The ability to form cooperative societies may explain why humans and social insects have come to dominate the earth. Here we examine the ecological consequences of cooperation by quantifying the fitness of cooperative (large groups) and non-cooperative (small groups) phenotypes in burying beetles (Nicrophorus nepalensis) along an elevational and temperature gradient. We experimentally created large and small groups along the gradient and manipulated interspecific competition with flies by heating carcasses. We show that cooperative groups performed as thermal generalists with similarly high breeding success at all temperatures and elevations, whereas non-cooperative groups performed as thermal specialists with higher breeding success only at intermediate temperatures and elevations. Studying the ecological consequences of cooperation may not only help us to understand why so many species of social insects have conquered the earth, but also to determine how climate change will affect the success of these and other social species, including our own.https://doi.org/10.7554/eLife.02440.001
The ability to live and work together in groups likely helped the earliest humans to leave their savannah homes in Africa and successfully settle around the globe. In doing so, humans shifted from being savannah specialists to generalists able to cope with a range of different environments. Cooperation is also believed to be a key to the global success of social insects like bees and ants. However, testing the idea that cooperation allows animals to become generalists that thrive in diverse environments—an idea referred to as the ‘social conquest hypothesis’—is difficult.
Climate change has added a new sense of urgency to understanding how species adapt to changing environments, and some studies of humans and other animals have suggested that cooperation may increase or decrease in changing environments. Living in social groups has both benefits and drawbacks: it helps some animals to avoid being eaten by predators, but it also creates more competition for mates, food or other resources. As such, predicting how climate change will impact human and animal societies has also been difficult to test.
Sun et al. have now tested the social conquest hypothesis by looking at how changes in environmental conditions affect the social behavior of the burying beetle. These insects find dead animals and then bury them to be eaten by their larvae. Burying beetles often fight each other to ensure that their own young get exclusive access to a food source. However, working together allows the beetles to bury a carcass before flies and other competitors discover it. Sun et al. compared how much the beetles cooperated at different elevations in the mountains of Taiwan. At each elevation the beetles faced different challenges: higher elevations were colder but had fewer flies, while lower elevations were warmer but had more flies.
Although burying beetles tended to work together more at warmer elevations, where the competition from flies was the most intense, beetles that cooperated with each other were able to successfully breed at all elevations. On the other hand, beetles that were less cooperative were best adapted to raising their young at more moderate elevations, where the climate and competition were less harsh. Similar results were seen when Sun et al. created non-cooperative and cooperative groups of beetles at different elevations and provided each group with a rat carcass. Further experiments that used heaters to artificially warm the carcasses directly proved that cooperation among beetles was indeed encouraged by higher temperatures.
Many studies have suggested that global warming might cause higher levels of conflict in human societies. But by studying how changes in an environment impact cooperation in burying beetles, Sun et al. provide new insights into how climate change may affect the future success of other social animals, including humans.https://doi.org/10.7554/eLife.02440.002
Social animals, including humans and many insects, have come to dominate the earth, possibly because of their ability to form complex societies (Laland et al., 2001; Fuentes et al., 2010; Boyd et al., 2011; Wilson, 2012; Lucky et al., 2013). While studies of animal social evolution often emphasize the environment drivers of group-living (Emlen, 1982; Rubenstein and Lovette, 2007; Jetz and Rubenstein, 2011; Gonzalez et al., 2013), the ecological consequences of sociality have received less attention. A rare exception comes from our own species, where cooperation is thought to have played a critical role in allowing modern humans to expand rapidly across the earth to exploit a more diverse range of environments than the African savannas in which our ancestors evolved (Laland et al., 2001). This shift from being a habitat specialist to generalist, and the subsequent ecological dominance by social species, has been termed the social conquest hypothesis (Wilson, 2012). Although this idea has drawn attention from a variety of disciplines, it has proven difficult to test empirically (Richerson and Boyd, 2008; Fuentes et al., 2010).
Animals derive a variety of cooperative benefits from living in groups (Alexander, 1974; Shen et al., 2014). Identifying the specific type of benefit individuals receive may help determine the ecological consequences of sociality. If the primary benefit of grouping is to cope with environmental challenges (e.g., predation risk, fluctuating climates, or interspecific competition) (Alexander, 1974; Korb and Foster, 2010; Jetz and Rubenstein, 2011; Celiker and Gore, 2012; Shen et al., 2012; Gonzalez et al., 2013), cooperation should translate into individuals adopting a generalist strategy that allows them to live in a broad range of conditions and cope with a variety of environmental challenges. In contrast, when species form groups as an adaptation to intraspecific challenges (e.g., competition with conspecific groups or with members of their own group over a lack of breeding vacancies or critical resources; Emlen, 1982; West et al., 2006; Reeve and Hölldobler, 2007; Gonzalez et al., 2013; Hsiang et al., 2013), cooperation should enable individuals to specialize in a single environment (Figure 1).
The contrast between habitat specialist and generalist strategies derives from ecological niche theory (Levins, 1968; Futuyma and Moreno, 1988). Although niche theory has been used to investigate a range of ecological phenomena including species interactions (Kassen, 2002), geographic distributions (Peterson et al., 2011) and the ecological consequences of climate change (Clavel et al., 2010), to our knowledge it has not yet been applied to social evolution. To understand how sociality influences niche breadth evolution, social and non-social populations from the same species need to be examined in a variety of different environments. That is, rather than focusing upon the ecological interactions of a species as a whole, one could separate a species’ total niche into different phenotypic components and then determine how these phenotypes influence fitness in varying environments (Roughgarden, 1972; Bolnick et al., 2010). For social species, total niche breadth can be partitioned into the ‘cooperative’ and ‘non-cooperative’ phenotypes, which correspond to generalist and specialist strategies, respectively if the grouping benefit is to cope with harsh environments or severe interspecific competition.
Here we examine how group-living impacts the generalist-specialist behavioral tradeoff and its subsequent effect on niche breadth (defined as a thermal performance that influences elevational distribution) in the facultative cooperatively breeding burying beetle (Nicrophorus nepalensis). The primary benefit of cooperative breeding behavior in burying beetles is to jointly prepare and bury carcasses more rapidly than their primary competitor, carrion-feeding flies (Table 1) (Eggert and Müller, 1992; Scott, 1994; Trumbo, 1995). We consider how intraspecific cooperation drives the evolution of thermal specialist vs generalist strategies along an elevational gradient where the degree of temperature-mediated interspecific competition with flies for resources (carcasses) varies with elevation. To determine how temperature influences the degree of interspecific competition, which in turn mediates the cooperative and competitive strategies of N. nepalensis, we first documented the natural patterns of group size, cooperation, breeding success, and the degree of interspecific competition with flies along the elevational gradient. We then experimentally manipulated the group size of N. nepalensis and the degree of interspecific competition with flies to determine the mechanisms underlying the fitness patterns along the elevational gradient.
We began by quantifying the natural patterns of group size, cooperative behavior, and breeding success along an elevational gradient in central Taiwan (Figure 2) where daily minimum air temperature decreased with increasing elevation (χ²1 = 222.50, p<0.001, n = 116). We found that group size decreased with increasing elevation (Figure 3A) and decreasing air temperature (Figure 3B). Furthermore, the probability of breeding successfully varied unimodally along the elevational (Figure 3C) and air temperature gradients (Figure 3D), peaking at intermediate elevations and air temperatures. Additionally, cooperative behavior—quantified as levels of cooperative carcass processing (‘Materials and methods’)—increased with increasing group size (Figure 4), suggesting that the greater breeding success at higher elevations was due to the cooperative behavior of groups.
To further determine how cooperation influences breeding success in different environments, we created small, non-cooperative groups (one male and one female, n = 53) and large, cooperative groups (three males and three females, n = 39) at 23 sites along the elevational gradient by placing locally trapped beetles on rat carcasses in specially designed breeding chambers that allowed flies and other small insects to move in-and-out of the chambers freely, but that limited the natural access of beetles (Figure 5). Initial group size simulated the number of beetles attracted to odorants produced by decomposing vertebrate carcasses, and the timing of beetle placement mimicked the natural pattern of arrival times, which are longer at higher elevations. We found that the probability of breeding successfully for small and large groups varied along the elevational gradient such that large groups performed as thermal generalists with similar breeding success at all elevations (Figure 6A) and air temperatures (Figure 6B), whereas small groups performed as thermal specialists with high breeding success only at intermediate elevations (Figure 6A) and air temperatures (Figure 6B). Moreover, large groups had higher breeding success than small groups at low elevations (Figure 6A) and at warmer temperatures (Figure 6B), but small groups had marginally higher breeding success than large groups at intermediate elevations (Figure 6A) and temperatures (Figure 6B). There were no significant differences in breeding success between large and small groups at high elevations (Figure 6A) and low air temperatures (Figure 6B).
To establish why breeding success varied with elevation and temperature differently in cooperative and non-cooperative groups, we quantified levels of cooperative carcass processing in our group size treatments across the elevational gradient. We found no relationship between cooperative carcass processing and elevation (Figure 7A) or air temperature (Figure 7B) in small groups. However, investment in cooperative carcass processing in large groups increased with decreasing elevation (Figure 7A) and increasing air temperature (Figure 7B), presumably because carcasses decompose more quickly at lower elevations (Figure 8A) where fly abundance (Figure 8B) and activity (Figure 8C) is highest. Experimental exclusion of flies from carcasses confirmed that flies indeed enhance carcass decomposition rates; the mean dry weight of carcasses from which flies were excluded was more than two times heavier than carcasses for which flies had access (Figure 9). Our data further showed that in large groups, per capita social conflict (‘Materials and methods’) varied unimodally with a peak at intermediate elevations and air temperatures (Figure 10). Importantly, only investment in cooperative carcass processing, and not social conflict, increased with increasing temperature in large groups. Together these results indicate that an individual’s cooperative and competitive strategies are not influenced directly by temperature-dependent physiological constraints per se because higher ambient temperatures typically reduce the cost of activity for ectotherms (Angilletta, 2009). Instead, our experiments suggest that an individual's cooperative and competitive strategies are influenced by temperature-mediated interspecific competition for resources, which increases with increasing temperature.
Experimental exclusion of flies from carcasses confirmed that interspecific competition between beetles and flies reduces beetle breeding success; the probability of beetles breeding successfully in small groups along the elevational gradient (from 1664 m to 2809 m) was lower when flies had access to carcasses than when they were excluded (Figure 11; for additional details see fly competition treatment in ‘Materials and methods’). To determine if temperature mediates this competition, we simultaneously manipulated group size and the degree of competition with flies along the portion of the elevational range where small groups had higher breeding success. We found that experimentally heating carcasses (‘Materials and methods’) increased fly abundance (Figure 8B) and activity (Figure 8C) relative to controls. If temperature-mediated competition with flies at low elevations explains why large groups had higher breeding success than small groups, then our heated carcass treatment at higher elevations should have decreased the probability of breeding successfully in small but not large groups. In support of this prediction, we found that heating carcasses differentially affected the breeding success of small and large groups when controlling for elevation such that the probability of breeding successfully in small groups decreased in the heated carcass treatments (Figure 12A), but the probability of breeding successfully for large groups remained the same (Figure 12A). Moreover, individuals were more cooperative in carcass processing in the heated carcass treatments than in the controls (Figure 12B).
In summary, our experiments demonstrated that cooperative beetle groups performed as thermal generalists, but non-cooperative groups performed as thermal specialists. This generalist-specialist behavioral tradeoff along the elevational gradient in N. nepalensis is generated by the tension between an individual's share of the grouping benefit and the group's productivity. At low elevations where the pressure of interspecific competition with flies is highest, individuals in large groups were not only more cooperative at handling carcasses, but they also engaged in lower levels of social conflict, both of which enabled them to outcompete flies. As a consequence, cooperation enables burying beetles to expand their thermal niche to a warmer region where competitors are more abundant. In contrast, we found that the ‘tragedy of the commons’ (Hardin, 1968; Rankin et al., 2007)—that is the degree of social conflict was higher in large groups, which led to a reduction in breeding success relative to small groups—occurred at intermediate elevations where the pressure of interspecific competition with flies was lower. At these intermediate elevations, non-cooperative groups have marginally higher breeding success than cooperative groups because intraspecific social conflict increased in the absence of interspecific conflict. Nonetheless, this within-group conflict has relatively little influence on the ecological dominance of burying beetles because breeding success is still relatively high in large groups in favorable environments, compared with those at elevations where environments are less favorable. We found a similar pattern in the natural populations (i.e., those without group size manipulations) where breeding success was highest at intermediate elevations even though there are many naturally occurring large groups in this region.
This study provides the first experimental evidence consistent with the social conquest hypothesis, which argues that cooperation promotes the evolution of generalist strategies when the primary benefit of living in groups is to cope with environmental challenges, including climate-mediated interspecific competition (Wilson, 2012). Preliminary support for this hypothesis comes from a recent comparative study of sponge-dwelling snapping shrimp (Synalpheus spp.), showing that eusocial species were more abundant and occupied a broader range of host sponge species than non-social sister species (Duffy and Macdonald, 2010). We have shown experimentally in burying beetles that cooperative groups performed as thermal generalists, but non-cooperative groups performed as thermal specialists. Being cooperative enables burying beetles to extend their range to lower elevations where temperatures are warmer and where competitors are more abundant because individuals in large groups were more cooperative at handling carcasses, which enabled them to outcompete flies. Thus, cooperation allows burying beetles to expand their thermal niche into an environment from which they would otherwise be competitively excluded. Ultimately, studying the ecological consequences of cooperation may not only help us to understand why so many species of social insects have conquered the earth, but also to determine how climate change will affect the success of these and other social species, including our own.
The elevational gradient in central Taiwan (Figure 2) covers broadleaf forest at lower elevations and mixed conifer-broadleaf forest at higher elevations. We chose study sites primarily in mature forests and avoided cultivated or open areas.
We conducted a preliminary investigation of the natural pattern of arrival times of free-ranging beetles on carcasses along the elevational gradient from August to September 2012 and from June to September 2013. In each trial, a 75 g rat carcass was presented on the soil and covered with a 21 × 21 × 21 cm iron cage with mesh size of 2 × 2 cm to prevent vertebrate scavengers. We video recorded the entire burial process. Because video recordings showed that the number of beetles on the carcass varied with time, we determined the mean group size (an average group size of the maximum number of beetles sampled every hour) before the burial was complete. Beetle arrival time was determined when the first burying beetle was observed on the carcass. The arrival time of free-ranging burying beetles on carcasses increased with increasing elevation (χ²1 = 24.41, p<0.001, n = 73).
To confirm that flies (Diptera) are the major competitors of burying beetles, we first examined the succession pattern of carrion-feeding insects on 150 g (n = 5) and 200 g (n = 7) rat carcasses. This experiment was conducted at an intermediate elevation (2000 m) from June to August 2011. Initially, rat carcasses were placed at 50 m intervals along the ground and covered by 21 × 21 × 21 cm iron cages following the previous procedure. Samples were collected daily in the morning (between 10:00 and 12:00) for three days to resemble the insect community at an early successional stage. Mean abundances of carrion-feeding insects on 12 carcasses were examined daily after exposure, continuing for 1 day (n = 5), 2 days (n = 3), and 3 days (n = 4). For each sampling period, we first used an aerial sweep net to collect flying insects before the carcass was moved. We then collected all insects present on the carcass. Finally, the soil beneath each carcass was sampled within a sieve tray (2500 cc), and insects were extracted by a modified Berlese funnel (Newell, 1955). All specimens were preserved in 70% ethanol for further identification in the laboratory. Taxonomic determination was made to the family level (Borror et al., 1989).
In total, 518 adult carrion-feeding insects were collected, representing 29 families in four orders (Table 1), including necrophagous, saprophagous, and omnivorous species (Smith, 1986). Of these, Diptera and Coleoptera were the two most represented groups, constituting 98.1% of the individuals captured. A GLM was performed to assess if the abundance (number of individuals per carcass) differed between insect families (Diptera and Coleoptera) using carcass weight and the day after carcass exposure as covariates. We found that the mean abundance of Diptera was significantly higher than that of Coleoptera (χ²1 = 49.85, p<0.001, n = 12).
Burying beetles were collected by hanging pitfall traps baited with 100 ± 10 g of rotting chicken. Pitfall traps were checked each morning. Beetles were housed individually in 320 ml transparent plastic cups and fed with mealworms (Zophobas morio) if they were kept more than three days before the experiment. Each beetle was weighed to the nearest 0.1 mg and marked with Testors enamel paint on the elytra (Butler et al., 2012) for individual identification the night before use. Sex was determined by the markings on the clypeus; males have a rectangular, orange marking, whereas females do not.
Our experimental chambers consisted of a smaller plastic container (21 × 13 × 13 cm with 10 cm of soil) located inside a larger container (41 × 31 × 21.5 cm with 11 cm of soil) (Figure 5). Multiple holes on the side walls of the smaller container permitted beetle movement between the two containers. The cap of the larger container was fitted with a digital camera and was raised up 2 cm by iron mesh to allow entry by free-ranging flies and beetles, but not by vertebrate scavengers (Figure 5). Digital cameras were powered by Yuasa lead-acid batteries (6V 12Ah), which were replaced every morning. We measured air temperature every 30 min for the duration of the experiment using Maxim's iButton devices that were placed within the larger container. Based upon the natural pattern of arrival times from our pilot study (see ’Group size in natural populations’ in ‘Materials and methods’), we released the marked beetles into the experimental apparatus 1 day, 2 days, and 3 days after the trials began at elevations of 1700–2000 m (low), 2000–2400 m (intermediate) and 2400–2800 m (high), respectively.
To quantify breeding success, we exhumed the carcasses approximately 14 days after they were buried and collected third instar larvae, if there were any. Across the 92 trials that were completed successfully, 52 trials resulted in successful breeding attempts and 40 trials contained carcasses that were completely consumed by maggots. The 40 failed trials were used to examine the carcass consumption rate by maggots as an indicator of interspecific competition along the elevational gradient (Figure 8A).
To assess the effect of fly competition on carcass decomposition rates, we evaluated the difference in carcass weight loss among net-covered treatments (i.e., fly access was restricted from the entire cage), natural fly access treatments, and fresh carcass controls at intermediate elevations (2100 m). The carcasses of natural fly access treatments were exposed to flies until maggots finished consuming and left the carcasses. The dried weights of all carcasses were obtained by dehydrating the carcasses to a constant weight in a drying oven at 65°C. We also compared the probability of breeding successfully in treatments where flies had access to the carcasses and those where flies were excluded along the elevational gradient (from 1664 m to 2809 m).
To explore temperature-mediated cooperation in response to fly competition in situ, a heating device was continuously applied underneath each carcass to provide a warming effect. To determine if heating carcasses made them more attractive to flies, we compared fly activity and abundance on heated carcasses to those of control treatments on the day we released the beetles in each trial. Fly activity was quantified as the total duration between the first fly arriving at the carcass and the last fly leaving the carcass, whereas fly abundance was quantified as the total number of flies video recorded between 6:00 to 18:00 at 30-min intervals. The heating device was constructed with a series circuit of cement resistors (40 Ω), which was powered by Yuasa lead-acid batteries (6V 12Ah). The soil temperature differences between the heated carcass treatment and its ambient environment were measured using thermal probes at a depth of 5 cm daily in the morning in 32 trials. On average, the heated carcass treatment created higher soil temperatures (28.7 ± 0.71°C) than those of ambient environment (17.4 ± 0.31°C) (χ²1 = 212.06, p<0.001, n = 64). Further, a total of 24 heated carcass treatments were conducted along the elevational gradient (from 2039 m to 2814 m) where small, non-cooperative groups had higher breeding success.
In total, 4488 hr of video were recorded from the 92 successful non-heated (control) trials (n = 39 large groups, 53 small groups) and 1170 hr from the heated carcass treatments (n = 9 large groups, 15 small groups). A variety of social behaviors, including per capita social conflict and investment in cooperative carcass processing, were scored on the first night (from 19:00 to 05:00) using the Observer Video-Pro software (Noldus) for the 34 successful breeding trials (n = 14 large groups, 20 small groups) and 11 trials of small groups failed at the lower elevations (from 1664 m to 1844 m). Aggressive interactions were defined as social conflict if a beetle grasped, bit, chased, or escaped from the other same-sexed individual. A sample video of aggressive interaction can be seen in Video 1. We measured per capita social conflict as the total number of aggressive interactions divided by mean group size for each observation period. To quantify total social investment in cooperative carcass processing, we estimated the cumulative time that each beetle spent depilating rat hair, removing maggots, or digging soil during carcass burial and preparation. A sample video of cooperative carcass processing can be seen in Video 2. Investment was quantified as the duration of cumulative time sampled for a 10 min observation period in each hour (100 min in total).
Multivariate analyses were performed using generalized linear models (GLMs). If the random effects of repeated sampling of study sites were required, generalized linear mixed models (GLMMs) were used. To test for the differences in the probability of breeding successfully between the two group sizes and carcass heating treatments along the elevational and temperature gradients, the outcome of breeding success (1 = Success, 0 = Failure) was fitted as a binomial response term. The environmental factors (elevation and daily minimum air temperature), group size treatments, and carcass heating treatments were fitted as covariates of interest. For the carcass heating treatments, the fitted value of the probability of breeding successfully was compared between heated carcass and control treatments. All statistic analyses were performed in the R statistical software package (R Core Team, 2012).
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Marcel DickeReviewing Editor; Wageningen University, The Netherlands
eLife posts the editorial decision letter and author response on a selection of the published articles (subject to the approval of the authors). An edited version of the letter sent to the authors after peer review is shown, indicating the substantive concerns or comments; minor concerns are not usually shown. Reviewers have the opportunity to discuss the decision before the letter is sent (see review process). Similarly, the author response typically shows only responses to the major concerns raised by the reviewers.
Thank you for sending your work entitled “Climate-mediated Cooperation Promotes Niche Expansion” for consideration at eLife. Your article has been favorably evaluated by a Senior editor and 2 reviewers, one of whom is a member of our Board of Reviewing Editors.
Your study addresses an interesting question, i.e., whether cooperative behaviour allows a species that experiences environmental challenges such as interspecific competition to occupy a wider range of niches than when cooperative behaviour is not exhibited. It includes both natural history elements documenting the actual situation along an elevation (and temperature) gradient followed by directed manipulative experiments. Overall the manuscript is well presented, but at some instances, clarity can be enhanced. The reviewers have also raised some concerns, especially relating to two figures that are central for the main conclusion of the study. In addition there is a concern about the statistical analysis to compare groups. This is explained below. The response to the concerns will be crucial in the decision on your manuscript.
Two figures that are central for the main conclusion: your study looks at group size and reproductive success in burying beetles as a function of a temperature/elevation gradient. Correlation data shows that burying beetle groups are larger at low elevation/high temperature, which may be due to factors like carcasses decomposing more quickly or that there are more beetles at low elevation. In addition you performed impressive field manipulations where you vary the group size (small and large) of semi natural beetle groups and follow how they perform across the gradient. This shows differences between the two groups sizes in success along the gradient.
You interpret this in light of the idea that social life allows organisms to invade new habitats where they would fail without sociality. Overall these are interesting data and an interesting idea but there are some concerns. The manipulation experiment data in Figures 5 and 6 are key to concluding that the large groups are more tolerant to environmental variation than small groups. However, looking at Figure 5, it looks like the large groups are doing worse in the intermediate values (and p=0.06 for the chi squared suggests that this is likely real). But you have drawn a straight line through things for large groups and one reviewer is worried that this is missing an important detail: small groups are best at intermediate temperatures and elevations. Moving to Figure 6, it is argued that there is no trend for the small groups but also, there are no small groups at all at low elevations/high temperature and if one removed the large groups at these points, one would lose the correlation for large groups I expect (was this done?). Without this, it is hard to know whether the correlation is a direct effect or the large groups or just down to the fact that small groups cannot make it for the key ranges where temperature effects would be seen.
To remove the concerns we would like to see more analyses that follow up on the above 1) Are small groups better under some conditions, 2) What does a mean success plot look like for Figure 5 (it looks like large groups plummet in the middle) and do the two mean plots differ in shape between small and large groups? 3) What happens if one compares data over the same temperature/elevation ranges in Figure 6?
Moreover, there is an additional ‘statistical concern’: there are several places in the text where a non-significant result is compared to a significant result and this is used to imply that one is biologically different to the other: e.g., temperature does not affect small groups (non significant) but it does effect large groups (significant). However, this is not the way to analyse this. Rather, these should be tested against each other to compare them. Finally, the practice of drawing a straight line through non-significant results that have high variance intuitively seems off: please reconsider.
It seems that small groups are good for some ranges and large ones for others and the beetles appear to be responding to this. If correct, then this suggests that the ability to be socially plastic allows them to tolerate more of a range in climate. This is a bit different to what you are suggesting: the large groups are no longer generalist but the species range is likely increased by being able to make large or small groups when needed. So, dependent on the additional analyses, the narrative of the paper would need to be reworked in response to this.https://doi.org/10.7554/eLife.02440.018
[…] Looking at Figure 5, it looks like the large groups are doing worse in the intermediate values (and p=0.06 for the chi squared suggests that this is likely real). But you have drawn a straight line through things for large groups and one reviewer is worried that this is missing an important detail: small groups are best at intermediate temperatures and elevations.
This is a very important point, and one that we apparently failed to make clear in the original manuscript. As you suggest, we now also interpret the result more clearly as small groups have marginally higher reproductive success than large groups at intermediate temperatures and elevations. These changes make the results fit even better in our generalist-specialist trade-off framework (see Figure 1). That is, small groups perform as thermal specialists and do best at intermediate temperatures and elevations, whereas as large groups are generalists with wider thermal niches, but lower reproductive success. The detailed discussion of this result is now added in the text and the figure legend of new Figure 6.
Moving to Figure 6, it is argued that there is no trend for the small groups but also, there are no small groups at all at low elevations/high temperature and if one removed the large groups at these points, one would lose the correlation for large groups I expect (was this done?). Without this, it is hard to know whether the correlation is a direct effect or the large groups or just down to the fact that small groups cannot make it for the key ranges where temperature effects would be seen.
Thank you for pointing this out. We actually did perform our experiments for both large and small groups at all elevations, but since all small group breeding attempts failed at low elevations, we did not show these data in the original figure. In other words, Figure 6 originally only showed total investment of successful breeding events to avoid the potential complications of including failed breeding events. We now realize this may have been misleading, so we have added the investment data of failed breeding events to the figure and analyses. Importantly, adding these points has no effect on the analyses, and the original pattern of investment for small groups remains the same (in new Figure 7).
To remove the concerns we would like to see more analyses that follow up on the above 1) Are small groups better under some conditions, 2) What does a mean success plot look like for Figure 5 (it looks like large groups plummet in the middle) and do the two mean plots differ in shape between small and large groups?
As suggested, we have added these new analyses. Small groups perform better at intermediate elevations (see response above for additional details) and we have now used regression to represent the non-significant relationship (the original straight line is the mean probability of breeding successfully).
What happens if one compares data over the same temperature/elevation ranges in Figure 6?
As we describe above, we have now added investment data of failed breeding event for small groups so that data for large and small groups cover the same temperature and elevational ranges in the new Figure 7.
Moreover, there is an additional ‘statistical concern’: there are several places in the text where a non-significant result is compared to a significant result and this is used to imply that one is biologically different to the other: e.g., temperature does not affect small groups (non significant) but it does effect large groups (significant). However, this is not the way to analyze this. Rather, these should be tested against each other to compare them.
Thank you for pointing out the need to perform multivariate analyses in these instances. We agree that this is a more appropriate way to analyze our data. We have added the analyses for every comparison, as suggested. Importantly, all of the results and conclusions remain the same.https://doi.org/10.7554/eLife.02440.019
- Sheng-Feng Shen
- Sheng-Feng Shen
- Dustin R Rubenstein
- Dustin R Rubenstein
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
We acknowledge Yen-Cheng Lin, Tzu-Neng Yuan, Ching-Fu Lin, and Yu-Ching Liu for their great support in the field. We also thank Wei-Ping Chan for help making Figure 2 and the staff at Mei-Feng Highland Experiment Farm, National Taiwan University for the logistic help.
Animal experimentation: All of the animals were handled according to approved Biosafety Committee protocols of the Academia Sinica. The protocol was approved by the Biosafety Committee of Academia Sinica (Permit Number:BSF0412-00002446).
- Marcel Dicke, Wageningen University, The Netherlands
© 2014, Sun et al.
This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.
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Plant species diversity affects carbon and nutrient cycling during litter decomposition, yet the generality of the direction of this effect and its magnitude remains uncertain. With a meta-analysis including 65 field studies across the Earth’s major forest ecosystems, we show here that decomposition was faster when litter was composed of more than one species. These positive biodiversity effects were mostly driven by temperate forests but were more variable in other forests. Litter mixture effects emerged most strongly in early decomposition stages and were related to divergence in litter quality. Litter diversity also accelerated nitrogen, but not phosphorus release, potentially indicating a decoupling of nitrogen and phosphorus cycling and perhaps a shift in ecosystem nutrient limitation with changing biodiversity. Our findings demonstrate the importance of litter diversity effects for carbon and nutrient dynamics during decomposition, and show how these effects vary with litter traits, decomposer complexity and forest characteristics.
To predict how species loss will affect ecosystems, it is important to consider how biodiversity influences processes such as decomposition.