Abstract
Escalating climate impacts on coral reefs are increasingly expanding management goals beyond preserving biodiversity to also maintaining ecosystem functions. Morphological and ecological species traits can help assess changes within reef communities beyond taxonomic identities alone. However, our limited understanding of trait interactions between habitat-building corals and associated reef fishes and whether they are captured by current monitoring practices hampers management. Here, we apply co-inertia analyses to test whether trait assemblages in corals and fishes co-vary across different habitats and test whether different components of the reef fish community (fisheries vs. non-target species) display distinct relationships. We find that spatial co-variation across habitat types between coral and fish traits is strengthened by the addition of non-target fishes. Additionally, even in fisheries with diverse targets, non-target species make unique contributions to the overall trait structure and highlight the importance of considering monitoring protocols when drawing conclusions about traits and ecosystems.
Similar content being viewed by others
Avoid common mistakes on your manuscript.
Introduction
On coral reefs, habitat-building corals are linked to fishes and other associated species through processes that include herbivory (Richardson et al. 2020; Darling et al. 2017), predation (Hempson et al. 2018), and habitat provisioning (Table S1) (Rogers et al. 2014). Traits can in some instances inform our understanding of functions performed by groups of species across spatial, temporal, and disturbance gradients (McLean et al. 2019; Pecuchet et al. 2020) and have applications in management, conservation prioritisation, restoration, and forecasting change (Laughlin et al. 2017; Beukhof et al. 2019; Grenié et al. 2018). A detailed understanding of trait-based composition of communities at relevant scales can thus guide decision-making in fisheries management, invasive species management, and spatial conservation (Givan et al. 2017; McLean et al. 2019; Mbaru et al. 2019). Fundamental to these applications is the use of existing monitoring datasets, but it is unclear whether current programs can effectively address trait-based research questions and support decision-making.
The composition of coral traits, affected by processes such as wave energy exposure and temperature regimes, shapes fish assemblages. For example, morphological traits determine structural complexity and therefore habitat provisioning, food availability, and size-specific refugia for fish assemblages (Darling et al. 2017). This non-random coral trait filtering also mediates disturbance responses (Richardson et al. 2018). Loss of corals with vulnerable traits through disturbances like bleaching-induced mortality affects the structure of fish communities, with planktivore, corallivore, and small-bodied fishes particularly vulnerable (Brandl et al. 2016), whilst herbivore abundances typically increase (Robinson et al. 2019a). The trait composition of fish assemblages in turn can also influence coral recovery trajectories through herbivory (Mumby and Harborne 2010). However, cross-taxon associations between different trait combinations are rarely evaluated, despite the importance of shared relationships across habitat-building and associated taxa.
Here, we explore linked spatial community trait structure of corals and fishes across reef habitats. Some monitoring programs focus on fisheries target (food fish) species (Houk et al. 2015; Andrew et al. 2011; Muller-Karanassos et al. 2021), but clearly, survey methods, trait selection, and trait data availability all impact the results and interpretations of trait-based research (Hadj-Hammou et al. 2021). We highlight the role that non-target fish play in detecting associations between coral and fish trait structure and how this varies across habitats, even on reefs that are subject to frequent disturbance. The objectives of this study are to (1) examine the trait-based structure of coral and fish communities, compare the relative contributions of non-target versus food-fish species to overall trait community structure, and identify traits that characterise specific reef habitats and (2) to test whether this is reflected in a higher correlation of the entre fish community with the coral community compared to food fish alone. Given the general differences in body size, motility, and association with the reef matrix between food and non-target fishes, we expect that non-target species occupy a different trait space and will contribute to stronger co-variation between the coral and fish communities.
Methods
In 2019, we surveyed 39 sites on outer, channel, patch or back and inner reefs at Chuuk Lagoon and Kuop Atoll in Chuuk State, Federated States of Micronesia (Houk et al. 2015) (Fig. 1). Coral bleaching occurred in 2016, causing significant declines in coral cover, particularly at outer reefs. Fish diversity and abundance were recorded with 12 stationary point counts per site (SPCs) (five metre radius, three minutes), distributed evenly across five 50 m transects. Previous monitoring focused on food-fish families identified through landings data (Houk et al. 2015; Cuetos-Bueno et al. 2018), a diverse group comprising of 136 reef fish species (Anderson et al. 2021). In 2019, we also recorded all non-cryptic, non-target families (188 species) (Table S2). Corals (identified to species level) and colony diameter were recorded with ten 1m2 quadrats per site placed along the fish transects (Houk et al. 2015).
To characterise co-occurring coral and fish assemblages, we compiled categorical and numeric trait information related to species’ ecology, morphology, and life history. Coral traits were growth form, larval development mode, growth rate (mm/year), lower depth limit (m), and bleaching susceptibility traits derived from The Coral Trait Database and bleaching vulnerability assessments (Madin et al. 2016; Foden et al. 2013). Fish traits were maximum total length (cm), maximum water depth (m), mean pelagic larval duration (PLD) (days), trophic mode, aggregation type, and water column position, assembled from FishBase (Froese and Pauly 2019) and the literature (Table S1). Where feasible, gaps were imputed within genera using the mean of available trait values (numeric) or the dominant trait (categorical) (Taugourdeau et al. 2014).
All analyses were conducted in R (Supplement). First, we built separate fish and coral trait spaces with principal coordinate analyses (PCoA) on Gower dissimilarity matrices. Within the fish trait space, three distinct fish trait groups were examined—all species, non-target, and food fishes. We then calculated community weighted mean (CWM) values for coral and fish communities from trait tables and log-transformed abundance data (to moderate the effects of extremely abundant species). CWM measures the contribution of each trait to the overall community at each site, weighted by species abundances (Garnier et al. 2004). To pinpoint the traits that characterise coral and fish assemblages across habitats, we ran an indicator species analysis on the CWMs (hereafter indicator trait analysis) (Dufrêne and Legendre 1997). We evaluated co-variation and identified shared patterns between the coral and fish trait communities (CWMs) with two co-inertia analyses. Co-inertia analysis is a flexible multivariate method for examining the shared structure of a pair of data tables (Dray et al. 2003). The first analysis included the whole fish community (both food and non-target species), whilst the second excluded non-target fishes to explore if detecting shared structuring was dependent on these species. For each co-inertia analysis, we ran a permutation test (n = 999) that yielded a p value to test significance, and an RV value to indicate the strength of the co-inertia (0–1, values closer to one indicate stronger correlation between communities).
Results and discussion
Our findings broadly meet our initial expectations of unique trait space contributions and stronger habitat associations with the inclusion of non-target fish species. The coral trait space in Chuuk Lagoon is generally homogenously populated, except for several taxa with unique sets of traits. These are mostly brooding corals with branching or encrusting morphologies (i.e. Isopora palifera) (Fig. 2). There is considerable overlap between food (91.18% of the total trait space) versus non-target fish (73.53% of the trait space), but both also make unique contributions to the trait space (Fig. 2). For the food fish, these are larger species occupying higher trophic levels (e.g. Gracila albomarginata) and for the non-target fish are small, reef-associated species (e.g. Chaetodon ornatissimus) (Fig. 2). There is a greater degree of overlap than we initially expected between food and non-target fish groups, and this reflects the diversity species targeted by Chuuk’s reef fishery. It is important to acknowledge that species traits will change at different life history stages, which we do not address here. The distinct contributions of functionally unique species could indicate candidates for focused monitoring and protection under a trait-based management strategy (McLean et al. 2021). We would expect to see further expansion of the trait space if specific monitoring of cryptobenthic fishes was included (Brandl et al. 2019). The choice to include or exclude different parts of the fish community has wider implications for how we detect and respond to anthropogenic change on coral reefs (Brandl et al. 2018).
Different habitats support assemblages characterised by different traits for both corals and fishes (Table 1). For example, outer reefs host encrusting and sub-massive coral growth forms with greater depth limits that populate the steep drop-offs. The prevalence of sub-massive and encrusting growth forms at outer reefs is probably a reflection of Chuuk’s disturbance history, including past bleaching events and cyclones (Houk et al. 2016). These disturbances disproportionately reduce the abundance of species with branching, fast-growing traits that might otherwise inhabit outer reef sites (Mellin et al. 2019). Contrastingly, inner and patch or back reefs are characterised by encrusting, long upright growth forms, alluding to the high coral cover of species like Porites rus on shallow, inner, and patch reefs in Chuuk (Fig. 1). Broadly, this portrays a post-bleaching coral community that may become increasingly representative of reefs globally as the climate changes (Alvarez-Filip et al. 2013; Hughes et al. 2018). For fishes, traits primarily held by non-target fish species (i.e. harem aggregations, sand-associated positions) are important in characterising the spatial composition of the reef (Table 1). This highlights their role in community structuring, and so the contribution of these species should clearly be incorporated into future trait-based analyses in Chuuk.
Co-inertia between fish and coral trait communities is stronger when all fishes are included in the analysis (p < 0.001), compared to only food fishes (p = 0.049) (Fig. 3). The traits most important for driving variation within the co-inertia differ slightly for each approach (Fig. S3). Fish and coral communities are organised roughly by reef types with outliers retained in the food fish community co-inertia analysis. These outliers represent exposed outer reefs subject to high wave energy. Visually, there is clearer structuring across reef types when non-target species are included and are supported both by the co-inertia and indicator analysis results. This pattern may relate to relative differences in size and therefore motility of food versus non-target fishes (Nash et al. 2015), with typically smaller non-target species exhibiting the greater site specificity that creates these detectable differences in habitat types. In line with prior evidence (Darling et al. 2017), these results highlight that including a wide range of species when discerning trait-based relationships across taxa is crucial, particularly as species with unique sets of traits may support vulnerable ecological roles (Mouillot et al. 2013) that might otherwise be overlooked in monitoring and management efforts.
Monitoring in Chuuk is presently focused on food fish, reflecting local management priorities and the fact that fishing is the primary driver of decline and variability fish assemblages in this region (Harborne et al. 2018; Houk et al. 2015). However, as climate disturbances become more frequent, it may be necessary to expand monitoring to capture the wider fish community (not just food fish) in a way that is still practical and affordable. This is because climate-driven changes in coral trait composition and associated changes in dependent fish species may also have long-term implications for food fish as a resource (Robinson et al. 2019b). We illustrate that trait-based perspectives must be accompanied by careful assessment of parts of the community that are excluded by sampling design.
References
Alvarez-Filip L, Carricart-Ganivet JP, Horta-Puga G, Iglesias-Prieto R (2013) Shifts in coral-assemblage composition do not ensure persistence of reef functionality. Scientific Reports 3(1):3486
Anderson L, Houk P, Miller MG, Cuetos-Bueno J, Graham C, Kanemoto K, Terk E, McLeod E, Beger M (2021) Trait groups as management entities in a complex, multi-species reef fishery. Conservation Biology 36:e13866
Andrew W, Atkinson S, Guilbeaux M, Wong A (2011) Helen reef management plan, 2011–2016. In: Board THR (ed) The Hatohobei State Leadership and the Hatohobei Community
Beukhof E, Frelat R, Pecuchet L, Maureaud A, Dencker TS, Sólmundsson J, Punzón A, Primicerio R, Hidalgo M, Möllmann C, Lindegren M (2019) Marine fish traits follow fast-slow continuum across oceans. Scientific Reports 9(1):17878
Brandl SJ, Emslie MJ, Ceccarelli DM, Richards Z T (2016) Habitat degradation increases functional originality in highly diverse coral reef fish assemblages. Ecosphere 7(11):e01557
Brandl SJ, Goatley CHR, Bellwood DR, Tornabene L (2018) The hidden half: ecology and evolution of cryptobenthic fishes on coral reefs. Biol Rev 93:1846–1873
Brandl SJ, Tornabene L, Goatley CH, Casey JM, Morais RA, Côté IM, Baldwin CC, Parravicini V, Schiettekatte NM, Bellwood DR (2019) Demographic dynamics of the smallest marine vertebrates fuel coral reef ecosystem functioning. Science 364(6446):1189
Cuetos-Bueno J, Hernandez-Ortiz D, Graham C, Houk P (2018) Human and environmental gradients predict catch, effort, and species composition in a large Micronesian coral-reef fishery. PLoS ONE 13(5):e0198068
Darling ES, Graham NAJ, Januchowski-Hartley FA, Nash KL, Pratchett MS, Wilson SK (2017) Relationships between structural complexity, coral traits, and reef fish assemblages. Coral Reefs 36(2):561–575
Dray S, Chessel D, Thioulouse J (2003) Co-inertia analysis and the linking of ecological data tables. Ecology 84(11):3078–3089
Dufrêne M, Legendre P (1997) Species assemblages and indicator species, the need for a flexible asymmetrical approach. Ecological Monographs 67(3):345–366
Foden WB, Butchart SH, Stuart SN, Vié JC, Akçakaya HR, Angulo A, DeVantier LM, Gutsche A, Turak E, Cao L, Donner SD (2013) Identifying the world’s most climate change vulnerable species: a systematic trait-based assessment of all birds, amphibians and corals. PLoS ONE 8(6):e65427
Froese R, Pauly D (2019) Fishbase. www.fishbase.org
Garnier E, Cortez J, Billès G, Navas ML, Roumet C, Debussche M, Laurent G, Blanchard A, Aubry D, Bellmann A, Neill C (2004) Plant functional markers capture ecosystem properties during secondary succession. Ecology 85(9):2630–2637
Givan O, Parravicini V, Kulbicki M, Belmaker J (2017) Trait structure reveals the processes underlying fish establishment in the Mediterranean. Global Ecology and Biogeography 26(2):142–153
Grenié M, Mouillot D, Villéger S, Denelle P, Tucker CM, Munoz F, Violle C (2018) Functional rarity of coral reef fishes at the global scale: hotspots and challenges for conservation. Biological Conservation 226:288–299
Hadj-Hammou J, Mouillot D, Graham NAJ (2021) Response and effect traits of coral reef fish. Frontiers in Marine Science 8:640619
Harborne AR, Green AL, Peterson NA, Beger M, Golbuu Y, Houk P, Spalding MD, Taylor BM, Terk E, Treml EA, Victor S (2018) Modelling and mapping regional-scale patterns of fishing impact and fish stocks to support coral-reef management in Micronesia. Diversity and Distributions 24(12):1729–1743
Hempson TN, Graham NAJ, Macneil MA, Hoey AS, Almany GR (2018) Mesopredator trophodynamics on thermally stressed coral reefs. Coral Reefs 37(1):135–144
Houk P, Camacho R, Johnson S, McLean M, Maxin S, Anson J, Joseph E, Nedlic O, Luckymis M, Adams K, Hess D (2015) The micronesia challenge: assessing the relative contribution of stressors on coral reefs to facilitate science-to-management feedback. PLoS ONE 10:e0130823
Houk P, Deblieck J, Benavente D, Maxin S, Yalon A, McLean M, Teresio C, Graham C, Kutta S, Stephen L, Cuetos-Bueno J (2016) Status and management of coral reefs and fisheries resources in Chuuk Lagoon and Kuop Atoll, Federated States of Micronesia
Hughes TP, Kerry JT, Baird AH, Connolly SR, Dietzel A, Eakin CM, Heron SF, Hoey AS, Hoogenboom MO, Liu G, McWilliam MJ (2018) Global warming transforms coral reef assemblages. Nature 556:492–496
Laughlin DC, Strahan RT, Huffman DW, Sánchez Meador AJ (2017) Using trait-based ecology to restore resilient ecosystems: historical conditions and the future of montane forests in western North America. Restoration Ecology 25(S2):S135–S146
Madin JS, Anderson KD, Andreasen MH, Bridge TC, Cairns SD, Connolly SR, Darling ES, Diaz M, Falster DS, Franklin EC, Gates RD (2016) The Coral Trait Database, a curated database of trait information for coral species from the global oceans. Scientific Data 3:160017
Mbaru EK, Graham NAJ, McClanahan TR, Cinner JE (2019) Functional traits illuminate the selective impacts of different fishing gears on coral reefs. Journal of Applied Ecology 57(2):241–252
McLean M, Auber A, Graham NA, Houk P, Villéger S, Violle C, Thuiller W, Wilson SK, Mouillot D (2019) Trait structure and redundancy determine sensitivity to disturbance in marine fish communities. Global Change Biology 25(10):3424–3437
McLean M, Stuart-Smith RD, Villéger S, Auber A, Edgar GJ, MacNeil MA, Loiseau N, Leprieur F, Mouillot D (2021) Trait similarity in reef fish faunas across the world’s oceans. Proceedings of the National Academy of Sciences 118(12):e2012318118
Mellin C, Thompson A, Jonker MJ, Emslie MJ (2019) Cross-shelf variation in coral community response to disturbance on the great barrier reef. Diversity 11(3):38
Mouillot D, Bellwood DR, Baraloto C, Chave J, Galzin R, Harmelin-Vivien M, Kulbicki M, Lavergne S, Lavorel S, Mouquet N, Paine CT (2013) Rare species support vulnerable functions in high-diversity ecosystems. PLoS Biology 11(5):e1001569
Muller-Karanassos C, Filous A, Friedlander AM, Cuetos-Bueno J, Gouezo M, Lindfield SJ, Nestor V, Marino LL, Mereb G, Olsudong D, Golbuu Y (2021) Effects of habitat, fishing, and fisheries management on reef fish populations in Palau. Fisheries Research 241:105996
Mumby PJ, Harborne AR (2010) Marine reserves enhance the recovery of corals on Caribbean reefs. PLoS ONE 5:e8657
Nash KL, Welsh JQ, Graham NAJ, Bellwood DR (2015) Home-range allometry in coral reef fishes: comparison to other vertebrates, methodological issues and management implications. Oecologia 177:73–83
Pecuchet L, Lindegren M, Kortsch S, Całkiewicz J, Jurgensone I, Margonski P, Otto SA, Putnis I, Strāķe S, Nordström MC (2020) Spatio-temporal dynamics of multi-trophic communities reveal ecosystem-wide functional reorganization. Ecography 43(2):197–208
Richardson LE, Graham NAJ, Hoey AS (2020) Coral species composition drives key ecosystem function on coral reefs. Proceedings of the Royal Society B: Biological Sciences 287(1921):20192214–20192214
Richardson LE, Graham NAJ, Pratchett MS, Eurich JG, Hoey AS (2018) Mass coral bleaching causes biotic homogenization of reef fish assemblages. Global Change Biology 24(7):3117–3129
Robinson JPW, Wilson SK, Jennings S, Graham NAJ (2019a) Thermal stress induces persistently altered coral reef fish assemblages. Global Change Biology 25(8):2739–2750
Robinson JP, Wilson SK, Robinson J, Gerry C, Lucas J, Assan C, Govinden R, Jennings S, Graham NA (2019b) Productive instability of coral reef fisheries after climate-driven regime shifts. Nature Ecology & Evolution 3(2):183–190
Rogers A, Blanchard JL, Mumby PJ (2014) Vulnerability of coral reef fisheries to a loss of structural complexity. Current Biology 24(9):1000–1005
Taugourdeau S, Villerd J, Plantureux S, Huguenin-Elie O, Amiaud B (2014) Filling the gap in functional trait databases: use of ecological hypotheses to replace missing data. Ecology and Evolution 4(7):944–958
Acknowledgements
We are grateful to the Chuuk Department of Marine Resources, Chuuk Conservation Society, Chuuk Women’s Council, and The Nature Conservancy Micronesia for their expertise and practical support. Thanks to Adele Dixon, Christy Starsinic, David Benavente, Clarice Graham, Season Kutta, Andrew McInnis, Selino Maxin, and Chimres Teresio for their participation in data collection. LA was funded by a Faculty Leeds Doctoral Scholarship. This project also received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement TRIM-DLV-747102 to MB.
Author information
Authors and Affiliations
Corresponding authors
Ethics declarations
Conflict of interest
On behalf of all authors, the corresponding author states that there is no conflict of interest.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
About this article
Cite this article
Anderson, L., McLean, M., Houk, P. et al. Co-variation of fish and coral traits in relation to habitat type and fishery status. Coral Reefs 42, 279–284 (2023). https://doi.org/10.1007/s00338-022-02312-0
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00338-022-02312-0