- Research article
- Open Access
Changes of diet and dominant intestinal microbes in farmland frogs
- Chun-Wen Chang†1, 2,
- Bing-Hong Huang†1,
- Si-Min Lin1,
- Chia-Lung Huang1 and
- Pei-Chun Liao1Email author
© Chang et al. 2016
- Received: 17 June 2015
- Accepted: 2 March 2016
- Published: 10 March 2016
Agricultural activities inevitably result in anthropogenic interference with natural habitats. The diet and the gut microbiota of farmland wildlife can be altered due to the changes in food webs within agricultural ecosystems. In this work, we compared the diet and intestinal microbiota of the frog Fejervarya limnocharis in natural and farmland habitats in order to understand how custom farming affects the health of in vivo microbial ecosystems.
The occurrence, abundance, and the numbers of prey categories of stomach content were significantly different between the frogs inhabiting natural and farmland habitats. In addition, differences in the abundance, species richness, and alpha-diversity of intestinal microbial communities were also statistically significant. The microbial composition, and particularly the composition of dominant microbes living in intestines, indicated that the land use practices might be one of factors affecting the gut microbial community composition. Although the first three dominant microbial phyla Bacteroidetes, Firmicutes, and Proteobacteria found in the intestines of frogs were classified as generalists among habitats, the most dominant gut bacterial phylum Bacteroidetes in natural environments was replaced by the microbial phylum Firmicutes in farmland frogs. Increased intestinal microbial richness of the farmland frogs, which is mostly contributed by numerous microbial species of Proteobacteria, Actinobacteria, Acidobacteria, and Planctomycetes, not only reflects the possible shifts in microbial community composition through the alteration of external ecosystem, but also indicates the higher risk of invasion by disease-related microbes.
This study indicates that anthropogenic activities, such as the custom farming, have not only affected the food resources of frogs, but also influenced the health and in vivo microbial ecosystem of wildlife.
- Custom farming
- Fejervarya limnocharis
- Gut microbiota
The gastrointestinal tract is the primary site where microorganisms interact with the host species. The gastrointestinal microbiota maintains the functions of nutrient, immune, and development regulation and is important for host health [1–4]. The gut microbiota is commonly influenced by the host diet [3, 5]. The composition of the intestinal microbial community is suggested to result from natural selection operating at the host level to stabilize the gut environment and at the microbial level to promote functional specialization . The relative abundance of symbionts and pathogenic microbes reflects the health status of the host species . Microbial interactions, e.g., resource competition, represent a deterministic factor for the dominance of the gastrointestinal microbial community . Diets serve as a source of gut microbes, which are further selected by the gastrointestinal environment.
The gastrointestinal microbes are composed of autochthonous components (residents) and allochthonous members (hitchhikers from ingested food and waters). Species composition of the gastrointestinal microbial community is different from that of environmental microbes . Firmicutes and Bacteroidetes are the most abundant gastrointestinal microbial phyla [10–14] that were suggested to descend from the early colonists in mammalian gut evolution , while Proteobacteria was found to be most dominant in tadpoles , house sparrow , and fish . The codominance of these phyla was suggested to be a consequence of niche partitioning and metabolic complementation . A healthy gut microbial community occupied by native bacteria could establish a selective environment to prevent emerging pathogens from building up a necessary population size to cause disease. The native microbes can prevent other similar taxa for colonization by high density blocking, and this effect is like the “founder-takes-all” effect of the field of population ecology . However, such “founder-takes-all” effect  could be vanished if fast colonization by abundant allochthonous microbes . Here, host immunity not only plays a role as a selective pressure on intestinal microbes but also an object of natural selection by the emerging microbes.
Since the importance of relationships between the food web complexity and species composition in an ecosystem, and between the diet content and intestinal microbiome is emphasized in literature , we aimed to explore whether the change in ecosystems as a result of agricultural activities alters the intestinal microbial composition of wildlife. Agricultural activities affect the distribution of wildlife in the natural environment. Farmland biodiversity is typically lower than that in natural fields, which is reflected in a widespread decline of species richness and/or abundance of farmland wildlife [20–23]. Custom farming and agricultural intensification that rely on the use of fertilizers and pesticides recurrently create selective pressures not only on vertebrates, but also on invertebrates [24, 25], plants [26, 27], and soil microbes [28, 29]. The change in land use alters the nutrient cycling of soil, which affects the diversity and abundances of numerous environmentally important genes of microbes . Changes in nutrient cycling affect the food webs of ecosystems , and changes in heterotrophic processes and diet diversity can further alter the digestive-tract microbiome of animals .
In this study, we used the rice frog Fejervarya limnocharis (Gravenhorst, 1829) (Amphibia, Anura, Ranidae) as a system to compare the food composition (diet) and intestinal microbiota between natural and farmland frog populations. Fejervarya limnocharis is widespread in East, Southeast, and South Asia. In Taiwan, it is one of the dominant amphibian species in lowland areas and is commonly found in farmlands. The Taiwanese F. limnocharis is phylogenetically inferred as a member of the core F. limnocharis group based on mtDNA and allozyme evidence [33, 34]. In this study, we profiled the diet and intestinal microbial composition of F. limnocharis in natural and farmland habitats. Comparisons of the stomach contents and dominant intestinal microbes were made to understand the changes of intestinal microbiota under the selective pressure of environmental change, such as the habitat variation due to agricultural activities. The multiple comparisons allowed us to address three questions: (1) Is there any dietary difference between frogs living in different habitats? (2) Does the intestinal bacterial diversity differ within and between frogs living in different habitats? (3) Does the compositional change in intestinal microbiota reflect the health of the in vivo microbial ecosystem in farmland frogs?
Diet differentiation between habitats
Stomach contents of F. limnocharis in natural habitat and farmlands
Comparison of stomach contents of rice frog (Fejervarya limnocharis) between two habitats by Wilcoxon rank-sum test
Number of prey item
1 ~ 10
1 ~ 3
Number of prey category
1 ~ 4
1 ~ 2
Volume of prey(mm3)
2.09 ~ 396.05
0.78 ~ 78.54
Sequencing depth and alpha-diversity of intestinal microbiota
Alpha-diversity of intestinal microbiota of rice frogs (Fejervarya limnocharis) at the natural habitat (N1 ~ N3) and farmland (F1 ~ F3)
ACE (95 % CI)
Chao1 (95 % CI)
Shannon index (95 % CI)
Simpson index (95 % CI)
640.451 (609.752, 684.662)
653.554 (611.576, 720.152)
720.152 (4.850, 4.907)
4.907 (0.022, 0.025)
361.315 (334.879, 403.679)
370.875 (334.723, 436.919)
436.919 (3.522, 3.583)
3.583 (0.085, 0.091)
524.321 (501.485, 559.152)
541.720 (507.338, 600.063)
600.063 (3.398, 3.442)
3.442 (0.100, 0.104)
797.248 (759.731, 848.877)
794.101 (749.071, 861.895)
861.895 (4.950, 5.001)
5.001 (0.018, 0.019)
1358.822 (1287.073, 1449.218)
1385.211 (1289.752, 1513.360)
1513.360 (5.275, 5.320)
5.320 (0.013, 0.014)
863.048 (797.642, 949.057)
839.505 (766.514, 942.678)
942.678 (2.928, 2.993)
2.993 (0.148, 0.155)
Dominant intestinal microbial taxa in rice frogs
Classification of gut bacteria
Intestinal microbial organisms were classified into three categories—generalists, specialists, and too rare—based on the multinomial species classification method. Eight phyla were habitat generalists (Firmicutes, Bacteroidetes, Proteobacteria, Spirochaetae, Lentisphaerae, Deferribacteres, Cyanobacteria, and Planctomycetes), ten were farmland specialists (Fusobacteria, Actinobacteria, Verrucomicrobia, Deinococcus-Thermus, Acidobacteria, Elusimicrobia, Synergistetes, Chloroflexi, Gemmatimonadetes, and one unclassified phylum), one was a natural-habitat specialist (Tenericutes), and ten phyla were too rare to be identified (Additional file 1: Table S3 and Additional file 4: Figure S3). At the species level, we found that 44 (8.1 %), 34 (6.3 %), 82 (15.2 %), and 381 (70.4 %) OTUs belonged to the generalist, natural-habitat specialist, farmland specialist, and too-rare types, respectively (Additional file 1: Table S4 and Additional file 4: Figure S3). This classification indicated that relatively low proportions of common gastrointestinal bacteria are found in both natural and farmland habitats and that approximately one-fifth of the bacteria differentiate the gut microbiota between habitats, while most microorganisms are rare in these habitats. We also performed pairwise comparisons of the gut microbial community of different host individuals and found a relatively high proportion of generalists and a lower proportion of specialists in gut bacterial communities of frogs within habitats (generalists: 13.97 % ± 1.59 %; specialists: 26.62 % ± 2.98 %) than those seen for frogs between habitats (generalists: 9.67 % ± 0.99 %; specialists: 30.83 % ± 1.28 %). However, these differences were not statistically significant, indicating that the individual effect cannot be neglected while explaining gut microbial diversity (Additional file 5: Figure S4).
The differences in stomach contents of rice frogs may reflect the changes in faunal species composition. There were long-term anthropogenic disturbance such as the use of fertilizers and pesticides in custom farming. These anthropogenic activities may alter the faunal species composition in farming habitat although the invertebrate fauna of both natural and farmlands were not directly investigated. The diet analysis showed that the food volume of rice frogs was not significantly different between the natural and farmland habitats, but the stomach content (abundance and number of prey categories) in farmland frogs showed lower diversity than that in frogs from natural habitats. Such dietary alteration is probably ascribed to agricultural activities. The increase of soil life (700 % increase of megafauna, 2500 % increase of nematodes, and 70 % increase of soil microorganisms) in 14-year of monitoring conservation agriculture and organic farming indicated the harmful effects of pesticides and fertilizers on the terrestrial ecosystem . In this study, the decreased number of prey categories in the guts of farmland frogs did not only point to the presence of simplified invertebrate and plant communities in farmlands and the decreased IRI of Hymenoptera (Fig. 2a), but also reflected the reduction of pollinator demand in the plant community . In contrast, the increase in the IRI of Orthoptera (Fig. 2a) often suggested an increase in monocot abundance, particularly of the Poaceae [37–39]. The dietary analysis suggested the occurrence of dramatic changes in the farmland ecosystem due to agricultural activities.
Conventional agriculture or custom farming may strongly alter the species composition in many ways . For example, habitat destruction during farming may reduce diet resources and subsequently alter gastrointestinal microbiome composition in the howler monkey (Alouatta pigra) . Habitat degradation following temperature change  and water pollution  can also subsequently alter amphibian gut microbiota. Research on the microbial composition surrounding the forest soils revealed similar dominant microbes among different forest types with slight difference in microbiota . This is similar to our findings that the dominant gut bacteria are habitat generalists and most gut microbes belong to the “too-rare” type bacteria. However, we found that approximately one-fifth of the gut bacteria were habitat specialists (Additional file 1: Table S3 and S4), indicating that the varied habitat indeed altered the gut microbial composition.
Our results suggest that the estimated intestinal microbial species richness in frog guts varied within the same order of magnitude as that in the human gut, as estimated based on fecal analysis . The gut microbiota is mainly determined by the environmental conditions where the host species reside . Although relatively few frog samples were chosen to represent the gut microbiota of rice frogs, the gut environments of different frog individuals from the same habitat may be similar because frogs from the same habitat might share similar niches. The digestive fluid secreted from some specialized cells in the epithelium of the small intestine, which maintains a stable environment in the gut [45, 46]. Therefore, the dominant gut bacteria could be similar among frogs with similar habitats because the coexistence of these dominant bacteria reflects the consequence of long-term selection in the gut environment. We also found that both dominant gut bacterial species in the natural habitat (Candidatus Hepatincola, uncultured α-Proteobacterium, total of 21.02 %) and farmland habitat (Morganella sp., total of 10.95 %) were habitat specialists, indicating that the external environment plays a major role in the gut-dominant bacteria in frogs.
On comparing the microbial species composition, a certain proportion of common microbial taxa (approximately 1/3 ~ 1/2) was similar between frogs from natural habitats and farmlands, revealing the host species specificity of microbes (Additional file 3: Figure S2). The same pattern of similar taxa in different microbial communities of diet-differentiated, geographically distant host populations was also found in wild and laboratory Drosophila  and Cylindroiulus fulviceps (Diplopoda) with different feeding treatments . However, the higher proportion of bacterial habitat specialists than habitat generalists suggested that external factors such as diet, geographic variation, and the environment still play major roles in determining the gut microbial composition (Additional file 4: Figure S3). Differences in dominant taxa, revealed by different clusters in phylogenetic analysis (Fig. 4), suggested strong selectivity of the microbial community in the gut environment .
The microbial abundances between frogs of natural habitat and farmland are different, especially in Bacteroidetes and Firmicutes. These two phyla are the most prevalent bacteria in digestive tracts of terrestrial animals [50, 51]. In natural population, Bacteroidetes are the mostly abundant microbes in rice frogs’ intestines followed by Firmicutes, but the abundance of Bacteroidetes is lower than Firmicutes in farmland population (Fig. 2b). The Bacteroidetes of the frogs of natural habitats were mostly composed of the order Bacteroidales (Fig. 4). Bacteroidales are known as symbiotic bacteria essential for the digestive activity of several organisms [1, 16, 25, 48, 52, 53]. However, the abundance of Bacteroidetes decreased in farmland frogs and was replaced by Firmicutes (Fig. 2b). Higher Firmicutes-to-Bacteroidetes ratio could improve the efficiency of calories uptake from food . These Firmicutes microbes were almost composed of Ruminococcaceae and Lachnospiraceae, which digest cellulose and ferment glucose and xylose to obtain nutrients and are the prevalent bacterial families in herbivore’s digestive system . The ecological meaning of the increased abundance of Ruminococcaceae and Lachnospiraceae in farmland frogs’ intestine is unknown yet, but the high Firmicutes-to-Bacteroidetes ratio suggests that the alteration of food composition might change the intestinal environments and microbial community in farmland frogs.
The differences in dominant intestinal microbial taxa between natural habitats and farmlands revealed in NJ analysis indicated that the frogs acquired different bacteria due to the changes in environmental conditions. In contrast to the high frequency of common microbial taxa in frogs from natural habitats, the intestinal microbial communities of farmland frogs were characterized by higher ratios of unique microbes (Additional files 2 and 3: Figure S1 and S2). These unique microbes mostly belonged to Proteobacteria, Actinobacteria, Acidobacteria, and Planctomycetes (Fig. 3). From the analysis of the top 10 microbial organisms of every frog intestinal samples, we found that the Classes of γ-Proteobacteria in farmland frogs have an obvious increase in abundance (19.75 %) than the frogs of natural habitats (0.05 %). Although γ-Proteobacteria is common in guts of diverse taxa including amphibians [e.g., House Sparrow (Passer domesticus) , leopard frog (Lithobates pipiens) ], most of the γ-Proteobacteria in farmland frogs belong to the order Enterobacteriales (72.91 %) (Fig. 4). Several intestinal bacteria that are dominant in the farmland frogs, such as species in the genera Treponema (Spirochaetes), Roseomonas (α-Proteobacteria), Clostridium (Firmicutes) and genera Legionella, Acinetobacter, Pseudomonas, Citrobacter, Morganella of γ-Proteobacteria (Fig. 4), were probably infectious disease-related pathogens. These bacterial genera are clinically proven to cause emerging infectious diseases (EID) not only in humans (e.g., Legionella [56, 57]; Acinetobacter [57–59]; Pseudomonas [60, 61]; Citrobacter [62, 63]; Morganella [64, 65]; Treponema [66, 67]; Roseomonas [68–70], and Clostridium [71, 72]), but also in amphibian (for example, Acinetobacter would cause ulceration and necrosis in Rhinoderma darwini , Pseudomonas and Citrobacter might induce immune-response in Rana pipiens [74, 75], and so did the Morganella in Andrias davidianus .)
These bacteria mostly belong to the Proteobacteria. Several Proteobacteria have pathogenic or antipathogenic functions in amphibians, for example, Janthinobacterium lividum in amphibian guts can inhibit the growth of lethal amphibian fungi [77, 78]. Certain antifungal bacteria from the genus Pseudomonas that were discovered on the skin of amphibians, that is, the salamander (Plethodon cinereus and Hemidactylium scutatum) [79, 80] and the frog (Rana muscosa) ), were also found in leopard frogs (Rana pipiens) ). The intestines of amphibians could serve as the reservoir for these antifungal bacteria via uptake of invertebrates that have come into contact with these bacteria in the soil or by eating their own shed skin . The dynamics of these bacteria may be an indicator of host susceptibility to these lethal fungi . These Proteobacteria were previously found in smaller amounts than Bacteroidetes and Firmicutes in healthy adult mammals  and human gastrointestinal samples  and in the frogs from natural habitats investigated in this study.
In addition to the phylum Proteobacteria, certain bacterial genera, such as Flavobacterium in phylum Bacteroidetes and Actinobacterium and Bacillus in phylum Firmicutes, that are chytrid-resistant or have probiotic capabilities were mostly found in the gut of frogs in the farmland habitat (sequence reads = 21, 59, and 4 in Flavobacterium, Actinobacterium, and Bacillus, respectively) but rarely in the natural habitat (sequence reads = 1, 4, and 0, respectively). The higher proportion of pathogen-resistant bacteria found in farmland frogs reflected the higher occurrence rate of harmful pathogens in the farmland habitat. The intestinal microbial composition in frogs from farmlands was possibly under a high risk of infectious diseases. Because stomach content is a proxy of food source in the natural environment, the differences in intestinal microbiota between farmland and natural habitats did not only explain the dietary alteration, but also reflected the risk of disease in farmland wildlife due to the ecosystem alterations as a result of anthropogenic activities.
Intestinal microbiota can possibly reflect the state of the immune system and health of the host species . Different microbial composition in frog guts may be related to pathogen resistance, for example, differential antifungal bacterium composition between populations may be important in preventing chytrid fungus infections . Differentiation of gut microbial composition could even reflect overall body healthy of frogs. We found lower food diversity but higher intestinal microbial richness in farmland frogs than in natural habitats. This can possibly be explained by the recurrent selective pressures from agricultural activities simplifying the farmland fauna and increasing the risks of infectious disease in frog predators. Simplified food sources could also weaken the immunity of wild animals and lead to higher pathogen invasion . Disturbance in gut microbial composition and microbial and ecological dynamics can lead to an increased risk of disease outbreaks in wildlife , or provide less anti-pathogen reservoir for preventing infection of skin pathogen . Anthropogenic ecosystem alteration and pathogen or vector movements via human or natural agencies could give rise to EID in wildlife [87, 88]. In this study, we showed that anthropogenic interference in ecosystem (such as agricultural activities) and a change of “vectors” (food contents) can weaken frog immunity, which is reflected in the change of intestinal microbial climax.
Alterations in diet and intestinal microbial composition in farmland F. limnocharis indicate that custom farming influences the intestinal ecosystem of wildlife. Food may not only play a resource role but also be one of the factors serve as a vector of infectious microbes. The intestinal microbial composition reflected the result of intestinal environmental selection by both extrinsic (environment, such as habitat disturbance, temperature, and food) and intrinsic (immune system) factors. In the farmland habitat, less diverse food content and more diverse intestinal microbiota in frogs were found than in natural habitats. This result suggests that the in vitro ecosystem changes in vivo ecosystem. The intestinal microbiota of F. limnocharis was determined by both environmental factors and host species, whereas the dominant intestinal microbes were more easily affected by external environmental conditions than were the rare microbes. The increased numbers of Proteobacteria suggested that pathogenic invasion was affected or will be affected by the weakened immunity of farmland frogs, which is probably caused by the heavy use of pesticides and fertilizers in farmland. The current study revealed the change in food resources and intestinal microbial diversity in farmland wildlife, and also suggested that outbreaks of disease-related bacteria within the gut microbial community can reflect the damage of in vivo and in vitro ecosystem health due to agricultural interference. It should be notified that the small sample size of frogs in this study may not be sufficient to draw strong conclusions, but could be indicative of changes across habitats. Even though, this research still represents different microbial composition between habitats and provides a reference for future studies regarding the amphibians’ gastrointestinal microbiota.
Fejervarya limnocharis is a medium-sized frog with an average body length of 4.3 cm and 5.5 cm in males and females, respectively . This species is widespread in lowland areas at altitudes below 1500 m in Taiwan. F. limnocharis generally aggregates around breeding ponds during the breeding season from spring to summer. F. limnocharis is tolerant to human disturbance, and therefore is commonly found in farmlands. Forty frog samples were collected from Hualin experimental forest (the natural habitat, 24°53′N, 121°33′E) and farmlands in Quchi Community (24°55′N, 121°32′E) in Xindian (Dist., New Taipei City, Taiwan) on September 27th, 2012. The distance between these two sites is less than 3 km. All frog samples were brought to the laboratory of Nation Taiwan Normal University for immediate profiling of diets and intestinal microbial composition.
Frog samples were sacrificed and preserved in 70 % ethanol. Stomach content of frogs (prey) was collected via dissection and stored in 70 % ethanol. The length and width of the stomach content items were measured using cartesian papers and the prey items were identified to order level under a stereomicroscope. The volume of prey items was estimated using the formula proposed by Dunham . For assessing the importance of each consumed prey category, the IRI was calculated based on the formula IRI = %O (%N + %V) , where %O, %N, and %V are the percentages of the occurrence, relative abundance, and measured volume of each prey category, respectively, in all stomachs. The intake rate (which describes the prey eaten by F. limnocharis) between habitats was compared using the Chi-square test. The numbers, categories, and volumes of stomach contents were compared between habitats using Wilcoxon rank-sum test. All statistical analyses were conducted using JMP 7.0.
The gut microbes of six frog samples from the natural environment (N1 ~ N3) and farmland (F1 ~ F3) were used for exploring the influence of food composition on intestinal microbial composition. Intestinal microbial metagenomic DNA was extracted based on a protocol described by Sharma et al. . For each sample, we amplified the V4 hypervariable 16S rRNA region using the primer set 27 F (5′-AGAGTTTGATCCTGGCTCAG-3′) and 533R (5′-TTACCGCGGCTGCTGGCAC-3′). The DNA library was constructed according to the Roche GS FLX Titanium emPCR kit (Roche Applied Science). Pyrosequencing was carried out by Welgene Biotech Co., Ltd. (Taipei, Taiwan) using a Roche 454 FLX titanium instrument and reagents following the manufacturer’s instructions. The V4 sequence fragments shorter than 200 bp, without barcodes, with polyN or polyA/T, and the reads with < Q25 were removed. Sequences with >97 % identity were treated as the same species and as an operational taxonomic unit (OTU). Each OTU was classified by annotating to the SILVA database. The alpha-diversity of the gut microbiota was estimated using community richness indices, i.e., the ACE , the Chao1 index [50, 94], and community diversity indices, i.e., the Shannon index and Simpson index. Indices ACE, Chao1, Shannon index and Simpson index between habitats were compared. Because the small sample size could result in non-normal distribution, we regenerated 20 normalized pseudodata based on the mean and standard deviation from the observed data, and performed 99,999 times permutations for a one-sample randomization test on differences of values between habitats. Validation of t-test was given by similar p-values before and after permutations. Rarefaction analysis was executed to measure how the gut microbial composition of the rice frog varied depending on the sample size.
After determination of the microbial diversity, the differences in the gut microbial composition of rice frogs between the natural and the farmland populations was examined by phylogenetic analysis. The neighbor-joining (NJ) method was used for constructing a genetic-distance tree to elucidate the genetic distribution patterns of intestinal microbes between different habitats. Nucleotide sequence alignments were performed using the Clustal W program. The evolutionary distances were computed using the p-distance method. The NJ tree was constructed using the program MEGA v. 5.05 . The NJ relationships of six dominant microbial phyla Bacteroidetes, Firmicutes, Proteobacteria, Planctomycetes, Actinobacteria, and Acidobacteria were reconstructed separately for revealing the grouping patterns of intestinal microbes between different habitats. In addition, every top 10 microbial OTUs of frogs (yielding a total 51 OTUs) were used to construct a genetic-distance tree using the NJ method for clearly representing the systematic positions of the dominant intestinal microbes of frogs in natural habitats and farmlands, with the following settings: the composite likelihood substitution model , the uniform rate among sites, the heterogeneous rates among lineages and complete deletion of gaps. A 1000 bootstrap replication was used to evaluate the supporting values for lineage grouping.
We also used the multinomial species classification method (CLAM)  to classify the bacteria of generalists and specialists in two distinct habitats with the vegan package in R. CLAM is a kind of two-group species classification method. The supermajority rule that uses the specialization threshold value 2/3 was adopted for determining the bacteria of habitat specialists. Under the supermajority rule, the minimum abundance for classification (i.e., coverage limit) was estimated and the taxa that had abundance below the coverage limit were considered as “too rare”. CLAM was also used for pairwise comparison between host individuals within habitats and between habitats. Comparisons of the proportions of generalists and specialists between “within habitats” and “between habitats” aid in understanding the degree of individual effect on gut microbial diversity.
Availability of data and materials
The 16S rDNA sequences identified in this study have been deposited in the NCBI GenBank under the Bioproject PRJNA279212 (Accession number: SRX965751). Frog samples were stored in the specimen room of Department of Life Science, National Taiwan Normal University.
Protocols of this study and the animal use were reviewed and approved by the Ethics Committee of National Pingtung University of Science and Technology (NPUST) (Approved No. NPUST-101-079) and the Institutional Animal Care and Use Committee of National Taiwan Normal University (Approved No. 101024).
We are grateful for the constructive comments from Chun-Yao Chen on earlier drafts of this manuscript. This research was financially supported by the National Science Council in Taiwan (NSC 102-2621-B-003-005-MY3) and was also subsidized by the National Taiwan Normal University (NTNU), Taiwan.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
- Hooper LV, Midtvedt T, Gordon JI. How host-microbial interactions shape the nutrient environment of the mammalian intestine. Annu Rev Nutr. 2002;22:283–307.View ArticlePubMedGoogle Scholar
- Round JL, Mazmanian SK. The gut microbiota shapes intestinal immune responses during health and disease. Nat Rev Immunol. 2009;9(5):313–23.View ArticlePubMedPubMed CentralGoogle Scholar
- Nicholson JK, Holmes E, Kinross J, Burcelin R, Gibson G, Jia W, et al. Host-gut microbiota metabolic interactions. Science. 2012;336(6086):1262–7.Google Scholar
- Hooper LV, Gordon JI. Commensal host-bacterial relationships in the gut. Science. 2001;292(5519):1115–8.View ArticlePubMedGoogle Scholar
- Zhang CH, Zhang MH, Wang SY, Han RJ, Cao YF, Hua WY, Mao YJ, Zhang XJ, 499 Pang XY, Wei CC, et al. Interactions between gut microbiota, host genetics and diet relevant to development of metabolic syndromes in mice. ISME J. 2010;4(2):232–41.Google Scholar
- Ley RE, Peterson DA, Gordon JI. Ecological and evolutionary forces shaping microbial diversity in the human intestine. Cell. 2006;124(4):837–48.View ArticlePubMedGoogle Scholar
- Sekirov I, Russell SL, Antunes LCM, Finlay BB. Gut microbiota in health and disease. Physiol Rev. 2010;90(3):859–904.View ArticlePubMedGoogle Scholar
- Savage DC. Microbial ecology of the gastrointestinal tract. Annu Rev Microbiol. 1977;31:107–33.View ArticlePubMedGoogle Scholar
- Ley RE, Lozupone CA, Hamady M, Knight R, Gordon JI. Worlds within worlds: evolution of the vertebrate gut microbiota. Nat Rev Microbiol. 2008;6(10):776–88.View ArticlePubMedPubMed CentralGoogle Scholar
- Eckburg PB, Bik EM, Bernstein CN, Purdom E, Dethlefsen L, Sargent M, Gill SR, 512 Nelson KE, Relman DA. Diversity of the human intestinal microbial flora. Science. 2005;308(5728):1635–8.Google Scholar
- Hayashi H, Sakamoto M, Benno Y. Phylogenetic analysis of the human gut microbiota using 16S rDNA clone libraries and strictly anaerobic culture-based methods. Microbiol Immunol. 2002;46(8):535–48.View ArticlePubMedGoogle Scholar
- Hold GL, Pryde SE, Russell VJ, Furrie E, Flint HJ. Assessment of microbial diversity in human colonic samples by 16S rDNA sequence analysis. FEMS Microbiol Ecol. 2002;39(1):33–9.View ArticlePubMedGoogle Scholar
- Suau A, Bonnet R, Sutren M, Godon JJ, Gibson GR, Collins MD, Dore J. Direct analysis of genes encoding 16S rRNA from complex communities reveals many novel molecular species within the human gut. Appl Environ Microbiol. 1999;65(11):4799–807.PubMedPubMed CentralGoogle Scholar
- Kohl KD, Cary TL, Karasov WH, Dearing MD. Restructuring of the amphibian gut microbiota through metamorphosis. Environ Microbiol Rep. 2013;5(6):899–903.View ArticlePubMedGoogle Scholar
- Leticia M, Alex M, Victor R-R, Pedro B-F, Raúl C-R, Jorge F-M, René C-V, 528 Alexander D, Ana Lilia H, Jorge S. Gut bacterial diversity of the House Sparrow (Passer domesticus) inferred by 16 s rRNA sequence analysis. Metagenomics. 2014;3.Google Scholar
- Sullam KE, Essinger SD, Lozupone CA, O’Connor MP, Rosen GL, Knight R, Kilham SS, Russell JA. Environmental and ecological factors that shape the gut bacterial communities of fish: a meta-analysis. Mol Ecol. 2012;21(13):3363–78.View ArticlePubMedGoogle Scholar
- Waters JM, Fraser CI, Hewitt GM. Founder takes all: density-dependent processes structure biodiversity. Trends Ecol Evol. 2013;28(2):78–85.View ArticlePubMedGoogle Scholar
- Natsopoulou ME, McMahon DP, Doublet V, Bryden J, Paxton RJ. Interspecific competition in honeybee intracellular gut parasites is asymmetric and favours the spread of an emerging infectious disease. Proc Royal Soc B Biol Sci. 2015;282(1798):20141896.View ArticleGoogle Scholar
- Ley RE, Hamady M, Lozupone C, Turnbaugh PJ, Ramey RR, Bircher JS, Schlegel 542 ML, Tucker TA, Schrenzel MD, Knight R, et al. Evolution of mammals and their gut microbes. Science. 2008;320(5883):1647–51.Google Scholar
- Kozakiewicz M, Kozakiewicz A. Long-term dynamics and biodiversity changes in small mammal communities in a mosaic of agricultural and forest habitats. Ann Zool Fenn. 2008;45(4):263–9.View ArticleGoogle Scholar
- Siriwardena GM, Baillie SR, Buckland ST, Fewster RM, Marchant JH, Wilson JD. Trends in the abundance of farmland birds: a quantitative comparison of smoothed Common Birds Census indices. J Appl Ecol. 1998;35(1):24–43.View ArticleGoogle Scholar
- Greenwood JJ. A second silent spring? Trends Ecol Evol. 1995;10(7):264–6.View ArticlePubMedGoogle Scholar
- Fuller RJ, Gregory RD, Gibbons DW, Marchant JH, Wilson JD, Baillie SR, Carter N. Population declines and range contractions among lowland farmland birds in Britain. Conserv Biol. 1995;9(6):1425–41.View ArticleGoogle Scholar
- Wardle DA, Nicholson KS, Bonner KI, Yeates GW. Effects of agricultural intensification on soil-associated arthropod population dynamics, community structure, diversity and temporal variability over a seven-year period. Soil Biol Biochem. 1999;31(12):1691–706.View ArticleGoogle Scholar
- Coyne MJ, Zitomersky NL, McGuire AM, Earl AM, Comstock LE. Evidence of extensive DNA transfer between Bacteroidales species within the human gut. Mbio. 2014;5(3):e01305–14.Google Scholar
- Sotherton NW, Self MJ. Changes in plant and arthropod diversity on lowland farmland: an overview. In: The ecology and conservation of Lowland farmland birds: 2000; the University of Southampton, UK. British Ornithologists' Union: 26–35.Google Scholar
- Jose-Maria L, Armengot L, Blanco-Moreno JM, Bassa M, Sans FX. Effects of agricultural intensification on plant diversity in Mediterranean dryland cereal fields. J Appl Ecol. 2010;47(4):832–40.View ArticleGoogle Scholar
- Dong WY, Zhang XY, Dai XQ, Fu XL, Yang FT, Liu XY, Sun XM, Wen XF, Schaeffer S. Changes in soil microbial community composition in response to fertilization of paddy soils in subtropical China. Appl Soil Ecol. 2014;84:140–7.View ArticleGoogle Scholar
- Berthrong ST, Buckley DH, Drinkwater LE. Agricultural management and labile carbon additions affect soil microbial community structure and interact with carbon and nitrogen cycling. Microb Ecol. 2013;66(1):158–70.View ArticlePubMedGoogle Scholar
- Paula FS, Rodrigues JLM, Zhou JZ, Wu LY, Mueller RC, Mirza BS, et al. Land use change alters functional gene diversity, composition and abundance in Amazon forest soil microbial communities. Mol Ecol. 2014;23(12):2988–99.Google Scholar
- Deangelis DL, Mulholland PJ, Palumbo AV, Steinman AD, Huston MA, Elwood JW. Nutrient dynamics and food-web stability. Annu Rev Ecol Syst. 1989;20:71–95.View ArticleGoogle Scholar
- Bolnick DI, Snowberg LK, Hirsch PE, Lauber CL, Knight R, Caporaso JG, Svanback R. Individuals’ diet diversity influences gut microbial diversity in two freshwater fish (threespine stickleback and Eurasian perch). Ecol Lett. 2014;17(8):979–87.View ArticlePubMedPubMed CentralGoogle Scholar
- Sumida M, Kotaki M, Islam MM, Djong TH, Igawa T, Kondo Y, et al. Evolutionary relationships and reproductive isolating mechanisms in the rice frog (Fejervarya limnocharis) species complex from Sri Lanka, Thailand, Taiwan and Japan, inferred from mtDNA gene sequences, allozymes, and crossing experiments. Zool Sci. 2007;24(6):547–62.Google Scholar
- Islam MM, Khan MMR, Tjong DH, Alam MS, Sumida M. Genetic differentiation of the Fejervarya limnocharis complex from Bangladesh and other Asian countries elucidated by allozyme analyses. Zool Sci. 2008;25(3):261–72.View ArticlePubMedGoogle Scholar
- Henneron L, Bernard L, Hedde M, Pelosi C, Villenave C, Chenu C, Bertrand M,Girardin C, Blanchart E. Fourteen years of evidence for positive effects of conservation agriculture and organic farming on soil life. Agron Sustain Dev. 2015;35(1):169–81.View ArticleGoogle Scholar
- Holzschuh A, Steffan-Dewenter I, Kleijn D, Tscharntke T. Diversity of flower-visiting bees in cereal fields: effects of farming system, landscape composition and regional context. J Appl Ecol. 2007;44(1):41–9.View ArticleGoogle Scholar
- Odum EP, Connell CE, Davenport LB. Population energy flow of three primary consumer components of old-field ecosystems. Ecology. 1962;43(1):88–96.View ArticleGoogle Scholar
- Smalley AE. Energy flow of a salt marsh grasshopper population. Ecology. 1960;41(4):672–7.View ArticleGoogle Scholar
- Hook Jr RIV. Energy and nutrient dynamics of spider and Orthopteran populations in a grassland ecosystem. Ecol Monogr. 1971;41(1):1–26.View ArticleGoogle Scholar
- Amato KR, Yeoman CJ, Kent A, Righini N, Carbonero F, Estrada A, Gaskins HR, 610 Stumpf RM, Yildirim S, Torralba M,et al. Habitat degradation impacts black howler monkey (Alouatta pigra) gastrointestinal microbiomes. ISME J. 2013;7(7):1344–53.Google Scholar
- Gossling J, Loesche WJ, Nace GW. Response of intestinal flora of laboratory-reared leopard frogs (Rana pipiens) to cold and fasting. Appl Environ Microbiol. 1982;44(1):67–71.PubMedPubMed CentralGoogle Scholar
- Kohl KD, Cary TL, Karasov WH, Dearing MD. Larval exposure to polychlorinated biphenyl 126 (PCB-126) causes persistent alteration of the amphibian gut microbiota. Environ Toxicol Chem. 2015;34(5):1113–8.View ArticlePubMedGoogle Scholar
- Lin YT, Hu HW, Whitman WB, Coleman DC, Chiu CY. Comparison of soil bacterial communities in a natural hardwood forest and coniferous plantations in perhumid subtropical low mountains. Bot Stud. 2014;55:50.View ArticleGoogle Scholar
- Knapp BA, Podmirseg SM, Seeber J, Meyer E, Insam H. Diet-related composition of the gut microbiota of Lumbricus rubellus as revealed by a molecular fingerprinting technique and cloning. Soil Biol Biochem. 2009;41(11):2299–307.View ArticleGoogle Scholar
- Bevins CL, Salzman NH. Paneth cells, antimicrobial peptides and maintenance of intestinal homeostasis. Nat Rev Microbiol. 2011;9(5):356–68.View ArticlePubMedGoogle Scholar
- Reilly DS, Tomassini N, Bevins CL, Zasloff M. A Paneth cell analog in Xenopus small-intestine expresses antimicrobial peptide genes: conservation of an intestinal host-defense system. J Histochem Cytochem. 1994;42(6):697–704.Google Scholar
- Chandler JA, Lang JM, Bhatnagar S, Eisen JA, Kopp A. Bacterial communities of diverse Drosophila species: Ecological context of a host-microbe model system. PLoS Genet. 2011;7(9), e1002272.View ArticlePubMedPubMed CentralGoogle Scholar
- Knapp BA, Seeber J, Podmirseg SM, Rief A, Meyer E, Insam H. Molecular fingerprinting analysis of the gut microbiota of Cylindroiulus fulviceps (Diplopoda). Pedobiologia. 2009;52(5):325–36.View ArticleGoogle Scholar
- Rawls JF, Mahowald MA, Ley RE, Gordon JI. Reciprocal gut microbiota transplants from zebrafish and mice to germ-free recipients reveal host habitat selection. Cell. 2006;127(2):423–33.View ArticlePubMedGoogle Scholar
- Chao A. Non-parametric estimation of the number of classes in a population. Scand J Stat. 1984;11:265–70.Google Scholar
- Tamura K, Peterson D, Peterson N, Stecher G, Nei M, Kumar S. MEGA5: molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods. Mol Biol Evol. 2011;28(10):2731–9.View ArticlePubMedPubMed CentralGoogle Scholar
- Knapp BA, Seeber J, Rief A, Meyer E, Insam H. Bacterial community composition of the gut microbiota of Cylindroiulus fulviceps (diplopoda) as revealed by molecular fingerprinting and cloning. Folia Microbiol. 2010;55(5):489–96.View ArticleGoogle Scholar
- Rawls JF, Samuel BS, Gordon JI. Gnotobiotic zebrafish reveal evolutionarily conserved responses to the gut microbiota. Proc Natl Acad Sci U S A. 2004;101(13):4596–601.View ArticlePubMedPubMed CentralGoogle Scholar
- Ley RE, Turnbaugh PJ, Klein S, Gordon JI. Microbial ecology - human gut microbes associated with obesity. Nature. 2006;444(7122):1022–3.View ArticlePubMedGoogle Scholar
- Rajilic-Stojanovic M, de Vos WM. The first 1000 cultured species of the human gastrointestinal microbiota. FEMS Microbiol Rev. 2014;38(5):996–1047.View ArticlePubMedPubMed CentralGoogle Scholar
- Fields BS, Benson RF, Besser RE. Legionella and Legionnaires’ disease: 25 years of investigation. Clin Microbiol Rev. 2002;15(3):506–26.View ArticlePubMedPubMed CentralGoogle Scholar
- Lerner P, Kassen J. Legionnaires disease and Acinetobacter bacteremia. Ann Intern Med. 1979;90(3):434–5.View ArticlePubMedGoogle Scholar
- Forster DH, Daschner FD. Acinetobacter species as nosocomial pathogens. Eur J Clin Microbiol Infect Dis. 1998;17(2):73–7.View ArticlePubMedGoogle Scholar
- Guerrero DM, Perez F, Conger NG, Solomkin JS, Adams MD, Rather PN, Bonomo RA. Acinetobacter baumannii-Associated skin and soft tissue infections: recognizing a broadening spectrum of disease. Surg Infect (Larchmt). 2010;11(1):49–57.View ArticleGoogle Scholar
- Kamei A, Koh AY, Gadjeva M, Priebe GP, Lory S, Pier GB. Analysis of acquisition of Pseudomonas aeruginosa gastrointestinal mucosal colonization and horizontal transmission in a murine model. J Infect Dis. 2010;201(1):71–80.View ArticlePubMedPubMed CentralGoogle Scholar
- Espejo AG. Gastrointestinal bacterial-infections, Pseudomonas and Cefotaxime. Rev Clin Esp. 1987;180(3):180.Google Scholar
- Raczynski AR, Muthupalani S, Schlieper K, Fox JG, Tannenbaum SR, Schauer DB. Enteric infection with Citrobacter rodentium induces coagulative liver necrosis and hepatic inflammation prior to peak infection and colonic disease. PLoS One. 2012;7(3), e33099.View ArticlePubMedPubMed CentralGoogle Scholar
- Doran TI. The role of Citrobacter in clinical disease of children: Review. Clin Infect Dis. 1999;28(2):384–94.View ArticlePubMedGoogle Scholar
- Mcdermott C, Mylotte JM. Morganella morganii: epidemiology of bacteremic disease. Infect Control Hosp Epidemiol. 1984;5(3):131–7.Google Scholar
- Samonis G, Anatoliotaki M, Apostolakou H, Souglakos J, Georgoulias V. Fatal septicemia and meningitis due to Morganella morganii in a patient with Hodgkin’s disease. Scand J Infect Dis. 2001;33(7):553–5.View ArticlePubMedGoogle Scholar
- Willis SG, Smith KS, Dunn VL, Gapter LA, Riviere KH, Riviere GR. Identification of seven Treponema species in health- and disease-associated dental plaque by nested PCR. J Clin Microbiol. 1999;37(3):867–9.PubMedPubMed CentralGoogle Scholar
- Edwards AM, Dymock D, Woodward MJ, Jenkinson HF. Genetic relatedness and phenotypic characteristics of Treponema associated with human periodontal tissues and ruminant foot disease. Microbiol Sgm. 2003;149:1083–93.View ArticleGoogle Scholar
- Tsai SF, Chen CH, Shu KH, Wu MJ. Peritonitis caused by Roseomonas in a patient undergoing automated peritoneal dialysis: case report and literature review. Intern Med. 2012;51(13):1721–4.View ArticlePubMedGoogle Scholar
- De I, Rolston KVI, Han XY. Clinical significance of Roseomonas species isolated from catheter and blood samples: Analysis of 36 cases in patients with cancer. Clin Infect Dis. 2004;38(11):1579–84.View ArticlePubMedGoogle Scholar
- Lewis L, Stock F, Williams D, Weir S, Gill VJ. Infections with Roseomonas gilardii and review of characteristics used for biochemical identification and molecular typing. Am J Clin Pathol. 1997;108(2):210–6.PubMedGoogle Scholar
- Malamood M, Hui CMC, Nannegari V, Palmieri T, Green J. Is a history of gastrointestinal surgery a risk factor for an increased incidence of Clostridium difficile infection in patients with inflammatory bowel disease? Gastroenterology. 2013;144(5):S653.View ArticleGoogle Scholar
- Urban E, Tusnadi A, Terhes G, Nagy E. Prevalence of gastrointestinal disease caused by Clostridium difficile in a university hospital in Hungary. J Hosp Infect. 2002;51(3):175–8.View ArticlePubMedGoogle Scholar
- Cooper JE, Needham JR, Griffin J. A bacterial disease of the Darwin’s frog (Rhinoderma darwini). Lab Anim. 1978;12(2):91–3.View ArticlePubMedGoogle Scholar
- Brodkin MA, Simon MP, Desantis AM, Boyer KJ. Response of Rana pipiens to graded doses of the bacterium Pseudomonas aeruginosa. J Herpetol. 1992;26(4):490–5.View ArticleGoogle Scholar
- Gibbs EL. Rana pipiens - health and disease, how little we know. Am Zool. 1973;13(1):93–6.View ArticleGoogle Scholar
- Wang L, Wei Y, Huang YQ. Morganella morganii as a causative agent of disease in the Chinese giant salamander (Andrias davidianus). Asian Herpetol Res. 2013;4(3):197–201.Google Scholar
- Wiggins PJ, Smith JM, Harris RN, Minbiole KPC. Gut of Red-backed Salamanders (Plethodon cinereus) may serve as a reservoir for an antifungal cutaneous bacterium. J Herpetol. 2011;45(3):329–32.View ArticleGoogle Scholar
- Ramsey JP, Mercurio A, Holland JA, Harris RN, Minbiole KPC. The cutaneous bacterium Janthinobacterium lividum inhibits the growth of Trichophyton rubrum in vitro. Int J Dermatol. 2015;54(2):156–9.View ArticlePubMedGoogle Scholar
- Lauer A, Simon MA, Banning JL, Andre E, Duncan K, Harris RN. Common cutaneous bacteria from the eastern red-backed salamander can inhibit pathogenic fungi. Copeia. 2007;3:630–40.View ArticleGoogle Scholar
- Lauer A, Simon MA, Banning JL, Lam BA, Harris RN. Diversity of cutaneous bacteria with antifungal activity isolated from female four-toed salamanders. ISME J. 2008;2(2):145–57.View ArticlePubMedGoogle Scholar
- Lam BA, Walke JB, Vredenburg VT, Harris RN. Proportion of individuals with anti-Batrachochytrium dendrobatidis skin bacteria is associated with population persistence in the frog Rana muscosa. Biol Conserv. 2010;143(2):529–31.View ArticleGoogle Scholar
- Banas JA, Loesche WJ, Nace GW. Classification and distribution of large intestinal bacteria in nonhibernating and hibernating leopard frogs (Rana pipiens). Appl Environ Microbiol. 1988;54(9):2305–10.PubMedPubMed CentralGoogle Scholar
- Meyer EA, Cramp RL, Bernal MH, Franklin CE. Changes in cutaneous microbial abundance with sloughing: possible implications for infection and disease in amphibians. Dis Aquat Org. 2012;101(3):235–42.View ArticlePubMedGoogle Scholar
- Bresciano JC, Salvador CA, Paz-Y-Miño C, Parody-Merino AM, Bosch J, Woodhams DC. Variation in the presence of anti-Batrachochytrium dendrobatidis bacteria of amphibians across life stages and elevations in Ecuador. Ecohealth. 2015;1–10.Google Scholar
- Knight DJW, Girling KJ. Gut flora in health and disease. Lancet. 2003;361(9371):1831.View ArticlePubMedGoogle Scholar
- Belden LK, Harris RN. Infectious diseases in wildlife: the community ecology context. Front Ecol Environ. 2007;5(10):533–9.View ArticleGoogle Scholar
- Williams ES, Yuill T, Artois M, Fischer J, Haigh SA. Emerging infectious diseases in wildlife. Rev Sci Tech. 2002;21(1):139–57.PubMedGoogle Scholar
- Daszak P, Cunningham AA, Hyatt AD. Anthropogenic environmental change and the emergence of infectious diseases in wildlife. Acta Trop. 2001;78(2):103–16.View ArticlePubMedGoogle Scholar
- Chen WS. 31 frogs in Taiwan. Taipei: Wild Bird Society; 2003.Google Scholar
- Dunham AE. Realized niche overlap, resource abundance, and intensity of interspecific competition. In: Huey RB, Pianka ER, Schoener TW, editors. Lizard ecology: studies of a model organism. Massachusetts, USA: Harvard University Press; 1983: 261–280.Google Scholar
- Pinkas L, Oliphant MS, Iverson ILK. Food habits of albacore, bluefin tuna, and bonito in California waters. California: State of California, Dept. of Fish and Game; 1971.Google Scholar
- Sharma R, John SJ, Damgaard DM, McAllister TA. Extraction of PCR-quality plant and microbial DNA from total rumen contents. Biotechniques. 2003;34(1):92–7.PubMedGoogle Scholar
- Chao A, Lee SM. Estimating the number of classes via sample coverage. J Am Stat Assoc. 1992;87(417):210–7.View ArticleGoogle Scholar
- Chao A, Bunge J. Estimating the number of species in a Stochastic abundance model. Biometrics. 2002;58(3):531–9.View ArticlePubMedGoogle Scholar
- Tamura K, Nei M, Kumar S. Prospects for inferring very large phylogenies by using the neighbor-joining method. Proc Natl Acad Sci U S A. 2004;101(30):11030–5.View ArticlePubMedPubMed CentralGoogle Scholar
- Chazdon RL, Chao A, Colwell RK, Lin SY, Norden N, Letcher SG, et al. A novel statistical method for classifying habitat generalists and specialists. Ecology. 2011;92(6):1332–43.Google Scholar