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1.
J Environ Manage ; 279: 111529, 2021 Feb 01.
Artículo en Inglés | MEDLINE | ID: mdl-33246754

RESUMEN

Urbanised estuaries, ports and harbours are often utilised for recreational purposes, notably recreational angling. Yet there has been little quantitative assessment of the footprint and intensity of these activities at scales suitable for spatial management. Urban and industrialised estuaries have previously been considered as having low conservation value, perhaps due to issues with contamination and disturbance. Studies in recent decades have demonstrated that many of these systems are still highly biodiverse and of high value to local residents. As a response, urbanised estuaries are now being considered by coastal spatial management initiatives, where assessments of recreational use in these areas can help avoid 'user-environmental' and 'user-user' conflict. The models of these activities need to be developed at a scale relevant to governments and regulatory authorities, but the few human-use models that do exist integrate fishing intensity to a regional or even continental scale; too large to capture the fine scale variation inherent in complex urban fisheries. Species Distribution Modeling (SDM) is a tool commonly used to assess drivers of species range, but can be applied to models of recreational fishing in complex environments, at a scale relevant to regulatory bodies. Using point-data from 573 visual surveys with recently developed Poisson point process models, we examine the recreational fishery in Australia's busiest estuarine port, Sydney Harbour. We demonstrate the utility of these models for understanding the distribution of boat and shore-based fishers, and the effects of a range of temporally static (geographical) and dynamic (weather) predictors on these distributions.


Asunto(s)
Conservación de los Recursos Naturales , Estuarios , Biodiversidad , Explotaciones Pesqueras , Humanos , Recreación
2.
J Environ Manage ; 261: 110203, 2020 May 01.
Artículo en Inglés | MEDLINE | ID: mdl-32148273

RESUMEN

Sea-level rise is an inevitable consequence of climate change and threatens coastal ecosystems, particularly intertidal habitats that are constrained by landward development. Intertidal habitats support significant biodiversity, but also provide natural buffers from climate-threats such as increased storm events. Predicting the effects of climate scenarios on coastal ecosystems is important for understanding both the degree of habitat loss for associated ecological communities and the risk of the loss of coastal buffer zones. We take a novel approach by combining remote sensing with the IUCN Red List of Ecosystem criteria to assess this impact. We quantified the extent of horizontal intertidal rocky shores along ~200 km of coastline in Eastern Australia using GIS and remote-sensing (LiDAR) and used this information to predict changes in extent under four different climate change driven sea-level rise scenarios. We then applied the IUCN Red List of Ecosystems Criterion C2 (habitat degradation over the next 50 years based on change in an abiotic variable) to estimate the status of this ecosystem using the Hawkesbury Shelf Marine Bioregion as a test coastline. We also used four individual rocky shores as case studies to investigate the role of local topography in determining the severity of sea-level rise impacts. We found that, if the habitat loss within the study area is representative of the entire bioregion, the IUCN status of this ecosystem is 'near threatened', assuming that an assessment of the other criteria would return lower categories of risk. There was, however, high spatial variability in this effect. Rocky shores with gentle slopes had the highest projected losses of area whereas rocky shores expanding above the current intertidal range were less affected. Among the sites surveyed in detail, the ecosystem status ranged from 'least concern' to 'vulnerable', but reached 'endangered' under upper estimates of the most severe scenario. Our results have important implications for conservation management, highlighting a new link between remote sensing and the IUCN Red List of Ecosystem criteria that can be applied worldwide to assess ecosystem risk to sea-level rise.


Asunto(s)
Conservación de los Recursos Naturales , Ecosistema , Australia , Cambio Climático , Tecnología de Sensores Remotos , Elevación del Nivel del Mar
3.
Conserv Biol ; 31(5): 1196-1201, 2017 10.
Artículo en Inglés | MEDLINE | ID: mdl-28464290

RESUMEN

Although the public desire for healthy environments is clear-cut, the science and management of ecosystem health has not been as simple. Ecological systems can be dynamic and can shift abruptly from one ecosystem state to another. Such unpredictable shifts result when ecological thresholds are crossed; that is, small cumulative increases in an environmental stressor drive a much greater change than could be predicted from linear effects, suggesting an unforeseen tipping point is crossed. In coastal waters, broad-scale seagrass loss often occurs as a sudden event associated with human-driven nutrient enrichment (eutrophication). We tested whether the response of seagrass ecosystems to coastal nutrient enrichment is subject to a threshold effect. We exposed seagrass plots to different levels of nutrient enrichment (dissolved inorganic nitrogen) for 10 months and measured net production. Seagrass response exhibited a threshold pattern when nutrient enrichment exceeded moderate levels: there was an abrupt and large shift from positive to negative net leaf production (from approximately 0.04 leaf production to 0.02 leaf loss per day). Epiphyte load also increased as nutrient enrichment increased, which may have driven the shift in leaf production. Inadvertently crossing such thresholds, as can occur through ineffective management of land-derived inputs such as wastewater and stormwater runoff along urbanized coasts, may account for the widely observed sudden loss of seagrass meadows. Identification of tipping points may improve not only adaptive-management monitoring that seeks to avoid threshold effects, but also restoration approaches in systems that have crossed them.


Asunto(s)
Ecosistema , Eutrofización , Conservación de los Recursos Naturales , Océanos y Mares , Poaceae
4.
PLoS One ; 17(6): e0271005, 2022.
Artículo en Inglés | MEDLINE | ID: mdl-35771754

RESUMEN

[This corrects the article DOI: 10.1371/journal.pone.0216107.].

5.
PLoS One ; 14(4): e0216107, 2019.
Artículo en Inglés | MEDLINE | ID: mdl-31013329

RESUMEN

[This corrects the article DOI: 10.1371/journal.pone.0190370.].

6.
PLoS One ; 13(4): e0190370, 2018.
Artículo en Inglés | MEDLINE | ID: mdl-29624579

RESUMEN

Seagrasses are in decline globally due to sustained pressure from coastal development, water quality declines and the ongoing threat from climate change. The result of this decline has been a change in coastal productivity, a reduction in critical fisheries habitat and increased erosion. Attempts to slow this decline have included legislative protection of habitat and direct restoration efforts. Monitoring the success of these approaches requires tracking changes in the abundance of seagrasses, but such monitoring is frequently conducted at either too coarse a spatial scale, or too infrequently to adequately detect changes within individual meadows. Here, we used high resolution aerial imagery to quantify the change in meadows dominated by Posidonia australis over five years at 14 sites in five estuaries in south-eastern Australia. Australia has some of the world's most diverse and extensive seagrass meadows, but the widely distributed P. australis has a slow growth rate, recovers poorly after disturbance, and suffers runaway attrition if the conditions for recovery are not met. In 2010, after declines of 12-57% between the 1940s and 1980s, P. australis was listed as a threatened ecological community in New South Wales. We quantified changes in area at fine spatial scales and, where loss was observed, describe the general patterns of temporal decline within each meadow. Our results demonstrate that seagrass meadows dominated by P. australis underwent declines of ~ 2-40% total area at 11 out of 14 study sites between 2009 and 2014. In the iconic Sydney Harbour, our analyses suggest that P. australis meadows are declining at an average rate greater than 10% yr-1, exceeding the global rate of seagrass decline. Highlighting these alarming declines across the study region should serve as means to prioritise management action and review the effectiveness of legislative listing as a method to limit impacts at an ecosystem level.


Asunto(s)
Alismatales/crecimiento & desarrollo , Conservación de los Recursos Naturales , Especies en Peligro de Extinción/estadística & datos numéricos , Monitoreo del Ambiente , Imágenes Satelitales
7.
Ecol Evol ; 7(13): 4640-4650, 2017 07.
Artículo en Inglés | MEDLINE | ID: mdl-28690794

RESUMEN

Historically, marine ecologists have lacked efficient tools that are capable of capturing detailed species distribution data over large areas. Emerging technologies such as high-resolution imaging and associated machine-learning image-scoring software are providing new tools to map species over large areas in the ocean. Here, we combine a novel diver propulsion vehicle (DPV) imaging system with free-to-use machine-learning software to semi-automatically generate dense and widespread abundance records of a habitat-forming algae over ~5,000 m2 of temperate reef. We employ replicable spatial techniques to test the effectiveness of traditional diver-based sampling, and better understand the distribution and spatial arrangement of one key algal species. We found that the effectiveness of a traditional survey depended on the level of spatial structuring, and generally 10-20 transects (50 × 1 m) were required to obtain reliable results. This represents 2-20 times greater replication than have been collected in previous studies. Furthermore, we demonstrate the usefulness of fine-resolution distribution modeling for understanding patterns in canopy algae cover at multiple spatial scales, and discuss applications to other marine habitats. Our analyses demonstrate that semi-automated methods of data gathering and processing provide more accurate results than traditional methods for describing habitat structure at seascape scales, and therefore represent vastly improved techniques for understanding and managing marine seascapes.

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