Jennifer M. Sunday’s research while affiliated with McGill University and other places

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Publications (39)


Fig. 1. Current state-based, and proposed alternative mechanism-based, approaches to defining and monitoring for resilience in marine protected areas (MPAs).
Measurements, mechanisms, and management recommendations for how marine protected areas can provide climate resilience
  • Article

November 2024

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60 Reads

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2 Citations

Marine Policy

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Jennifer E Caselle

The number of marine protected areas (MPAs) implemented globally is rising, with calls to protect 30 % of the ocean by 2030. One potential benefit of MPAs is increased resilience to anthropogenic climate change impacts. However, realistic ecological expectations are needed to identify the conditions that may yield resilience benefits and determine effective evaluation methods. To date, global meta-analyses have consistently shown positive ecological effects of protection, yet assessing resilience effects has been more complex. 'Resilience' is challenging to define and measure and may manifest at various spatiotemporal scales. Additionally, identifying an appropriate reference point to quantify resilience is challenging. Robust assessments require long time series to estimate variability or opportunistic observation of disturbance and recovery. Such data are not always available. We suggest an alternative, complementary approach. First, it is crucial to define the ecological and socioeconomic mechanisms by which an MPA could provide any resilience benefit to the human-natural system; these mechanisms are both limited and context-dependent. Then, we can measure indicators of resilience to assess the contribution of such mechanisms inside MPAs. This provides a pathway to assess how conservation influences adaptive capacity, overcoming the challenge of directly measuring resilience itself. Finally, it is critical to recognize that MPAs are only one tool in a portfolio of management actions that could improve resilience. They should not be misconstrued as standalone solutions, but rather as integral parts of a comprehensive approach to ecosystem-based sustainability management.


Effect of environmental DNA sampling resolution in detecting nearshore fish biodiversity compared to capture surveys

October 2024

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41 Reads

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1 Citation

Sampling and sequencing marine environmental DNA (eDNA) provides a tool that can increase our ability to monitor biodiversity, but movement and mixing of eDNA after release from organisms before collection could affect our inference of species distributions. To assess how conditions at differing spatial scales influence the inferred species richness and compositional turnover, we conducted a paired eDNA metabarcoding and capture (beach seining) survey of fishes on the coast of British Columbia. We found more taxa were typically detected using eDNA compared to beach seining. eDNA identified more taxa with alternative habitat preferences, and this richness difference was greater in areas of high seawater movement, suggesting eDNA has a larger spatial grain influenced by water motion. By contrast, we found that eDNA consistently missed low biomass species present in seining surveys. Spatial turnover of communities surveyed using beach seining differed from that of the eDNA and was better explained by factors that vary at small (10–1000s meters) spatial scales. Specifically, vegetation cover and shoreline exposure explained most species turnover from seining, while eDNA turnover was not explained by those factors and showed a distance decay pattern (a change from 10% to 25% similarity from 2 km to 10 km of distance), suggesting unmeasured environmental variation at larger scales drives its turnover. Our findings indicate that the eDNA sample grain is larger than that of capture surveys. Whereas seining can detect differences in fish distributions at scales of 10s–100s of meters, eDNA can best summarize fish biodiversity at larger scales possibly more relevant to regional biodiversity assessments.


(a) Euler plot depicting observations of species per site detected only by eDNA (yellow), only by trawl (blue), and by both methods (green) at the regional level. The size of species is proportional to the incidence of a given species, with the smallest fish detected only once, and the largest fish detected 15 times. (b) Euler plot depicting observation of species per site detected only by trawl (blue) and by both eDNA and trawl (green) at the regional level. The size of species is proportional to the species’ biomass density (kg/km), with the smallest fish with a mean biomass (standardized by the net‐tow length of the trawl) of 1.22e‐04 kg/km and the largest fish with a mean biomass of 3.87 kg/km. Species silhouettes for both panels were sourced from phylopic or outlined from pictures featured in FishBase.
(a) Map illustrating the location of scientific trawl surveys and concurrent eDNA water collection sampling around Vancouver Island, BC, Canada, with numbers corresponding to sites. (b) Euler plots depicting observed species detected only by eDNA (yellow), only by trawl (blue), and by both methods (green) at the regional (top), subregional and site (bottom) levels. Southern sites detected more species overall than northern sites. Sites 1 through 7 are northern sites while sites 8 through 16 are southern sites.
Principal coordinate analysis (PCoA) plot illustrating community similarity between species’ detected by eDNA sampling (hollow, dashed circles) and by trawl surveys (filled, solid circles). The color of the point and line correlates to the region of sampling, in the north (yellow), the south (blue). The plots represent the dissimilarity and clustering patterns of species composition across different spatial scales and sampling regions. (a) Points corresponding to the same set number between eDNA samples and trawl samples are connected with a line and labeled by set. (b) Convex hulls show the grouping of samples collected by eDNA in the north (yellow/dashed), eDNA in the south (blue/dashed), trawls in the north (yellow/solid), and trawls in the south (blue, solid).
(a) Maximum species length (cm) density distributions for all species caught in trawl (blue) and all species caught in eDNA (yellow) (b) Maximum species length (cm) density distributions of species exclusively caught in trawl (blue), exclusively in eDNA (yellow) and in both methods (green) (a, b) These distributions do not reflect the actual length distributions from the trawl but rather represent a species‐level trait distribution. (c) Standardized biomass density in (kg/km) of all fish detected in trawl, comparing distributions of fish found only in trawl (blue) and those also found in eDNA (green). Note log‐scale of y‐axis.
Alluvial diagram illustrating the relationship between habitat (left) and detection methods (right). The strength of the relationship is proportional to the size of the chord. The depth range of the trawl (0–200 m) encompasses benthopelagic, pelagic, and bathypelagic habitats. Habitats are listed in order of decreasing depths.
Detection differences between eDNA and mid‐water trawls are driven by fish biomass and habitat preferences
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July 2024

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339 Reads

Marine scientific trawl surveys are commonly used to assess the distribution and population size of fisheries‐related species, yet the method is effort‐intensive and can be environmentally destructive. Sequencing environmental DNA (eDNA) from water samples can reveal the presence of organisms in a community without capturing them; however, we expect the detectability of taxa to differ between eDNA and trawl surveys, and understanding how species traits and population variables contribute to detection differences can help calibrate our expectations from each form of sampling. Here, we coupled eDNA metabarcoding and capture trawl surveys in British Columbia, Canada, to examine species traits that explain recurrent differences in detectability between the two methods, including habitat, body size, and biomass. At the regional scale, 17 of 23 fish species (74%) captured by the trawl were detected by eDNA metabarcoding, and 39 additional species were detected by eDNA sampling only. We found that eDNA metabarcoding disproportionately detected trawl‐caught species with greater local biomass (i.e., greater biomass in the adjacent trawl). Fish detected only in eDNA had a greater range of body lengths and a broader range of habitat preferences outside the trawls' target size and sampling areas. Our results suggest that with our level of sampling, eDNA metabarcoding can adequately recapitulate detection of fish communities detected by trawl surveys, but with a bias toward fish of high population biomass and greater inclusion of fish from outside the trawled area.

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Schematic of the goals, processes, and summary of the teaching tutorials created as part of the Living Data Tutorials. The upper panel shows the overarching goal to link open science in research and open science in teaching, the middle panel shows the process of tutorial development (data exploration, conceptual exploration, tutorial objectives, and tutorial format), and the lower panel shows the six undergraduate teaching tutorials.
of content, examples, and knowledge testing questions covered in the tutorial, “Community Ecology: Hemlock Looper Outbreak on Anticosti Island”. (a) Students interpret community ecology plots by describing tree communities using box plots of species' abundances and using bar graphs to estimate the proportion of each tree species that was damaged by the hemlock looper (Objective 1). (b) Students evaluate the hemlock looper's tree species preferences by plotting tree species' mortality against tree species' abundance (Objective 2). (c) Students make management recommendations in other geographical regions based on information covered throughout the tutorial and suggested videos provided in this section (Objective 3).
“Understanding Biodiversity with Metrics & Rank Abundance Curves” tutorial content and examples of the material and exercises. Students are taught to (a) identify, calculate, and implement commonly used metrics (richness, Shannon and Simpson diversity, and evenness) to quantify biodiversity (Objective 1), (b) understand and create rank abundance curves to visualize biodiversity (Objective 2), and (c) use the R package “codyn” to calculate diversity metrics and plot over time to visualize biodiversity change following disturbance (Objective 3).
Harnessing open science practices to teach ecology and evolutionary biology using interactive tutorials

May 2024

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80 Reads

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1 Citation

Open science skills are increasingly important for a career in ecology and evolutionary biology (EEB) as efforts to make data and analyses publicly available continue to become more commonplace. While learning core concepts in EEB, students are also expected to gain skills in conducting open science to prepare for future careers. Core open science skills like programming, data sharing, and practices that promote reproducibility can be taught to undergraduate students alongside core concepts in EEB. Yet, these skills are not always taught in biology undergraduate programs, and a major challenge in developing open science skills and learning EEB concepts simultaneously is the high cognitive load associated with learning multiple disparate concepts at the same time. One solution is to provide students with easily digestible, scaffolded, pre‐formatted code in the form of vignettes and interactive tutorials. Here, we present six open source teaching tutorials for undergraduate students in EEB. These tutorials teach fundamental ecological concepts, data literacy, programming (using R software), and analysis skills using publicly available datasets while introducing students to open science concepts and tools. Spanning a variety of EEB topics and skill levels, these tutorials serve as examples and resources for educators to integrate open science tools, programming, and data literacy into teaching EEB at the undergraduate level.


Conceptual relationships between population growth rate, temperature and resource concentration, with predicted competitive outcomes. Relationships illustrated are produced from the Norberg‐Resource model that allows the half‐saturation constant, Ks, to vary with temperature (see Methods) using hypothetical parameters for illustration. Population growth rate relationships generated from this model with temperature and nutrient concentration of two species (panels a and b, sharing colour scale of panel a, see Supplementary Methods for model parameters used) can be cut along a single temperature (dotted vertical lines, c) to show a Monod curves with a differing half‐saturation constants (Ks) for each species (shown in panel c). Cutting along a nutrient concentration (horizontal solid lines, d) shows the thermal response curve for the population growth rate at that concentration (panel d). The zero‐net‐growth isocline (dashed line, e) provides a prediction for how the minimum resource requirement for growth, or R*, changes with temperature according to this model (panel e), in this case predicting that species 1 will win in a resource competition at low temperatures and species 2 will win at high temperatures. (f) Considering multiple species with similar curve shapes and differing curve heights shows how patterns of competitive dominance for a single limiting resource based on R* could be different from those with the highest population growth rate across temperatures. See supplementary materials for model parameters.
Estimates of population growth rates as a function of temperature and nitrate concentration. Points indicate estimates of growth rates from models fit to cell density data within each temperature and nutrient treatment for Amphidinium carterae (AC), Chlamydomonas sp. (CH), Chroomonas salina (CS) and Tetraselmis tetrahele (TT). Lines indicate best‐fit model predictions from the best model for each species (Norberg model with Ks varying with temperature for AC and TT, Norberg model with Ks fixed for CH and CS) that included temperature, nitrate and time. Black points indicate the thermal optimum of population growth rate from best‐fit direct models.
Population growth rates and predicted minimum resource requirement as a function of temperature. (a) Lines represent the mean estimates of nutrient‐replete intrinsic growth rate (upper panel) and R* (lower panel) from the best‐fit model fitted to the data in Experiment 1, for Amphidinium carterae (AC), Chlamydomonas sp. (CH), Chroomonas salina (CS) and Tetraselmis tetrahele (TT). Grey‐shaded areas represent upper and lower 95% confidence intervals based on model bootstrapping. Points in the upper panels indicate estimates of nutrient‐replete intrinsic growth rate based on indirect model‐fits of growth rate to nutrient concentrations across temperature (fitting a Monod model at every temperature, Table S2). (b) Comparison of curve shape for functional responses of growth rate (r) and minimum resource requirements (R*) as a function of temperature of each species. Values represent estimates of curve asymmetry (based on skewness as usually applied to probability distributions), curve ‘flatness’ (based on kurtosis as usually applied to probability distributions) and thermal optima (temperature of maximum r and minimum R*). Lines connect values of the same species, with colour representing species as in panel (a).
Estimated growth rates and minimum resource requirements from experiments of populations brought to equilibrium under semi‐continuous flow. All values from Experiment 2, for Amphidinium carterae (AC), Chlamydomonas sp. (CH), Chroomonas salina (CS) and Tetraselmis tetrahele (TT). Population growth rates (r) were estimated from logistic‐growth equations fit to cell density as a function of time; minimum resource requirements were estimated as asymptotic environmental nitrate concentrations at population equilibrium. (a) Points indicate estimated values from each independent replicate, and lines with shading indicate best‐fit generalized additive models with 95% confidence intervals. The upper row shows the temperature dependance of population growth rate, and bottom row shows the temperature dependence of R*. (b) Comparison of curve shape for functional responses of growth rate (r) and minimum resource requirements (R*) as a function of temperature of each species. Values represent estimates of curve asymmetry (based on skewness as usually applied to probability distributions), curve flatness (based on kurtosis as usually applied to probability distributions) and thermal optima (temperature of maximum growth rate and minimum R*). Lines connect values of the same species, with colour representing species as in panel (a).
Review of population growth and minimum resource requirement (R*) across temperatures compiled from other studies. (a) Colours represent species of bacteria and microalgae from 5 previous data sources in which growth rate and R* were estimated or could be derived across multiple experimental temperatures (Bestion et al., 2018; Descamps‐Julien & Gonzalez, 2005; Lewington‐Pearce et al., 2019; Reay et al., 1999; Tilman et al., 1981). Dashed lines highlight a single result counter to general predictions. (b) The same results are shown after standardizing temperatures to degrees (°C) above or below the optimum temperature for each metric; lines have slight transparency to show overlap. Growth rates were standardized across species to indicate growth rates relative to the within‐study maximum (hence all curves cross 0,1).
Temperature dependence of competitive ability is cold-shifted compared to that of growth rate in marine phytoplankton

December 2023

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117 Reads

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7 Citations

Ecology Letters

The effect of climate warming on community composition is expected to be contingent on competitive outcomes, yet approaches to projecting ecological outcomes often rely on measures of density‐independent performance across temperatures. Recent theory suggests that the temperature response of competitive ability differs in shape from that of population growth rate. Here, we test this hypothesis empirically and find thermal performance curves of competitive ability in aquatic microorganisms to be systematically left‐shifted and flatter compared to those of exponential growth rate. The minimum resource requirement for growth, R* —an inverse indicator of competitive ability—changes with temperature following a U‐shaped pattern in all four species tested, contrasting from their left‐skewed density‐independent growth rate thermal performance curves. Our results provide new evidence that exploitative competitive success is highest at temperatures that are sub‐optimal for growth, suggesting performance estimates of density‐independent variables might underpredict performance in cooler competitive environments.


Temperate species underfill their tropical thermal potentials on land

November 2023

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600 Reads

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12 Citations

Nature Ecology & Evolution

Understanding how temperature determines the distribution of life is necessary to assess species' sensitivities to contemporary climate change. Here, we test the importance of temperature in limiting the geographic ranges of ectotherms by comparing the temperatures and areas that species occupy to the temperatures and areas species could potentially occupy on the basis of their physiological thermal tolerances. We find that marine species across all latitudes and terrestrial species from the tropics occupy temperatures that closely match their thermal tolerances. However, terrestrial species from temperate and polar latitudes are absent from warm, thermally tolerable areas that they could potentially occupy beyond their equatorward range limits, indicating that extreme temperature is often not the factor limiting their distributions at lower latitudes. This matches predictions from the hypothesis that adaptation to cold environments that facilitates survival in temperate and polar regions is associated with a performance trade-off that reduces species' abilities to contend in the tropics, possibly due to biotic exclusion. Our findings predict more direct responses to climate warming of marine ranges and cool range edges of terrestrial species.


Harnessing open science practices to teach ecology and evolution using interactive tutorials

August 2023

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127 Reads

Open science skills are increasingly important for a career in ecology and evolution as efforts to make data and analyses publicly available and transparent continue to become more commonplace. However, open science skills are not typically taught in biology undergraduate programs. In learning core concepts in ecology and evolutionary biology (EEB), students must also gain skills in open science or they will miss out on opportunities to prepare for future careers. Core open science skills, like programming and practices that promote reproducibility and data sharing, can be taught to undergraduate students alongside core concepts in EEB. Yet, a major challenge in teaching open science skills and EEB concepts simultaneously is the high cognitive load associated with teaching multiple disparate concepts at the same time. One solution is to provide students with easily digestible, scaffolded, pre-formatted code in the form of vignettes and interactive tutorials. Here we present six open-source teaching tutorials for undergraduate students in EEB. These tutorials were developed through a graduate student based working group entitled Data Bytes in Ecology and Evolutionary Biology. These tutorials combine teaching data literacy and programming (using R) with analyzing publicly available data sets to teach fundamental ecological and evolutionary concepts and by doing so, introduce students to open science concepts and tools. Spanning a variety of EEB topics and skill levels, these tutorials serve as examples of how educators can integrate open science tools, programming, and data literacy into undergraduate teachings in topics of ecology and evolution.


Global patterns of thermal niche filling in ectotherms

August 2023

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828 Reads

Understanding how temperature determines the distribution of life is necessary to assess species’ sensitivities to contemporary climate change. Here we test the importance of temperature in limiting the geographic ranges of ectotherms by comparing the temperatures and areas that species occupy to the temperatures and areas species could potentially occupy based on their physiological thermal tolerances. We find that marine species at large and terrestrial species from the tropics occupy temperatures that closely match their thermal tolerances. However, terrestrial species from temperate and polar latitudes are absent from warm, thermally tolerable areas that they could potentially occupy beyond their equatorward range limits, indicating that temperature is often not the factor limiting their distributions at lower latitudes. This supports the hypothesis that the adaptation to cold necessary to live in temperate and polar regions is associated with a performance trade-off that reduces species’ abilities to contend in the tropics, possibly due to biotic exclusion. Our findings predict more direct responses to climate warming of marine ranges and cool range edges of terrestrial species.


Model description
a, The biophysical model uses heat transfer principles to simulate body temperature and thermal performance of a lizard-like ectotherm that thermoregulates behaviourally by moving between sun-exposed and shaded conditions. The model uses information on body mass, skin absorbance, preferred temperature (Tpref), thermoregulatory ability (λ) and critical thermal limits (CTmax and CTmin). b, To perform the sensitivity analysis of the biophysical model, we changed the value of one trait at a time drawing random values from their input distributions. Then, the effect of each trait on cumulative performance is estimated by computing the slope of the relationship between the change in performance and the change in each trait value. This process is repeated across locations (grid cells) on a global map to investigate emerging geographical patterns of trait sensitivity.
Sensitivity of thermal performance to each functional trait
Predicted effect of each functional trait on thermal performance. Negative sensitivity values (blue shading) indicate that an increase in the trait value reduces thermal performance, whereas positive values (red shading) denote that higher trait values increase thermal performance.
Relationship between mean species traits and predicted sensitivity
a–d, Observed body mass (a), preferred temperature (b) and maximum (c) and minimum (d) critical thermal limits of lizard species in relation to the predicted sensitivity of cumulative performance to variation in each trait modelled across its geographical range. Dashed line represents non-significant relationship (see model estimates and standard errors in Table 1).
Trait variances of species assemblages in relation to the absolute value of sensitivity
a–d, Relationship between the variance in body mass (a), preferred temperature (b) and maximum (c) and minimum (d) critical thermal limits of lizard assemblages in relation to the sensitivity of thermal performance to variation in each trait. Trait variances were corrected for spatial autocorrelation using Moran eigenvectors. Dashed and solid lines represent, respectively, fitted values of the ordinary and quantile linear regressions (quantile 0.9) and shaded areas are regression confidence intervals. Each grey circle represents trait variance in one cell and circle size is proportional to the percentage of species with known trait value data at each cell.
Climate drives global functional trait variation in lizards

March 2023

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887 Reads

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13 Citations

Nature Ecology & Evolution

A major challenge in ecology and evolution is to disentangle the mechanisms driving broad-scale variation in biological traits such as body size, colour, thermal physiology traits and behaviour. Climate has long been thought to drive trait evolution and abiotic filtering of trait variation in ectotherms because their thermal performance and fitness are closely related to environmental conditions. However, previous studies investigating climatic variables associated with trait variation have lacked a mechanistic description of the underpinning processes. Here, we use a mechanistic model to predict how climate affects thermal performance of ectotherms and thereby the direction and strength of the effect of selection on different functional traits. We show that climate drives macro-evolutionary patterns in body size, cold tolerance and preferred body temperatures among lizards, and that trait variation is more constrained in regions where selection is predicted to be stronger. These findings provide a mechanistic explanation for observations on how climate drives trait variation in ectotherms through its effect on thermal performance. By connecting physical, physiological and macro-evolutionary principles, the model and results provide an integrative, mechanistic framework for predicting organismal responses to present climates and climate change.


Map showing the location of each reef community in Bocas del Toro, Panama. Colouring corresponds to reef type: lagoonal reef or forereef. Letters represent reef community locations: Isla Colon (C), Cayo Roldan (R), Isla Cristobal Sureste (O), Isla Solarte (S), Isla Bastimento (B), Cayo Agua (A), Isla Bastimento Norte (N), Zapatilla Oeste (Z), Peninsula Valiente (V), Tobobe (T), Almirante Pta. Gallinazo (G).
Variation in reef community composition and function across space and time. Colouring shows two spatially distinct types of reef communities differentiated by benthic cover (A, D, G), coral species (B, E, H), and coral traits (C, F, I). Each point represents one of 11 reef communities in a given year. PCoA and MFA biplots show variation in all communities across all years (A-C) and the species most associated (D-F). Coloured ellipses highlight the reef type associated with each species or trait. Timeplots show temporal variation in community composition along the first PCoA and MFA axes (G-I). Black lines represent the predicted trends and coloured bands represent standard error. Grey dashed lines mark the years during which bleaching events occurred in Bocas del Toro. Asterisks mark significant trends (*p <.05; **p <.01; ***p <.001). Letters represent reef locations and mark community composition in 2013.
Environmental conditions that drive variation in reef community composition and function across space and time. Colouring within each RDA triplot differentiates lagoonal reef and forereef communities of benthic cover (A), the coral species (B), and coral traits (C). Points represent each of 11 reef communities in Bocas del Toro every year of monitoring. Arrows show the loading of environmental variables that explain variation within and between reef communities. Letters represent reef locations and mark community composition in 2013.
Change in reef community diversity over time. Temporal change in lagoonal reef and forereef taxonomic, or coral species, diversity (A) and functional, or coral trait, diversity (B). Black lines show the predicted trend, coloured lines show the observed trends of individual reef communities and coloured bands represent standard error. Grey, dashed lines mark the years during which bleaching events occurred in Bocas del Toro. Asterisks mark significant trends (*p <.05; ***p <.001). Letters represent reef locations and mark community diversity in 2013.
Spatial and temporal variation in reef community composition. Dominant benthic cover, coral species, and traits shown are those with highest loading scores in PCoA and MFA ordination spaces.
Spatio-temporal patterns in coral reef composition and function across an altered environmental gradient: A 15-year study in the Caribbean

January 2023

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503 Reads

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4 Citations

Coral species, which function to build the framework structure of reef ecosystems, vary across sheltered to exposed environmental gradients. For centuries, conditions in sheltered environments that impact lagoonal reefs have been altered by local anthropogenic disturbances, while conditions in exposed environments that impact forereefs have largely buffered the effects of local anthropogenic disturbances. Yet, bleaching events induced by global anthropogenic disturbances challenge how we predict changes in reef composition and function across environmental gradients. Here, we quantify spatio-temporal variation in the composition and function of 11 coral reefs across sheltered to exposed environmental conditions over 15 years and 3 bleaching events in Bocas del Toro, Panama. We find that the composition and function of lagoonal reefs and forereefs were distinct and shaped by an environmental gradient altered by anthropogenic disturbance. Lagoonal reefs lacked major reef-building species and experienced greater losses in coral species and diversity over time. Although only lagoonal reefs changed in coral species composition, both lagoonal reefs and forereefs became functionally similar over time. Our findings indicate that lagoonal reefs may be less resilient to global environmental change than forereefs due to long-term effects of local anthropogenic disturbances. Additionally, increasing global anthropogenic disturbances might lead to the homogenization of reef function, as reefs adapt to novel environmental conditions.


Citations (29)


... The results of this model would best be used to inform adaptive management in pre-established networks and set expectations for what may happen along a coastline with marine reserves as a species shifts. We do not expect that this research will necessarily drive a redesign of reserve networks as there are often governance barriers to such efforts (Wilson et al. 2020) even as reserve managers seek guidance on how to manage for climate resilience (McLeod et al. 2009;White et al. 2025). That said, there are clear management lessons: if the management goal is to encourage persistence of the shifting species, as in the examples of Atlantic croaker (Micropogonias undulatus; Kleisner et al. 2017) and black rockfish (Sebastes melanops; Fuller et al. 2015), having a network of many small reserves is more likely to benefit the species. ...

Reference:

Managing range-shifting, competing species in marine reserve networks: the importance of reserve configuration and transient dynamics in age-structured populations
Measurements, mechanisms, and management recommendations for how marine protected areas can provide climate resilience
  • Citing Article
  • November 2024

Marine Policy

... Previous studies have shown how sampling effort (through duration or replicate numbers) can improve species detections, particularly in aquatic environments (Willoughby et al., 2016;Millard-Martin et al., 2024). This was evident here when looking at the sampling effort of three replicates per method used at each of the 10 sites, and it is suggested that there is scope for increased species detections for each method (Fig. 5). ...

Effect of environmental DNA sampling resolution in detecting nearshore fish biodiversity compared to capture surveys
  • Citing Article
  • October 2024

... Importantly, our findings can inform new and ongoing development of modular curricula in multiple life science subdisciplines (e.g., evolutionary biology, Griffith et al. 2024 ;microbiology, Dill-McFarland et al. 2021 developers of open-access, modular curricula in the life sciences provide comprehensive instructional support materials (e.g., instructor manuals), consider that "just in time" teaching of data science skills benefits both students and instructors, and plan for ongoing maintenance and iterative revisions of modules using student and instructor feedback. ...

Harnessing open science practices to teach ecology and evolutionary biology using interactive tutorials

... A study combining new theory with laboratory assays integrated the temperature-dependence expression from MTE with the resource availability expression from the Monod equation to model temperature and nutrient-dependent population growth . They theoretically demonstrated that the optimum temperature for growth shifts towards colder temperatures under lower resource availability: an expectation that was corroborated with empirical data from phytoplankton growth assays (Sunday et al., 2023;Thomas et al., 2017). While this approach models effects of resource availability on population growth in a way that is not captured by canonical MTE, it omits top-down effects of population density on resource availability. ...

Temperature dependence of competitive ability is cold-shifted compared to that of growth rate in marine phytoplankton

Ecology Letters

... In addition, variation in rates of warming in space could mean that divergent thermal limits are reached at similar levels of global warming. For instance, tropical species are thought to be closest to their thermal limits [46], with recent evidence suggesting terrestrial temperate species are underfilling the warmer end of their niches [150]. While this would be expected to temper the abruptness of biodiversity loss, faster warming at high latitudes ('polar amplification' [151]) or high elevations could cause a greater clustering in when thermal limits are exceeded across latitudes. ...

Temperate species underfill their tropical thermal potentials on land

Nature Ecology & Evolution

... Ectotherms are an ideal system for studying environmental adaptation in the context of climate change due to their reliance on external thermal and hydric gradients (Angilletta 2009;Siepielski et al. 2017;Baeckens et al. 2021;Cox & Cox 2015). Lizards, in particular, provide a useful model for testing climate related hypotheses, and have been the focus of several multi-taxa studies investigating their vulnerability, resilience, and relationship with climate (Rubalcaba et al. 2023;Jara et al. 2019;Lanna et al. 2022;Sinervo et al. 2010;Sinervo et al. 2024;Cosendey et al. 2022;Garcia-Porta et al. 2019).The Western-Canaries Lizard, Gallotia galloti, is a medium sized lacertid endemic to the islands of Tenerife and La Palma (Canary Islands), and the most abundant reptile inhabiting all environments of Tenerife. Tenerife's diverse environments encompass an elevational gradient from sea level to the peak of El Teide stratovolcano over 3700 m, which is accompanied by a shift in vegetation structure and microclimate (Sperling et al. 2004). ...

Climate drives global functional trait variation in lizards

Nature Ecology & Evolution

... The cryptic host lineages identified here were structured across an inshore to offshore gradient in the BTRC, with L2 and L3 more prevalent inside Bahia Almirante (inshore), and L1 more prevalent outside the bay (offshore). Inshore BTRC sites are characterized by limited influence from the open ocean, riverine inputs that deliver nutrients, agricultural runoff and sewage to the bay, higher turbidity, and, most recently, hypoxic events that have altered coral communities (38,39). We find evidence that lineages exhibit unique skeleton morphologies that could contribute to their success in these distinct environments. ...

Spatio-temporal patterns in coral reef composition and function across an altered environmental gradient: A 15-year study in the Caribbean

... We recognize that there are other possible frameworks for combining the effects of oxygen and temperature on fish (e.g. the aerobic growth index in Clarke et al. 2021, 2022, Moreé et al. 2023, Ern 2019), yet comparison of different frameworks is beyond the scope of this study. The metabolic index was found to closely align with species distributions across biogeographic scales to define species' range limits , Sunday et al. 2022) and has been used to explain contemporary distributions (Franco et al. 2022, Penn and, past extinction events (Penn and Deutsch 2022), and predict future marine habitat shifts (Chen et al. 2024). ...

Biological sensitivities to high‐resolution climate change projections in the California current marine ecosystem

Global Change Biology

... To address this, novel funding strategies must spur the adoption of cooperative research (Rölfer et al., 2021;Rosendal et al., 2016). Networks need financing toward collection rescues and backups, standardization, and education and legal compliance services (Bakker et al., 2020;Bledsoe et al., 2022;Boundy-Mills et al., 2020;Goodwin et al., 2017;O'Brien et al., 2022;Supplementary Table 1). Specimen repositories need expansions to accommodate project vouchers alongside type specimens (Colella et al., 2020). ...

Data rescue: saving environmental data from extinction

... However, these models often rely on many parameters, which are difficult to obtain for the majority of extant taxa. An alternative approach to understanding ectotherm responses to environmental change is to identify common mechanistic links (Srivastava et al. 2021). For example, robust predictions could be formulated based on the effects of temperature on life history traits, which could then be tested in a complex environment under various combinations of biotic and abiotic factors. ...

Wildcards in climate change biology