Meta-analysis on the responses of traits of different taxonomic groups to global and local stressors

Acta Oecologica 69 (2015) 65e70

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Meta-analysis on the responses of traits of different taxonomic groups to global and local stressors € cs, Ralf B. Scha €fer John G. Mbaka*, Eduard Szo Institute for Environmental Sciences, University Koblenz-Landau, Landau, Germany

a r t i c l e i n f o

a b s t r a c t

Article history: Received 22 May 2015 Received in revised form 7 September 2015 Accepted 8 September 2015 Available online xxx

Climate change and pollution are considered as major drivers of biodiversity loss. Climate change is a global multi-stressor, whereas pollution predominantly acts on the local scale. Organisms traits provide mechanistic links between biotic responses and stressors. We reviewed and analyzed the literature on the responses of vertebrates, invertebrates, microorganisms and plants traits to climate change (437 studies) and pollution (121 studies), to assess whether there was uniformity (i.e. convergence) in the responses of traits to the multi-stressors. For climate change, the traits related to tolerance responded uniformly across taxonomic groups, indicating trait convergence. For pollution, the low number of studies hampered a comparison across taxonomic groups. However, aquatic invertebrates that are tolerant, or exhibit high dispersal or reproduction capacities increased in response to pollution, whereas body mass and size increased in phytoplankton and fish, respectively. We provide a set of traits that have the potential to predict ecosystem-wide effects of climate change and pollution. © 2015 Elsevier Masson SAS. All rights reserved.

Keywords: Biomonitoring Species traits Climate change Pollution Contamination Community ecology Stressors

Contents 1. 2. 3.

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5.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 Methods: literature survey and data analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 3.1. Literature survey and response of taxonomic groups . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 3.2. Convergence of trait responses across taxonomic groups . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 4.1. Use of traits in studies on climate change and pollution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 4.2. Convergence and strength of trait responses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 Author contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 Performed data analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 Disclosure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 Supplementary data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69

1. Introduction * Corresponding author. E-mail addresses: [email protected] (J.G. Mbaka), szoecs@uni-landau. € cs), [email protected] (R.B. Sch€ de (E. Szo afer). http://dx.doi.org/10.1016/j.actao.2015.09.002 1146-609X/© 2015 Elsevier Masson SAS. All rights reserved.

The Millennium Ecosystem Assessment (MEA) considers

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climate change and pollution as major stressors in ecosystems (MEA, 2005), which may lead to a global ecosystem state shift and threaten ecosystem services that are crucial for human well-being (Perrings et al., 2010; Barnosky et al., 2012). Climate change and pollution act on different spatial scales; climate change is related to large spatial scales and pollution is often a local or a regional phenomenon, though diffuse inputs may result in an ubiquitous presence of some chemicals (MacLeod et al., 2014). The alteration of ecosystems structure and functioning by these multi-stressors has promoted the search for diagnostic and predictive tools that can also be applied over large spatial scales (Lamouroux et al., 2002; Sch€ afer et al., 2007; Newbold et al., 2012; Díaz et al., 2013). Here, climate change and pollution are termed as ῾multi-stressors᾿ due to their association with multiple individual stressors such as changes in precipitation and temperature in the case of climate change. Traits have been advocated as a tool that may overcome the limitations of taxonomy-based approaches when diagnosing and predicting the effects of climate change and pollution (McGill et al., 2006; Statzner et al., 2007; Green et al., 2008). Traits have a long tradition in ecology, particularly in plant ecology (Cornelissen et al., 2003), where they have shown potential to predict community composition (Shipley et al., 2006). They have also been applied to detect the effects of stressors, for example in aquatic ecosystems (e.g., Statzner et al., 2001; Mouillot et al., 2006; Mellado-Díaz et al., 2008). Trait databases on different spatial scales have been compiled for different taxonomic groups and are a crucial prerequisite to advance the establishment of trait-stressor relationships (Table S1). In comparison with taxonomy-based approaches, traits have several advantages: traits permit data aggregation at variable spatial-scales, thus allowing detection of the effects of stressors across biogeographic dec et al., 1999; Moretti et al., 2009), regions (Díaz et al., 1998; Dole which is particularly relevant for climate change due to its manifestation over large areas. On large spatial scales, taxonomybased approaches often lack power to find the effects of stressors on biota because of strong variations in the species pools. Moreover, traits can establish explicit, and in many cases mechanistic, relationships between biotic responses and environmental gradients and stressors, which improve the interpretation and allow testing ecological hypotheses (Shipley, 2010). In this context, traits add value to taxonomic data by revealing functional structures and often portray seasonal and inter-annual stability compared to ^che and Resh, 2007). Finally, traits can taxonomic measures (Be provide a sensitive tool for predicting biological responses to stress across different taxonomic groups (Aubin et al., 2013). For example, the decrease in organisms body size has been suggested as an universal response to climate change in various taxonomic groups (e.g., birds, Van Buskirk et al., 2010; fish, Daufresne et al., 2009; Baudron et al., 2014; salamanders, Caruso et al., 2014). Identification of similar trait responses within and across taxonomic groups indicates trait convergence; in other words the development of similar adaptations in response to specific environmental and habitat conditions (Grime, 2006). The idea of trait convergence is also inherent to the ῾habitat templet concept᾿ hypothesizing that spatio-temporal habitat variations provide a ῾templet᾿, which selects for life history and other species traits (Southwood, 1977). Similarly, Keddy (1992) developed a conceptual framework where environmental factors and stressors act like a ῾filter᾿, removing species lacking the required combinations of traits, such that organisms with certain traits dominate in a particular environment. Previous reviews on traits were limited to specific taxonomic groups (e.g., lichens, Cornelissen et al., 2007; stream invertebrates, Menezes et al., 2010; birds, Luck et al., 2012), whereas a comparison of the responses of different taxonomic groups to specific multi-

stressors is lacking. We reviewed the literature and conducted a meta-analysis on the responses of organisms traits to two multistressors acting on different spatial scales (i.e. climate change and pollution). We aimed to (i) quantify the response (and nonresponse) of traits of different taxonomic groups to climate change and pollution, and (ii) assess whether there is trait convergence in responses to multi-stressors across taxonomic groups. 2. Methods: literature survey and data analysis We extracted peer reviewed studies on the effects of climate change and pollution on organisms traits by searching the Web of Science database (years 1972e2014). We used search terms such as ʻ(algae OR plankton* OR diatom* OR phytoplankton OR periphyton OR macrophyte*) OR (fish*) OR (zoobentho* OR invertebrate* OR zooplankton*) OR (forb* OR grass OR sedge* OR tree* OR shrub* OR lichen* OR bryophyte* OR plant*) OR (myriapod* OR crustacean* OR chelicerate* OR arachnid* OR insect* OR arthropod*) OR (avian* OR bird*) OR (microb* OR bacteria OR virus* OR fungi OR protist* OR protozoa* OR microorganism*) AND (functional group* OR functional type* OR functional categor* OR trait*) AND (climat* OR warming OR drought* OR temperature OR pollution OR contamination OR toxic*)ʼ to find the respective papers. The papers were screened for information on the response of traits related to populations (e.g. average body size of population) or communities (e.g. abundance-weighted average body size of the community) to climate change and pollution. A total of 558 studies were included in our analysis and a brief description of the trait responses to climate change and pollution in the individual studies is provided in Table S2. Though not exhaustive, we consider that our study selection was unbiased. However, we focused on organism traits and, thus, studies on microorganisms may have been undersampled as they partly rely on functional genes. The studies were classified into field monitoring and experiments, which relied on field sampling and experiments, respectively, as well as into laboratory studies. We classified the trait information as specific traits that were often used, such as body size, mass, reproduction, functional diversity and tolerance, and into two general categories (other biological and other ecological traits) that were rarely reported. Furthermore, traits were categorized as responding and non-responding significantly to the multi-stressors under scrutiny, where the direction was coded as positive (‘þ’) or negative (‘’) for responding traits and as neutral (‘0’) for non-responding traits. Thus, positive and negative responses indicate a statistically significant increase and decrease in a trait (e.g. body mass), respectively, whereas a neutral response indicates no significant change. Pollutants were categorized as organic, inorganic or nutrients. To evaluate the potential convergence of the trait responses, we aggregated the direction of the trait response across studies within the same taxonomic groups as follows:

P 0 0  P 0 0  ð þ   Þ Response ¼ P0 0  P 0 0  ð þ þ  Þ

(i)

We also evaluated the strength of trait responses by calculating the proportion of responding traits per taxonomic group as follows:

P0 0  P 0 0  ð þ þ  Þ Proportion ¼ P0 0  P0 0  P 0 0  ð þ þ  þ 0 Þ

(ii)

The aggregated response was only calculated for taxonomic groups or traits for which more than 10 studies were available. All calculations and graphics were done in R (R Development Core Team, 2014).

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Fig. 1. Number of investigated traits per taxonomic group. Count refers to the number of studies.

Fig. 2. The direction (on the left-hand side) and strength (on the right-hand side) of traits response to climate change and pollution. For strength, several symbols overlapped, i.e. reproductive capacity of plants, birds, and terrestrial arthropods (proportion ¼ 0.800.90), and mass of fish, phytoplankton, plants and aquatic invertebrates (proportion ¼ 0.750.85).

3. Results 3.1. Literature survey and response of taxonomic groups Most of the 558 studies (78%) targeted the effects of climate change, with 22% of the studies focussing on pollution. The majority of studies dealt with the response of the traits of terrestrial plants (22%), phytoplankton (20%), birds (17%) and aquatic invertebrates (12%). Microorganisms traits were least studied and accounted for 5% of studies. Climate change was primarily assessed using the traits of terrestrial plants (28%), birds (21%) and phytoplankton (13%), whereas nutrients and toxicants were mainly assessed using

the traits of phytoplankton (41%) and aquatic invertebrates (25%), respectively (Fig. 1). Among the taxonomic groups, all traits were investigated for invertebrates, whereas only functional diversity, mass and traits related to tolerance were investigated for microorganisms (Fig. 1). Climate change was primarily investigated using mass and reproductive capacity (>40 studies) and size of birds, terrestrial plants and phytoplankton. In addition, traits related to tolerance of fish and aquatic invertebrates were also frequently (>20 studies) used to investigate climate change. Pollution was primarily investigated using mass of phytoplankton, and traits related to tolerance, dispersal and reproduction of aquatic invertebrates (Fig. 1). Aquatic

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invertebrates and terrestrial arthropods responded most strongly (proportion of studies: > 95%) to climate change through tolerance and reproductive capacity. With regard to pollution, aquatic invertebrates responded most strongly (proportion of studies: > 90%) through reproductive capacity (Fig. 2).

despite relying on relatively unspecific response traits. Invertebrate traits were also successfully applied in the development of a salinity indicator, and an index to classify study sites with respect to €fer et al., 2011). toxicity categories (Archaimbault et al., 2010; Scha 4.2. Convergence and strength of trait responses

3.2. Convergence of trait responses across taxonomic groups The traits related to tolerance responded to climate change most uniformly across taxonomic groups (Fig. 2). Aquatic invertebrates, fish, terrestrial arthropods and plants with traits related to tolerance increased in response to climate change. In addition, the reproductive capacity of birds, aquatic invertebrates and terrestrial arthropods and plants increased, whereas the body size of terrestrial arthropods, aquatic invertebrates, phytoplankton, birds and fish decreased. With regard to pollution, the aquatic invertebrates' traits related to tolerance, reproduction and dispersal increased (Fig. 2). The mass of phytoplankton increased, and the reproductive capacity of birds decreased in response to pollution. 4. Discussion 4.1. Use of traits in studies on climate change and pollution In comparison with microorganisms, the traits of organisms such as terrestrial plants and aquatic invertebrates have been widely used to characterize the effects of multi-stressors on ecosystems (e.g. Chessman, 2009; Dobrowski et al., 2011; Foden et al., 2013). This discrepancy may be because easily accessible online trait databases are available for terrestrial plants (e.g. LEDA, BIOPOP and TRY plant traits databases, Poschlod et al., 2003; Kleyer et al., 2008; Kattge et al., 2011), invertebrates (e.g. freshwaterecology.info database, Schmidt-Kloiber and Hering, 2015), birds and phytoplankton. Such trait databases are missing for microorganisms (Table S1) and may reflect the limited autecological knowledge (Green et al., 2008). More importantly, studies on the response of microorganisms to climate change and pollution partly focus on functional genes and their diversity rather than organism traits (e.g. Liang et al., 2011; Sun et al., 2015). The latter were the main focus of our meta-analysis, which may explain the low number of microbial studies it covered. The lower number of trait studies on pollution may partly follow from the fact that pollution often occurs on smaller spatial and temporal scales (Beelen et al., 2009) and traits may be particularly useful when assessing changes over large areas (Woodward et al., 2013). Nevertheless, a trait-based approach allowed for the derivation of thresholds for pesticides in freshwater ecosystems based on data from different regional studies (Sch€ afer et al., 2012). In addition, ecosystems are subject to multiple stressors concurrently, and traits may help to disentangle effects from different stressors ^che, and to study interactions between stressors (Statzner and Be 2010; Moe et al., 2013; Mondy and Usseglio-Polatera, 2013). Moreover, the term pollution comprises different chemicals such as nutrients, inorganic and organic toxicants, which differ in their modes of actions and may consequently differ in their trait responses (Rubach et al., 2010; Swain et al., 2010). Additionally, pollution may involve pulse (short-term, discrete events), press (sharp increase to maintain a constant level), or ramp (increasing intensity over time) disturbances (Bender et al., 1984; Lake, 2000), which have been suggested to differ in their trait responses €fer et al., 2011). Thus, the merits of trait-based approaches (Scha may be limited, when adaptations are required for pollutants with different modes of action and disturbance regimes. Nevertheless, trait-based approaches were successfully applied for aquatic in€fer and Liess, 2013), vertebrates for a wide range of toxicants (Scha

We found a convergence in the response of traits, particularly traits related to tolerance, to climate change across taxonomic groups. Moreover, traits related to tolerance and reproduction responded strongest with more than 80% of studies that found significant effects. The tolerance of organisms to stressors plays the crucial role for the response and, in the case of press and ramp disturbances where the stressor prevails (Lake, 2000), may also influence recovery. The strong response of traits related to reproduction can be explained by their implications for coping with stress, with a higher number of offsprings and more frequent reproduction fostering recovery and adaptation (Møller et al., 2010). Traits related to size and mass exhibited contrasting responses. For example, terrestrial plants rather increased in size and mass, whereas most studies on phytoplankton demonstrated a decrease in size (Daufresne et al., 2009). The differences in the response of size and mass can be explained by the differences in ecological processes and confounding factors that may be found in different ecosystems. The increase in size and mass of terrestrial plants, through enhanced growth, may result from increased precipitation and carbon dioxide fertilisation due to global warming. The decrease in size of phytoplankton may be a consequence of climate-enhanced grazing of the large-sized phytoplankton species by zooplankton (Amthor, 1995; Winder and Sommer, 2012). Generally, reduction in body size may be more pronounced for organisms with short generation times (e.g. hours to weeks for phytoplankton, Hansen and Carey, 2015), due to their ability to respond rapidly to environmental changes, when compared with organisms with long generation times (e.g. up to 150 years for trees, Petit and Hampe, 2006) (Hetem et al., 2014). Moreover, global warming can cause pronounced body size declines in ectothermic organisms since more metabolic energy is needed to achieve and maintain adult body sizes at elevated temperatures (Daufresne et al., 2009; Sheridan and Bickford, 2011). Given that environmental temperatures can affect the body sizes and metabolic rates of organisms differently (see Kingsolver and Huey, 2008; Dillon et al., 2010; Buckley et al., 2012), this may also explain the differences in body size responses (Fig. 2). Despite the observed differences in size and mass, the general negative correlation between tolerance and size responses is in agreement with the fact that desiccation-tolerant organisms tend to be small in size (Alpert, 2006). Moreover, the climate-induced decline in body sizes found in our meta-analysis for aquatic organisms is in agreement with Daufresne et al. (2009). Although dispersal has been shown as a crucial response mechanism for climate change (Berg et al., 2010; Travis et al., 2013), few studies scrutinized dispersal as a response to climate change. This may be attributed to the fact that dispersal has not been adequately integrated in many studies, which have small spatio-temporal scales (Table S2). We concur with Gardner et al. (2011) that more large-scale studies on the effect of climate change are needed to explicitly link traits to global climate change. The contrasting trait responses (e.g. reproduction) observed in our study may also be due to different trait responses across species under experimental and natural conditions (see also Sandel et al., 2010). Finally, correlations exist between traits (i.e. trait syndromes, Verberk et al., 2013; Díaz et al., 2013), and it can be difficult to establish clear links between traits and stressors if the response of one trait is a consequence of environmental filtering for a linked trait.

J.G. Mbaka et al. / Acta Oecologica 69 (2015) 65e70

5. Conclusions Our meta-analysis shows that trait convergence is limited to few traits. Traits related to tolerance and reproduction responded most strongly to stress, suggesting that they may potentially have higher power to detect climate change and pollution. The links between traits (e.g. dispersal capacity) and stressors (e.g. climate change) on regional or global scales need further scrutiny. Further analysis on the combined effects of climate change and pollution on organisms are required to predict trait responses in multiple multi-stressor scenarios. Finally, it would be important to account for the type of disturbance regime in future analyses on trait responses to pollutants, as it might reveal stronger convergence. Unfortunately, low sample size precluded us to account for this in this study. Author contributions Conceived the study: J.G.M. and R.B.S. Reviewed papers: J.G.M. Performed data analysis E.S. Wrote paper: J.G.M. and R.B.S. Disclosure All authors have approved the final article. No competing interests exist. Acknowledgements We are grateful for comments on an earlier version of the ndez Gonza lez, Katharina Peters and manuscript by Diego Ferna two anonymous reviewers. The work was funded by the German Academic Exchange Service (DAAD) (Grant number: A/12/91652). Appendix A. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.actao.2015.09.002. References Alpert, P., 2006. Constraints of tolerance: why are desiccation-tolerant organisms so small or rare? J. Exp. Biol. 209, 1575e1584. Amthor, J.S., 1995. Terrestrial higher plants response to increasing atmospheric [Co2] in relation to the global carbon cycle. Glob. Change Biol. 1, 243e274. Archaimbault, V., Usseglio-Polatera, P., Garric, J., Wasson, J., Babut, M., 2010. Assessing pollution of toxic sediment in streams using bio-ecological traits of benthic macroinvertebrates. Freshw. Biol. 55, 1430e1446. Aubin, I., Venier, L., Pearce, J., Moretti, M., 2013. Can a trait-based multi-taxa approach improve our assessment of forest management impact on biodiversity? Biodivers. Conserv. 22, 2957e2975. Barnosky, A.D., Hadly, E.A., Bascompte, J., Berlow, E.L., Brown, J.H., Fortelius, M., Getz, W.M., Harte, J., Hastings, A., Marquet, P.A., Martinez, N.D., Mooers, A., Roopnarine, P., Vermeij, G., Williams, J.W., Gillespie, R., Kitzes, J., Marshall, C., Matzke, N., Mindell, D.P., Revilla, E., Smith, A.B., 2012. Approaching a state shift in Earth's, biosphere. Nature 486, 52e58. Baudron, A.R., Needle, C.L., Rijnsdorp, A.D., Tara Marshall, C., 2014. Warming temperatures and smaller body sizes: synchronous changes in growth of North Sea fishes. Glob. Change Biol. 20, 1023e1031. ^che, L.A., Resh, V.H., 2007. Biological traits of benthic macroinvertebrates in Be California mediterranean-climate streams:long-term annual variability and trait diversity patterns. Fundam. Appl. Limnol. 169, 1e23. Beelen, R., Hoek, G., Pebesma, E., Vienneau, D., de Hoogh, K., Briggs, D.J., 2009. Mapping of background air pollution at a fine spatial scale across the. Eur. Union. Sci. Total Environ. 407, 1852e1867. Bender, E.A., Case, T.J., Gilpin, M.E., 1984. Perturbation experiments in community ecology: theory and practice. Ecology 65, 1e13. Berg, M.P., Kiers, E.T., Driessen, G., Van Der Heijden, M., Kooi, B.W., Kuenen, F., Liefting, M., Verhoef, H.A., Ellers, J., 2010. Adapt or disperse: understanding species persistence in a changing world. Glob. Change Biol. 16, 587e598. Buckley, L.B., Hurlbert, A.H., Jetz, W., 2012. Broad-scale ecological implications of

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