Comparisons of south Florida’s seawall and natural mangrove stands reveal similar structural attributes

Timm, Michael R; Araújo, Rafael J.

doi:10.1016/j.ufug.2018.03.013

Cited by 4 publications

(7 citation statements)

References 21 publications

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“…The complexity index has been criticized because it is strongly influenced by the number of species in the stand (Araújo & Polanía, 1985;Neumann & Starlinger, 2001). Mangrove communities in the New World contain fewer species when compared to their Indo-Pacific counterparts, so the complexity index has been commonly calculated for mangrove forests throughout the Americas (see Timm & Araújo, 2018). For Old World estimates see Kamruzzaman, Osawa, Deshar, Sharma and Mouctar (2017), George et al (2018), and Macamo, Adams, Bandeira, Mabilana and António (2018).…”

Section: Complexity Indexmentioning

confidence: 99%

“…The structural characterization of a mangrove forest is a mandatory step in the evaluation of mangrove areas (Pool, Snedaker, & Lugo 1977;Cintrón & Schaeffer-Novelli, 1983;Timm & Araújo, 2018). Forest structure-a descriptive measure of important attributes of the vegetation-provides a snapshot of mangrove forest development and health (Pool et al, 1977;Cintrón & Schaeffer-Novelli, 1983;Datta & Deb, 2017).…”

Section: Introductionmentioning

confidence: 99%

“…Forest structure-a descriptive measure of important attributes of the vegetation-provides a snapshot of mangrove forest development and health (Pool et al, 1977;Cintrón & Schaeffer-Novelli, 1983;Datta & Deb, 2017). The calculation of structure also permits the delineation of mangrove areas based on similar attributes and allows for baseline assessments and intersite forest comparisons (Cintrón & Schaeffer-Novelli, 1985;Timm & Araújo, 2018). Although the methods used in the calculation of mangrove forest structure were developed for general forestry use, in the 1970s, mangrove ecologists began the process of choosing and standardizing a set of structural attributes that would allow for the characterization of mangrove stands in a wide array of geographical areas (Pool et al, 1977;Martínez, Cintrón & Encarnación, 1979;Schaeffer-Novelli, Cintrón, & Adaime, 1980;Jiménez, 1981).…”

Section: Introductionmentioning

confidence: 99%

“…The protocol was formalized in a classic paper by Cintrón and Schaeffer-Novelli (1984), which provided for a standardized set of methods and techniques to study mangrove structure. Since then, the methodology has been applied by many researchers around the world (Araújo & Polanía, 1985;Cintrón & Schaeffer-Novelli, 1985;Day, Conner, Day, Ley-Lou, & Navarra, 1987;Finn, 1996;Fromard et al, 1998;Lovelock, Feller, McKee, & Thompson, 2005;Timm & Araújo, 2018) and has been used in country-wide assessments and management of mangrove areas and resources (Instituto de Recursos Naturales y del Ambiente [Irena], 1986;Jiménez, 1994;Sánchez-Páez & Alvarez-León, 1997;Araújo, 2006;Arden & Price/University of Miami, 2008).…”

Section: Introductionmentioning

confidence: 99%

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An R package for computation of mangrove forest structural parameters using plot and plotless methods

Araújo

Shideler

2019

MYB

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Mangrove structure is influenced not only by the magnitude and periodicity of favorable energy inputs (temperature, hydroperiod, tides, sunlight, and nutrients), but also by stressors (salinity, drought, storms, and frost), which may have a diminishing effect on forest structure. In worldwide characterization of mangrove forests, researchers use several structural parameters to inform, compare, classify, and evaluate mangrove communities for both research and management. However, the calculation of these structural parameters involves a multi-step series of protocols and formula applications that are error-prone and time consuming. Using standard mangrove structure methodologies found in the literature, the mangroveStructure package for R was developed to deliver a simple tool to quickly calculate mangrove forest structure based on either plot or plotless methods. Outputs of the package include density, diameter, basal area, height, as well as relative values of density, dominance, frequency, and importance value. Output also includes common structural indices (complexity index and mean stand diameter) and visual representations of relative values, diameter and height histograms, and canopy height distributions along the transect line. This package will be useful to scientists interested in mangrove field surveys and those seeking a better understanding of mangrove ecosystems structural variability. To familiarize users with its many features, the package includes example data sets collected in the mangroves of Darién, Panama, and south Florida, USA.

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Section: Complexity Indexmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An R package for computation of mangrove forest structural parameters using plot and plotless methods

Araújo

Shideler

2019

MYB

Self Cite

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“…The critical services and benefits that mangroves provide are broadly recognized [29,30] however, mangroves are also under threat globally [31], and especially so in coastal urban areas where they continue to be cleared for both urban expansion, and infrastructure development, principally port and shipping facilities. In coastal urban areas, maintaining and increasing mangrove cover is understood to be an important component of combating the adverse impacts of climate change for urban populations (see for example [32]), but with the notable exception of recent efforts to steer away from so called grey infrastructure (encompassing engineered structures) and toward green infrastructure for coastal defence [33,34], mangroves are not often identified explicitly as green infrastructure [35].…”

Section: Introductionmentioning

confidence: 99%

Green and Blue Infrastructure in Darwin; Carbon Economies and the Social and Cultural Dimensions of Valuing Urban Mangroves in Australia

Atchison

2019

Urban Science

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Darwin’s mangrove ecosystems, some of the most extensive and biodiverse in the world, are part of the urban fabric in the tropical north of Australia but they are also clearly at risk from the current scale and pace of development. Climate motivated market-based responses, the so-called ‘new-carbon economies’, are one prominent approach to thinking differently about the value of living infrastructure and how it might provide for and improve liveability. In the Australian context, there are recent efforts to promote mangrove ecosystems as blue infrastructure, specifically as blue carbon, but also little recognition or valuation of them as green or urban infrastructure. Drawing on observational and qualitative analysis of semi-structured interviews, this study examines how key stakeholders in Darwin frame and understand mangroves in relation to the urban, and how they are anticipating and responding to governance efforts to frame mangroves and pay for their carbon sequestration and storage services as blue carbon. The push for large infrastructure development and an expanding urban footprint, present serious challenges for mangrove protection, and the study evidences both denial and complacency in this regard. However, although the concept of blue carbon is already taking effect in some circles, it was not viewed as straightforward or as appropriate by all study participants and may very well work in practice to exclude groups within the community. Both clear governance problems, as well as unrecognized and vernacular community connections to mangroves in Darwin, indicate that there are ongoing conceptual and empirical challenges to be considered in recognizing and valuing mangroves as part of urban life.

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Mangroves as Coastal Protection for Restoring Low-Energy Waterfront Property

Weaver,

Stehno

2024

Preprint

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Mangroves offer vital ecological advantages including air and water filtration, coastal and estuarine habitat provision, sediment stabilization, and wave energy absorption. Their intricate root systems play a key role in safeguarding shorelines from tsunamis and erosive storms by dissipating wave energy. Moreover, mangroves shield against boat wakes and wind-waves, bolstering shoreline defense. Wave dissipation is a function of forest width, tree diameter, and forest density. Restoration efforts of juvenile mangroves in Florida’s Indian River Lagoon (IRL) aim to reduce wave energy in areas vulnerable to erosion. Physical model testing of wave dissipation through mangroves is limited due to the complexity in representing the mangrove structure, where prop roots are non-uniform in both diameter and location. Previous studies have quantified wave dissipating effects through use of scaled and parameterized mangrove structures. This study measures the dissipation effects of live mangroves in a wave flume, forced by conditions representative of the IRL. These measurements are used to validate a parameterized dowel model. Error between wave attenuation factors for the live mangrove and dowel system was on average 2.5%. Validation of the modularized dowel system allowed for further parameterized testing to understand forest structure effects, such as sediment stabilization and wave attenuation.

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Comparisons of south Florida’s seawall and natural mangrove stands reveal similar structural attributes

Cited by 4 publications

References 21 publications

An R package for computation of mangrove forest structural parameters using plot and plotless methods

An R package for computation of mangrove forest structural parameters using plot and plotless methods

Green and Blue Infrastructure in Darwin; Carbon Economies and the Social and Cultural Dimensions of Valuing Urban Mangroves in Australia

Mangroves as Coastal Protection for Restoring Low-Energy Waterfront Property

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