bioRxiv Science⌕ Search

bioRxiv · 10.1101/2022.04.18.488673

Severe drought events trigger long-term salt marsh dieback in the Southeastern and Gulf of Mexico USA

Abstract

The frequency of salt marsh dieback events has increased over the last 25 years with unknown consequences to the resilience of the ecosystem to accelerated sea level rise (SLR). Salt marsh ecosystems impacted by sudden vegetation dieback events were previously thought to recover naturally within a few months to years. In this study, we provide evidence that approximately 14% of total marsh area has not revegetated 10-years after a dieback event in Charleston, SC. Dieback onset coincided with a severe drought in 2012, and a second dieback event occurred in 2016 after a historic flood influenced by Hurricane Joaquin in October of 2015, with unvegetated zones reaching nearly 30% of total marsh area in 2017. Most affected areas were associated with lower elevation zones in the interior of the marsh (midmarsh). During the 2013 dieback event, we estimate that unvegetated midmarsh area expanded by 300%. Grass planting was shown to be an effective restoration practice, with restored plants having greater aboveground biomass than relict sites after two years of transplanting. A positive restoration outcome indicated that the stressors that caused the initial dieback are no longer present. Despite that, many dieback areas have not recovered naturally even as they are located within the typical elevation range of a healthy vegetated marsh. A mechanistic modelling approach was used to assess the effects of vegetation dieback on salt marsh resilience to SLR. Predictions indicate that a highly productive restored marsh (2000 g m-2 y-1) would persist at a moderate SLR rate of 60 cm 100 y-1, whereas a non- restored mudflat would lose all of its elevation capital after 100 years. Thus, rapid restoration of marsh dieback is critical to avoid further degradation. Also, failure to incorporate the increasing frequency and intensity of extreme climatic events which trigger irreversible marsh diebacks underestimates salt marsh vulnerability to climate change. At an elevated SLR rate of 122 cm 100 y-1, most likely an extreme climate change scenario, even highly productive ecosystems augmented by sediment placement would not keep pace with SLR. Thus, climate change mitigation actions are also urgently needed to preserve present-day marsh ecosystems.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Rolando, J. L., Hodges, M., Garcia, K. D., Krueger, G., Williams, N., Carr, J., Robinson, J., George, A., Morris, J. T., Kostka, J. E.. 2022-04-18. Severe drought events trigger long-term salt marsh dieback in the Southeastern and Gulf of Mexico USA. https://doi.org/10.1101/2022.04.18.488673

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Beyond Single-Metric Assessments: Uncovering Masked Butterfly Declines via Multi-Scalar Analysis in Central Alberta

1. This study analyzed 21 years (2000-2025) of butterfly count data from Central Alberta, integrated with intensive 5-year (2021-2025) high-resolution intra-seasonal sampling. 2. Long-term macro-scale analysis revealed a significant decline in Shannon Diversity, a change that remained obscured when relying solely on traditional metrics of species richness and evenness. 3. This diversity decline was primarily driven by the severe, long-term collapse of the native Common Ringlet (Coenonympha tullia). 4. Four other dominant species--Cabbage White (Pieris rapae), Clouded Sulphur (Colias eriphyle), European Skipper (Thymelicus lineola), and Common Wood Nymph (Cercyonis pegala)--maintained long-term population stability, though their abundances were significantly constrained by extreme winter minimum temperatures and rapid spring warming. 5. High-resolution intra-seasonal analysis (2021-2025) demonstrated that community indices and species-specific abundances were strongly limited by daily weather, particularly wind velocity and temperature. 6. These findings illustrate that while traditional metrics like richness and evenness are fundamental to community ecology, they provide incomplete insights when applied in isolation; they are most effective when utilized as part of a complementary, multi-scalar framework. 7. This study highlights the necessity of coupling multi-decadal historical datasets with high-frequency, fine-scale sampling to accurately identify the mechanisms of community turnover that simpler metrics may overlook. 8. The results underscore the critical importance of standardized citizen science monitoring in quantifying environmental impacts and establishing conservation priorities for terrestrial insect groups.

ecology↗

From concentration to export: resource contrasts and bee traits shape pollinator spillover to crops

Floral plantings can either concentrate bees or export them to adjacent crops, yet the ecological conditions influencing these outcomes remain unclear. Here, we develop a mathematical model as proof of concept for our previous integrative hypothesis: concentrator and exporter outcomes can arise as alternative, context-dependent outcomes of the same underlying resource-selection process. Using bees as a model and focusing specifically on spillover from floral plantings to crops, we identified resource-specific thresholds separating concentration- and export-favoring conditions. Our model translates differences in relative patch attractiveness into context-dependent concentration and export outcomes and generates resource-specific, testable predictions about the conditions favoring pollinator movement into crops. In our simulations, the concentrator-exporter transition occurred at a lower flowering-intensity contrast than at pollen or nectar contrasts, which suggests that flowering intensity may provide an initial cue for bee movement, whereas nectar and pollen rewards refine or sustain bee responses once crops are perceived as attractive. Spillover thresholds differed among resource contrasts, whereas response steepness varied across bee-trait and community scenarios. Under the model's trait-sensitivity formulation, predicted spillover probability responded more strongly to flowering contrast for specialists than for generalists; colony size amplified this response, whereas bee richness dampened it. Together, these patterns show how flowering and resource contrasts interact with bee traits and community context to shape predicted spillover. Our results confirm that the concentrator and exporter hypotheses can be understood as context-dependent outcomes of the same ecological process rather than as mutually exclusive alternatives. Experimental tests of the predicted thresholds conducted in the field could reveal when and where floral plantings are most likely to promote bee spillover to crops, potentially supporting crop pollination.

ecology↗

A Computational Re-evaluation of Spatial Trials for Zoonotic Tuberculosis Control: Model Misspecification, Diagnostic Miss-classification, and the Illusion of Wildlife Culling Efficacy

1. Wildlife reservoir management frequently relies on the Randomised Badger Culling Trial's (RBCT) trade-off hypothesis, which posits that reductions in cattle herd infections are offset by a perturbation effect driven by disrupted host dispersal. This paper evaluates the computational and epidemiological robustness of this historical trial, which serves as the foundational empirical experiment guiding zoonotic tuberculosis (Mycobacterium bovis) control policies. 2. Using generalized linear mixed models with a generalized Poisson error distribution to explicitly address historical data overdispersion, this study contrasts traditional parametric inference against exact cluster-constrained permutation tests across distinct operational definitions of disease incidence. 3. Non-parametric diagnostics reveal that previously reported treatment and perturbation effects render as statistical artifacts under exact non-parametric permutation. Inside culling zones, parametric significance fails to withstand exact permutation verification due to extreme data leverage in localized cluster blocks. 4. Crucially, when diagnostic misclassification biases are eliminated by analysing total reactor datasets, all apparent culling effects disappear, and information criteria overwhelmingly favour nested null architectures. Unconfirmed reactors likely represent true biological infections missed by low-sensitivity post-mortem macro-necropsy, proving that host removal tracks observation noise rather than genuine zoonotic transmission pathways. 5. Finally, empirical scaling conducted in this study identifies a novel mathematical saturation effect, demonstrating that this sub-linear scaling is an operational artifact of unmodelled herd-level disease recurrence over time. 6. Policy implications. Because current zoonotic tuberculosis intervention frameworks are built upon a structurally misspecified statistical model, they have driven large-scale veterinary policies resulting in substantial, unevidenced ecological and economic interventions while failing to provide genuine public health, animal health, or disease control benefits.

ecology↗