, AgroParisTech, Universit e Paris-Saclay, F-91405 Orsay Cedex, France a
b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 1 February 2017 Received in revised form 23 April 2017 Accepted 28 June 2017
We studied the abundance of the common cuckoo Cuculus canorus L. little cuckoo Cuculus poliocephalus L. and Asian cuckoo Cuculus saturatus L. and avian top predators as indicators of bird species richness (surrogate of biodiversity) in disturbed environments caused by radioactive contamination in Chernobyl, Ukraine and Fukushima, Japan, comparing their efficiency as indicators of local biodiversity hotspots. Bird species richness and birds abundance were quantified in each sample site during the breeding seasons between 2006 and 2015 and the level of background radiation was measured at every site. The correlation between number of cuckoos, top predators, land use composition and level of background radiation with bird species richness as response variable were examined using Generalized Linear Mixed Models. The strength of correlation between species richness and abundance and the covariates obtained from the model outputs were used as measure of the efficiency of each predictor, as well as the AIC of each model. Background radiation was negatively correlated with bird species richness and bird abundance in both countries, while number of top predators and cuckoos were both positively correlated with bird species richness and abundance. However, model with number of cuckoos was more performant than model with number of avian top predators. These differences in performance supports the hypothesis that cuckoos are a largely superior bioindicator than top predators. © 2017 Elsevier Ltd. All rights reserved.
Keywords: Background radiation Bioindicator Cuculus spp. Species richness hotspots Top predators
1. Introduction The loss of biodiversity is of critical concern, and an increasing number of studies indicates that biodiversity plays a central role in long-term ecosystem functioning (Groombridge and Jenkins, 2002; Pereira et al., 2012). For this reason, research focused on the spatial distribution of biodiversity is necessary. Species richness provides one of the simplest univariate measures of community diversity (Magurran, 2004). However, the study of biodiversity is difficult, time consuming and costly. In many situations, the study of biodiversity can also be further complicated, as for example in areas with high levels of radiation. For this reason, considering that data on biodiversity are hard to acquire, the use of surrogates for
* Corresponding author. Czech University of Life Sciences Prague, Faculty of Environmental Sciences, Department of Applied Geoinformatics and Spatial Plan 129, 165 00 Prague 6, Czech Republic. ning, Kamýcka E-mail address: [email protected] (F. Morelli). http://dx.doi.org/10.1016/j.jenvrad.2017.06.029 0265-931X/© 2017 Elsevier Ltd. All rights reserved.
estimates can be advantageous in ecological planning. A suitable strategy is to measure the biodiversity indirectly, using measurable €nninen, 2015; attributes, as surrogates or proxies (Armon and Ha Burger, 2006; Lindenmayer et al., 2014; Magurran, 2004; Mellin et al., 2011; Noss, 1990). However, studies on efficiency of such surrogates of biodiversity produce contrasting and conflicting results (Grantham et al., 2010). One of the most emblematic examples is the case of avian top predators used as indicators of biodiversity. In fact, raptors are considered suitable bioindicators because they are umbrella species, and their distribution can mirror hotspots of biodiversity (Sergio et al., 2008b, 2006). The central ecological rationale is clear: The presence and the abundance of raptors would be spatiotemporally correlated with biodiversity, and could be assessed by ecologist as the guarantee of the occurrence of all other species positioned below the trophic level occupied by the top predator. The main reasons can be listed as follows: trophic cascade connections, facilitation of resources, dependence on ecosystem
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productivity, occurrence of raptors mainly in areas characterized by higher landscape heterogeneity due to niche occupation and links to multiple ecosystem components (Sergio et al., 2008a, b). However, the efficiency of top predators as biodiversity indicators is far from being demonstrated. The debate has been intense during the last decades (Cabeza et al., 2007; Roth and Weber, 2008; Sergio et al., 2008a, 2006). The use of avian top predators was strongly promoted because they are very charismatic species and thus easy to use in order to involve people in conservation projects (Sergio et al., 2008a). However, much criticism has been directed against these surrogates. The criticisms included methodological biases introduced in the sampling design that could result in overlooking a huge proportion of potential bird species present in the study area during sampling, but also other ry et al., 2007; Roth and Weber, 2008). Cabeza et al. issues (Ke (2007) highlighted how the occurrence of top predators could be more related to fragmented landscapes (as anthropized environments) than to areas characterized by high biodiversity. Other reasons for suspecting the lack of accuracy of raptors as biodiversity indicators are that these birds are often generalist species, and, therefore, they can hardly be associated with areas characterized by communities composed of both generalist and specialist species, as are areas of higher diversity (Ozaki et al., 2006). Finally, we can argue that species with so large home-ranges as raptors (Newton, 2010), using feeding areas maybe far away from the breeding areas, are scarcely linked to particular sites in a territory. Thus, the extent to which top predators constitutes a valid surrogate of local biodiversity hotspots is still a question under debate. Another bird species recently proposed as a surrogate for identifying hotspots of bird species richness is the common cuckoo Cuculus canorus, shown to be a reliable indicator of taxonomic and functional diversity in bird communities (Morelli et al., 2015; Tryjanowski and Morelli, 2015). The species was also found to be a good proxy for environmental characteristics in disturbed landscapes (Møller et al., 2016). The reasons behind the surrogacy of the cuckoo are completely different from the reasons behind toppredator surrogacy. While again top-predators are hypothesized indicators mainly because they are at the top of the food web, they can indicate the health of the entire trophic cascade. In contrast, cuckoo surrocagy is related to more complex and co-evolutionary mechanisms. The occurrence of this brood parasite would be related to the presence and the abundance of host species. However, the distribution of host species would be related to environmental characteristics, and also to the occurrence of other species that are not hosts of cuckoos through biotic interactions and shared niches. All these characteristics could result in areas with a greater overall number of species in a community (Møller et al., 2016; Morelli et al., 2015). In this study, we assessed the efficiency of the abundance of cuckoos as indicator of bird species richness and bird abundance in two areas in which a major nuclear disaster has occurred recently (Fukushima, Japan and Chernobyl, Ukraine) (Møller and Mousseau, 2016), comparing the efficiency of cuckoos with the efficiency of avian top predators and radiation level in the field (a measure of environmental disturbance) as indicators of bird species richness and bird abundance in the same areas. The rationale for conducting these studies in radioactively contaminated areas is that such sites suffer from reduced abundance of many species of birds (Møller et al., 2015; Møller and Mousseau, 2007a, 2007b), and hence we should expect that such reductions in species richness and abundance should be reflected in a reduction in the number of cuckoos, if cuckoos were reliable indicators of species richness and abundance of birds. We also analyzed the relationship between background radiation and the abundance of butterflies and cuckoos, respectively, in an attempt to test if cuckoo abundance was a
159
consequence of the abundance of butterflies that constitute the main diet of cuckoos. 2. Materials and methods 2.1. Study area and bird data collection The breeding bird census were performed using point counts selected randomly, located at ca. 100-m intervals in forested areas west of the exclusion zone around the Fukushima Daiichi power plants in 2011e2016 (Møller et al., 2015) or in forested areas within the Chernobyl Exclusion Zone or adjacent areas, or in areas in southern Belarus around Gomel during the breeding seasons 2006e2015 (Møller et al., 2015). At least one local ornithologist participated in the censuses in Japan to confirm the identity of some bird species. The number of butterflies was assessed in the same point counts, during the bird surveys. Point count census method was adopted because provides reliable information on relative abundance of birds (Bibby et al., 2005; Blondel et al., 1970; Møller, 1983; Vorísek et al., 2010) and insects like butterflies (Møller et al., 2015). The method is based on an observer recording for a period of 5 min all birds and other animals seen and heard. Extensive national monitoring programs for breeding and wintering birds based on point counts take place in many different countries, and this effort is part of environmental monitoring by the European Union (Vorísek et al., 2010). This method has provided highly repeatable results for birds and other animals at Chernobyl and Fukushima (Møller and Mousseau, 2011). A.P.M. conducted these standard point counts during 29 Maye11 June 2006e2015 in the surroundings of Chernobyl (898 census points) and during 11e19 July 2011e2015 at Fukushima (1500 census points). Thus, one single 5-min count was recorded at each observation point in each of the study years. The fact that one person made all counts eliminates any variance in results due to inter-observer variability. There are no bird census data from Chernobyl or Fukushima before the accidents, nor to the best of our knowledge have other scientists conducted bird censuses comparable to ours in the years following the accidents (Møller et al., 2013). We directly tested the reliability of our counts by letting two persons independently perform counts, and the degree of consistency was high for both species richness, total abundance and abundance of individual species (details reported by Møller and Mousseau, 2007a for Chernobyl; similar results exist for Fukushima: A. P. Møller and I. Nishiumi, unpublished data). 2.2. Bird species richness and environmental variables We used a measure of biodiversity related to biological diversity of bird species in the communities and a measure related to environmental composition and disturbance in each sample site. Bird species richness was used as a biodiversity measure, because it is a basic surrogate for the more complex concept of ecological diversity (Magurran, 2004; Morelli, 2013), and because it is the most ski et al., 2011; Young popular diversity index in ecology (Wuczyn et al., 2013). At each site sampled, species richness was calculated as the number of bird species recorded. Furthermore, the number of cuckoos was calculated as the number of cuckoo individuals (none or common cuckoo in Chernobyl and none, little cuckoo or Asian cuckoo in Fukushima). The abundance of top predators was calculated as the total number of individuals of the following raptor species: goshawk Accipiter gentilis, white-tailed sea eagle Haliaeetus albicilla, lesser spotted eagle Aquila pomarina, buzzard Buteo buteo and kestrel Falco tinnunculus) for Chernobyl and the total number of individuals or species of raptors (sparrowhawk Accipiter nisus,
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goshawk Accipiter gentilis, black kite Milvus migrans, buzzard Buteo buteo, grey-faced buzzard Butastur indicus, kestrel Falco tinnunculus and peregrine falcon Falco peregrinus) for Fukushima. For each sampled site, we recorded the percentage of land use type, grouping the following categories: farmland, deciduous, coniferous, bush and grass. These variables were used in order to describe the land use composition in each environment. We measured radiation in the field at each census point, and we cross-validated these measurements with those reported by the Ukrainian Ministry of Emergencies. Once having finished the 5-min census, we measured a and b radiation levels at ground level directly in the field at each point where were censused invertebrates using a hand-held dosimeter (Model: Inspector; SE International, Summertown, TN, USA). We measured levels twoethree times at each site and averaged the results. We crossvalidated our measurements in Ukraine against data from those published by Shestopalov (1996), estimated as the mid-point of the ranges published in the Chernobyl atlas. This analysis revealed a very strong positive relationship [linear regression on logelog transformed data: F ¼ 1546.49, df ¼ 1, 252, r2 ¼ 0.86, P < 0.0001, slope (SE) ¼ 1.28 (0.10)], suggesting that our field estimates of radiation provided reliable measurements of levels of radiation among sites. At Fukushima, we used the same dosimeters, and the measurements were cross-validated with readings with a dosimeter that had been recently calibrated and certified to be accurate by the factory (International Medcom, Sebastopol, CA, USA). We crossvalidated tests at Fukushima by comparing our own measurements with those obtained at the same locations with a TCS 171ALOKA used by the Japanese authorities. Again, there was a very strong positive relationship [linear regression on logelog transformed data: F ¼ 2427.97, df ¼ 1, 20, r2 ¼ 0.99, P < 0.0001, slope (SE) ¼ 1.120 (0.023)]. We have made extensive measurements of internal dose with a gamma spectrometer in hundreds of birds at Chernobyl during 2010e2012 and found very strong positive correlations between internal dose and background radiation level (A. P. Møller & T. A. Mousseau, unpublished). Analysis of this extensive dataset will be published in an accompanying paper. Finally, even if internal and external doses were not strongly positively correlated, we could still not escape the conclusion that the abundance and the diversity of birds is strongly negatively correlated with background radiation. 2.3. Statistical analyses We log10-transformed background radiation level. The nature and strength of correlations between number of bird species and number of birds (bird abundance) with number of top predators (abundance of raptors), number of cuckoos (abundance of cuckoos), environmental variables and radiation level in each sample site, were assessed using Generalized Linear Mixed Models (GLM) (Bates et al., 2015; McCullagh and Nelder, 1989). We used Mantel tests to test for spatial autocorrelation in the data (Legendre and Fortin, 2010; Mantel, 1967), based on the geographic distance matrix and the matrix of differences in bird species richness among sites, applying Monte Carlo permutations with 999 randomizations to test for significance (Oksanen et al., 2016). Sampled sites were treated as statistically dependent observations because the spatial autocorrelation in both studied countries was slight but significant (rM ¼ 0.12, 999 randomizations p < 0.05). Country, year and site were included as random effects to account for possible consistent differences among these groups. We ran three series of models: 1) in the first model, bird species richness was used as a response variable assuming a poisson distribution for this count variable, while the predictors were number
of top predators, number of cuckoos, percentage of farmland, coniferous and bush, radiation level and geographic coordinates of sample sites. Multicollinearity of predictors was avoided introducing in each model only predictors not strongly correlated, considering variance inflation factors (VIF) below 2 amongst these explanatory variables (Neter et al., 1996). The inclusion of geographic coordinates as additional covariates in the models was used in order to alleviate the spatial autocorrelation of datasets (Hu and Lo, 2007). 2) In the second model, bird abundance was used as a response variable assuming a poisson distribution, while the predictors were the same than in the first model. 3) Finally, in a third model, we assessed the association between number of butterflies and number of cuckoos and radiation level. The confidence intervals for the significant variables selected in the models were calculated by the Wald method (Bates et al., 2014). The efficiency of number of avian top predators and cuckoos as surrogates of bird species richness and bird abundance was compared using the outputs of the respective models. The values and signs of estimates, as well as the range of confidence intervals for each predictor in the best model were compared. Furthermore, Akaike Information Criterion (AIC) was used to determine the models that ‘best’ explained variation in the data (Burnham and Anderson, 2002). The multimodel inference was performed using the package ‘AICcmodavg’ in R (Mazerolle, 2016), and comparing a models of bird species richness excluding as predictor alternatively the number of cuckoos or the number of avian raptors. The best model was selected considering lowest AIC, because this model had the strongest support for data (Mazerolle, 2016). All statistical tests were performed with R software (R Development Core Team, 2017). 3. Results 3.1. Correlation between bird species richness, number of cuckoos, raptors, land use composition and background radiation Bird species richness in Fukushima ranged between 0 and 10 species, with a mean of 3.83 species (0.05), N ¼ 1500 (Fig. 1). The number of cuckoos ranged between 0 and 2, mean (SE) ¼ 0.20 (0.01) in Fukushima, N ¼ 1500, while the number of raptors ranged between 0 and 3, mean (SE) ¼ 0.012 (0.010) in Fukushima, N ¼ 1500 (Fig. 1). Bird species richness in Chernobyl ranged between 1 and 13, mean (SE) ¼ 5.57 (0.07), N ¼ 981 (Fig. 1). The number of cuckoos ranged between 0 and 4, mean (SE) ¼ 0.60 (0.02) in Chernobyl, N ¼ 1500, while the number of raptors ranged between 0 and 3, mean (SE) ¼ 0.049 (0.008) in Chernobyl, N ¼ 981 (Fig. 1). Radiation level ranged from 0.02 to 38.11 mSv/h, mean (SE) ¼ 6.26 (0.19), N ¼ 1500 in Fukushima, and from 0.01 to 379.7 mSv/h, mean (SE) ¼ 17.65 (1.54), N ¼ 981 in Chernobyl (Fig. 1). The bird species richness decreased with level of ionizing radiation in both countries, increasing with number of raptors and with number of cuckoos (Table 1, Fig. 1). The bird species richness was also slightly but positively correlated with farmlands and negatively correlated with bush (Table 1). Bird species richness was most strongly correlated with the number of cuckoos than avian top predators (Fig. 2). The best model selection confirmed also that number of cuckoos was largely most important than number of avian top predators explaining the bird species richness (Table 2). 3.2. Correlation between bird abundance, number of cuckoos, raptors, land use composition and background radiation Bird abundance per census point in Fukushima ranged between 0 and 51 individuals per point on average 5.82, SE ¼ 0.11, N ¼ 1500. Bird abundance in Chernobyl ranged between 0 and 32 individuals
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Fig. 1. Box plots of the distribution of data on raptor abundance, cuckoo abundance and background radiation for Fukushima, Japan (above) and Chernobyl, Ukraine (below). Box plots show medians, quartiles, 5- and 95-percentiles and extreme values.
Table 1 Fixed-effect parameters in a Generalized Linear Mixed Model, accounting for bird species richness in relation to number of avian top predators, number of cuckoos, land use composition and background radiation level in Fukushima and Chernobyl. Random effects: Country (groups ¼ 2), year (groups ¼ 28) and sites (groups ¼ 27). The table shows estimates, 95% confidence intervals (CI), SE, c2 and p values. Only significant variables are shown in the table. Predictors
Estimate
CI
SE
c2
p
Intercept No. raptors No. cuckoos Log radiation Farmland Bush
1.493 0.129 0.207 0.190 0.001 0.003
1.402/1.585 0.084/0.182 0.713/0.240 0.237/0.143 0.000/0.003 0.005/0.002
0.047 0.025 0.017 0.024 4.7e-4 6.5e-4
31.9 5.3 12.1 7.9 2.5 5.6
<0.05 <0.05 <0.05 <0.05 <0.05 <0.05
per census point, mean (SE) ¼ 6.70 (0.12), N ¼ 981. The sample sites without birds (0 individuals) represented less than 0.8% of the total recorded (19 cases from 2481). The best model showed that the number of avian raptors, number of cuckoos, bush percentage and background radiation were significant predictors of bird abundance in both countries (Table 3). The bird abundance decreased with level of ionizing radiation in both countries, increasing with number of raptors and with number of cuckoos (Table 3, Fig. 3). The bird abundance was also slightly but negatively correlated with bush (Table 3). Finally, the number of butterflies decreased with increasing level of ionizing radiation in Chernobyl, and that was also the case in Fukushima, however these differences were not statistically significant (Z ¼ 0.625, p ¼ 0.532, estimate (SE) ¼ 0.002 (0.002)).
There was no significant association between abundance of cuckoos and abundance of butterflies (Z ¼ 0.672, p ¼ 0.502, estimate (SE) ¼ 0.029 (0.043)).
4. Discussion We found significant associations between bird species richness and the abundance of cuckoos and avian top predators in Chernobyl and Fukushima. These effects were still present after inclusion of the degree of ionizing radiation as a covariate, implying that other mechanisms than the presence of cuckoos are at work. Furthermore, some characteristics of land use composition contributed to the variation in bird species richness (farmland and bush) and bird abundance (bush). The slight but positive association with farmland coverage can be explained by the fact that cultivated areas often support more different species than forestal areas, being more heterogeneous mosaics (Morelli et al., 2013). The negative effect of bush coverage in bird diversity, instead, it is less easy to be interpreted, and could be simply related to an opposite association between farmland and bush coverage. However, here we focused our effort on understanding the associations among birds, cuckoo abundance and raptors abundance and radiation level. Large-scale environmental perturbations like those in Chernobyl and Fukushima are interesting because they allow for tests of predictions derived from ecological and conservation biological theory across large spatial scales. The common cuckoo has been shown to be an efficient bioindicator of biodiversity in many European countries (Morelli et al., 2015; Tryjanowski and Morelli,
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Fig. 2. Associations between the number of avian top predators, number of cuckoos, background radiation and species richness of birds in Fukushima, Japan (above) and Chernobyl, Ukraine (below). The lines are estimates and 95% confidence intervals.
Table 2 List of GLMMs performed in this study, accounting for variation in bird species richness in relation to number of avian top predators, number of cuckoos, land use composition and background radiation level in Fukushima and Chernobyl. Random effects: Country (groups ¼ 2), year (groups ¼ 28) and sites (groups ¼ 27). The choice of the best model was performed using the model selection and multimodel inference based on Akaike's information criterion (AIC) in the package AICcmodavg from R (Mazerolle, 2016). Model
AIC
DAIC
Full model Cuckoos model (excluding raptors) Raptors model (excluding cuckoos)
9609.7 9634.1 9748.7
0.0 24.4 139.0
2015). In this study we extended our previous exploration of bioindicator capacities, to three different cuckoo species, using the number of cuckoos as proxy for overall species richness or abundance of birds in the community. Cuckoos are well-known for their obligate parasitism of other bird species (Davies, 2000; Erritzøe et al., 2012). We have previously shown that the bioindicator efficiency of common cuckoo is not only due to their close relationship with their hosts (Morelli et al., 2015). In fact, cuckoos are as efficient bioindicators for hosts as for non-hosts (Morelli et al. unpublished data). This suggests that other mechanisms are involved. Cuckoos have a main diet of large lepidopteran caterpillars (Erritzøe et al., 2012), which are characteristic herbivores of a range of different plant species (Dyer et al., 2007). Here we tested the possibility that at least part of the bioindicator ability of the abundance of cuckoos is due to links to butterfly caterpillars. However, here we could show that this was not the case.
Table 3 Fixed-effect parameters in a Generalized Linear Mixed Model, accounting for number of birds (bird abundance) in relation to number of avian top predators, number of cuckoos, land use composition and background radiation level in Fukushima and Chernobyl. Random effects: Country (groups ¼ 2), year (groups ¼ 28) and sites (groups ¼ 27). The table shows estimates, 95% confidence intervals (CI), SE, c2 and p values. Only significant variables are showed in the table. Predictors
Estimate
CI
SE
c2
p
Intercept No. raptors No. cuckoos Log radiation Bush
1.882 0.136 0.199 0.202 0.007
1.663/2.101 0.096/0.176 0.170/0.229 0.252/0.152 0.008/0.005
0.111 0.020 0.015 0.026 0.001
16.9 6.7 13.3 7.8 10.9
<0.05 <0.05 <0.05 <0.05 <0.05
Superficially, we might conclude that the reduction in number of birds of prey and cuckoos arose as a consequence of a reduction in the abundance of prey and hosts, respectively, However, that is not the case given that the abundance of cuckoos is as strong a predictor of species richness and abundance of hosts as on nonhosts (Morelli et al. unpublished data). Thus cuckoos are bioindicators of hosts and non-hosts alike, suggesting that their abundance reflects environmental conditions rather than the abundance of other bird species such as prey and hosts. The findings reported here may be explained as consequences of ecological traps or competive voids. Ecological traps arise from organisms moving into ecological settings where their fitness is reduced compared to what it might have been had they behaved differently (Dwernychuk and Boag, 1972; Gates and Gysel, 1978).
F. Morelli et al. / Journal of Environmental Radioactivity 177 (2017) 158e164
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Fig. 3. Associations between the number of avian top predators, number of cuckoos, background radiation and abundance of birds in Fukushima, Japan (above) and Chernobyl, Ukraine (below). The lines are estimates and 95% confidence intervals.
We have already published a study of barn swallows Hirundo rustica showing evidence consistent with ecological traps (Møller et al., 2006). We have additional census data of birds consistent with ecological traps. In contrast, competitive voids that may arise from the reduction in abundance or diversity of competitors due to radiation effects. We have no evidence consistent with this hypotheses. Finally, we consider it uniquely that this mechanism may account for the findings on cuckoos, because cuckoos are specialist consumers of large social butterfly caterpillars. The present study has additional implications. We have shown elsewhere that extreme environmental perturbations of the level of ionizing radiation affect the abundance and diversity of birds (Møller et al., 2015; Møller and Mousseau, 2007a, 2007b). Because both cuckoos and other birds are negatively affected by radioactive contamination, we hypothesize that it is partly ionizing radiation that is causing covariation between abundance and diversity of cuckoos on the one hand, and abundance and diversity of other species on the other. Similar explanations might also apply to other components of environmental change such as climate change and intensification of agriculture and forestry that are likely to impact many different species including the diversity and abundance of cuckoos. Clearly, this does not explain why cuckoos rather than raptors are prime bioindicators of species richness of birds. Here, we are providing new evidence on the old debate about the efficiency of avian top predators as potential indicators of hotspots of biodiversity (Cabeza et al., 2007; Roth and Weber, 2008). We demonstrated how the abundance of cuckoos is much more reliable than the abundance of raptor species as indicator of overall bird species richness and abundance even in highly disturbed
environments. Probably co-evolutionary interactions linking parasites to hosts are the main causes of the efficiency of cuckoos as indicators of species richness and abundance. We emphasize that similar arguments about coevolution between predators and prey cannot account for the patterns. This suggests that more tight ecological links than those caused by predators at the top position in a trophic food chain are required for them being suitable as more efficient bioindicators than brood parasites. In conclusion, we have shown that number of cuckoos is a reliable indicator of species richness and abundance of birds around Chernobyl and Fukushima, suggesting that even large scale environmental perturbation is reflected in the abundance of cuckoos, while that is the case to a much smaller extent for raptors. Appendix A. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.jenvrad.2017.06.029. References Armon, R.H., H€ anninen, O., 2015. Environmental Indicators. Springer, Netherlands doi:978-94-017-9498-5. Bates, D., Maechler, M., Bolker, B., Walker, S., 2015. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1e48. http://dx.doi.org/10.18637/ jss.v067.i01. Bates, D., Maechler, M., Bolker, B., Walker, S., 2014. lme4: Linear Mixed-Effects Models using Eigen and S4-R Package. Bibby, C.J., Hill, D.A., Burgess, N.D., Mustoe, S., 2005. Bird Census Techniques. Academic Press, London, UK. thode des indices ponctuels Blondel, J., Ferry, C., Frochot, B., 1970. La me
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