Predicting seagrass decline due to cumulative stressors

Adams, Matthew; Koh, Edwin J.Y.; Vilas, María P.; Collier, Catherine; Lambert, Victoria; Sisson, Scott A.; Quiroz, Matias; McDonald‐Madden, Eve; McKenzie, Len; O’Brien, Katherine R.

doi:10.1016/j.envsoft.2020.104717

Cited by 30 publications

(53 citation statements)

References 81 publications

(111 reference statements)

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“…To design a marine protection system for all seagrass communities, these spatial complexities and differing sensitivities to environmental conditions would need to be adapted into a broader marine protection approach. We are now able to better evaluate environmental risk to seagrass habitats from natural processes and anthropogenic activity and to assess environmental threats that affect seagrass at a large scale including cyclones and floods 4 , 36 , 58 , climate change 59 , 60 , and more localised impacts such as coastal development, dredging, and oil spills 61 , 62 . Spatial assessments of cumulative anthropogenic risk to seagrasses in the GBRWHA found risks tend to accumulate where ports and coastal development pressures overlay with inputs from coastal catchment runoff 38 .…”

Section: Discussionmentioning

confidence: 99%

A spatial analysis of seagrass habitat and community diversity in the Great Barrier Reef World Heritage Area

Carter

Collier

Lawrence

et al. 2021

Sci Rep

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The Great Barrier Reef World Heritage Area (GBRWHA) in north eastern Australia spans 2500 km of coastline and covers an area of ~ 350,000 km2. It includes one of the world’s largest seagrass resources. To provide a foundation to monitor, establish trends and manage the protection of seagrass meadows in the GBRWHA we quantified potential seagrass community extent using six random forest models that include environmental data and seagrass sampling history. We identified 88,331 km2 of potential seagrass habitat in intertidal and subtidal areas: 1111 km2 in estuaries, 16,276 km2 in coastal areas, and 70,934 km2 in reef areas. Thirty-six seagrass community types were defined by species assemblages within these habitat types using multivariate regression tree models. We show that the structure, location and distribution of the seagrass communities is the result of complex environmental interactions. These environmental conditions include depth, tidal exposure, latitude, current speed, benthic light, proportion of mud in the sediment, water type, water temperature, salinity, and wind speed. Our analysis will underpin spatial planning, can be used in the design of monitoring programs to represent the diversity of seagrass communities and will facilitate our understanding of environmental risk to these habitats.

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Section: Discussionmentioning

confidence: 99%

A spatial analysis of seagrass habitat and community diversity in the Great Barrier Reef World Heritage Area

Carter

Collier

Lawrence

et al. 2021

Sci Rep

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“…Therefore, the interaction between stressors is now viewed as a critical issue, and it is suggested that single-factor experiments are not adequate for assessing the effects of several disturbances on coastal marine ecosystems (Wernberg et al, 2012;Todgham and Stillman, 2013;Ontoria et al, 2019b). In the last years, an increasing number of papers aiming to understand cumulative impacts of stressors have exponentially increased (Gunderson et al, 2016;Adams et al, 2020;Stockbridge et al, 2020), and more empirical data on the effects of the interaction of increasing temperature and nutrient over-enrichment at an individual level has been obtained (Touchette and Burkholder, 2002;Bintz et al, 2003;Touchette et al, 2003;Burnell et al, 2013;Kaldy, 2014;Kaldy et al, 2017;Egea et al, 2018;Moreno-Marín et al, 2018;Mvungi and Pillay, 2019;Ontoria et al, 2019b). Nevertheless, responses depend on their local adaptation and life history traits (Tuya et al, 2019;Anton et al, 2020) are species-specific, and to our knowledge, there is very limited information about the combined effects of these two stressors in any tropical seagrasses species (Artika et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Species-Specific Trait Responses of Three Tropical Seagrasses to Multiple Stressors: The Case of Increasing Temperature and Nutrient Enrichment

2020

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Seagrass meadows are declining globally. The decrease of seagrass area is influenced by the simultaneous occurrence of many factors at the local and global scale, including nutrient enrichment and climate change. This study aims to find out how increasing temperature and nutrient enrichment affect the morphological, biochemical and physiological responses of three coexisting tropical species, Thalassia hemprichii, Cymodocea serrulata and Halophila stipulacea. To achieve these aims, a 1-month experiment under laboratory conditions combining two temperature (maximum ambient temperature and current average temperature) and two nutrient (high and low N and P concentrations) treatments was conducted. The results showed that the seagrasses were differentially affected by all treatments depending on their lifehistory strategies. Under higher temperature treatments, C. serrulata showed photoacclimation strategies, while T. hemprichii showed decreased photo-physiological performance. In contrast, T. hemprichii was resistant to nutrient over-enrichment, showing enhanced nutrient content and physiological changes, but C. serrulata suffered BG nutrient loss. The limited response of H. stipulacea to nutrient enrichment or high temperature suggests that this seagrass is a tolerant species that may have a dormancy state with lower photosynthetic performance and smaller-size individuals. Interaction between both factors was limited and generally showed antagonistic effects only on morphological and biochemical traits, but not on physiological traits. These results highlight the different effects and strategies co-inhabiting seagrasses have in response to environmental changes, showing winners and losers of a climate change scenario that may eventually cause biodiversity loss. Trait responses to these stressors could potentially make the seagrasses weaker to cope with following events, due to BG biomass or nutrient loss. This is of importance as biodiversity loss in tropical seagrass ecosystems could change the overall effectiveness of ecosystem functions and services provided by the seagrass meadows.

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“…(A topographical interpretation of these findings is also provided in the next section.) In this way, we also demonstrated that our methods are well-suited for applications where there is little prior knowledge about the parameter values (14-16, 29) but also for those where prior beliefs can be confidently included as part of the model-data fitting process (6,8,35,36,58,59).…”

Section: Discussionmentioning

confidence: 73%

Analysis of sloppiness in model simulations: unveiling parameter uncertainty when mathematical models are fitted to data

Monsalve-Bravo,

Lawson,

Drovandi

et al. 2022

Preprint

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are informed primarily from the data or are also substantively influenced by the priors. We focus on the very common context in complex systems where the amount and quality of data are low compared to the number of model parameters to be collectively estimated, and showcase the benefits of our technique for applications in biochemistry, ecology, and cardiac electrophysiology. We also show how stiff parameter combinations, once identified, uncover controlling mechanisms underlying the system being modeled and inform which of the model parameters need to be prioritized in future experiments for improved parameter inference from collective model-data fitting.Teaser: Bayesian analysis of sloppiness unveils critical parameter combinations that have strong influence on the model outputs.

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Predicting seagrass decline due to cumulative stressors

Cited by 30 publications

References 81 publications

A spatial analysis of seagrass habitat and community diversity in the Great Barrier Reef World Heritage Area

A spatial analysis of seagrass habitat and community diversity in the Great Barrier Reef World Heritage Area

Species-Specific Trait Responses of Three Tropical Seagrasses to Multiple Stressors: The Case of Increasing Temperature and Nutrient Enrichment

Analysis of sloppiness in model simulations: unveiling parameter uncertainty when mathematical models are fitted to data

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