Seagrass depth range and water quality in southern Moreton Bay, Queensland, Australia

Abal, Eva; Dennison, W.C.

doi:10.1071/mf9960763

Cited by 130 publications

(69 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Although the duration of the current bloom (3.5 months) was not as long as some of the previous blooms, the repeated reduction in light to seagrass habitats during the summer months each year is likely to impact on the health of the seagrass meadows (Abal and Dennison 1996) and may have contributed to the observed decline in the health of seagrass beds in Northern Deception Bay over recent years (Buchanan Heritage Services 2003). Any effect of L. majuscula blooms on the health and fitness of the remaining Deception Bay seagrass beds is of considerable concern as these beds are the only appreciable coastal seagrass beds in Moreton Bay north of the Brisbane River (∼30 km to the south).…”

Section: Environmental and Social Impactsmentioning

confidence: 99%

Mapping the distribution, biomass and tissue nutrient levels of a marine benthic cyanobacteria bloom (Lyngbya majuscula)

Ahern

Ahern²,

Savige³

et al. 2007

Mar. Freshwater Res.

View full text Add to dashboard Cite

Abstract. Benthic cyanobacteria blooms, including those of the nitrogen-fixing species Lyngbya majuscula, appear to be becoming more numerous and widespread in marine habitats worldwide, and have negative impacts on the environment and human health. The progression of a L. majuscula bloom in south-east Queensland, Australia was mapped along with intensive biomass and tissue nutrient sampling every 10-14 days over the bloom's 3.5-month duration in summer [2005][2006]. Data-integrated GIS maps illustrated the changes in biomass and tissue nutrient pool of the L. majuscula through different growth phases (incipient, rapid expansion, plateau or peak and decline) of the bloom. At the peak, L. majuscula covered 509 ha and had a mean density of 115 g dw m −2 , with the maximum density recorded 503 g dw m −2 . The highest mean total carbon (29.4% C), nitrogen (3.5% N) and phosphorus (0.143% P) contents in L. majuscula tissue corresponded with the peak in biomass. Three-dimensional modelling calculated that at the peak, the bloom contained 5057 t ww (510 t dw ) of L. majuscula; 150 000 kg C; 18 000 kg N; 720 kg P; and 5200 kg Fe. This information gives an insight into L. majuscula bloom dynamics and ecophysiology and provides quantitative data for models.

show abstract

Section: Environmental and Social Impactsmentioning

confidence: 99%

Mapping the distribution, biomass and tissue nutrient levels of a marine benthic cyanobacteria bloom (Lyngbya majuscula)

Ahern

Ahern²,

Savige³

et al. 2007

Mar. Freshwater Res.

View full text Add to dashboard Cite

show abstract

“…The maximum depth of seagrass distribution has been used as a bioindicator of estuarine health (Abal and Dennison 1996), and a similar approach has been used for coral communities to infer changes in water quality on coral reefs (Kleypas 1996;van Woesik et al 1999;Cooper et al 2007). Coral growth and distribution is determined by available irradiance (Yentsch et al 2002), and the maximum depth of coral reef development can be defined as the zone of transition from zooxanthellate hard corals to azooxanthellate filter feeders along a depth gradient.…”

Section: Maximum Depth Of Coral-reef Developmentmentioning

confidence: 99%

Bioindicators of changes in water quality on coral reefs: review and recommendations for monitoring programmes

2009

View full text Add to dashboard Cite

Effective environmental management requires monitoring programmes that provide specific links between changes in environmental conditions and ecosystem health. This article reviews the suitability of a range of bioindicators for use in monitoring programmes that link changes in water quality to changes in the condition of coral-reef ecosystems. From the literature, 21 candidate bioindicators were identified, whose responses to changes in water quality varied spatially and temporally; responses ranged from rapid (hours) changes within individual corals to long-term (years) changes in community composition. From this list, the most suitable bioindicators were identified by determining whether responses were (i) specific, (ii) monotonic, (iii) variable, (iv) practical and (v) ecologically relevant to management goals. For long-term monitoring programmes that aim to quantify the effects of chronic changes in water quality, 11 bioindicators were selected: symbiont photophysiology, colony brightness, tissue thickness and surface rugosity of massive corals, skeletal elemental and isotopic composition, abundance of macro-bioeroders, micro-and meiobenthic organisms such as foraminifera, coral recruitment, macroalgal cover, taxonomic richness of corals and the maximal depth of coralreef development. For short-term monitoring programmes, or environmental impact assessments that aim to quantify the effects of acute changes in water quality, a subset of seven of these bioindicators were selected, including partial mortality. Their choice will depend on the specific objectives and the timeframe available for each monitoring programme. An assessment framework is presented to assist in the selection of bioindicators to quantify the effects of changing water quality on coral-reef ecosystems.

show abstract

“…In general, for all SAV species there is a strong positive relationship between water clarity and the maximum water column depth to which plants grow (Chambers and Kalff 1985;Duarte 1991;Abal and Dennison 1996;Olesen 1996). Numerous statistical models have been reported describing relationships between maximum SAV colonization depth (Z c ) and water transparency measured by K d or Secchi depth (Canfield et al 1985;Vant et al 1986;Duarte and Kalff 1987;Carter et al 2000).…”

Section: Minimum Light Requirement For Sav Survivalmentioning

confidence: 99%

Habitat requirements for submerged aquatic vegetation in Chesapeake Bay: Water quality, light regime, and physical-chemical factors

et al. 2004

View full text Add to dashboard Cite

We developed an algorithm for calculating habitat suitability for seagrasses and related submerged aquatic vegetation (SAV) at coastal sites where monitoring data are available for five water quality variables that govern light availability at the leaf surface. We developed independent estimates of the minimum light required for SAV survival both as a percentage of surface light passing through the water column to the depth of SAV growth (PLW min ) and as a percentage of light reaching leaves through the epiphyte layer (PLL min ). Values were computed by applying, as inputs to this algorithm, statistically derived values for water quality variables that correspond to thresholds for SAV presence in Chesapeake Bay. These estimates of PLW min and PLL min compared well with the values established from a literature review. Calculations account for tidal range, and total light attenuation is partitioned into water column and epiphyte contributions. Water column attenuation is further partitioned into effects of chlorophyll a (chl a), total suspended solids (TSS) and other substances. We used this algorithm to predict potential SAV presence throughout the Bay where calculated light available at plant leaves exceeded PLL min . Predictions closely matched results of aerial photographic monitoring surveys of SAV distribution. Correspondence between predictions and observations was particularly strong in the mesohaline and polyhaline regions, which contain 75-80% of all potential SAV sites in this estuary. The method also allows for independent assessment of effects of physical and chemical factors other than light in limiting SAV growth and survival. Although this algorithm was developed with data from Chesapeake Bay, its general structure allows it to be calibrated and used as a quantitative tool for applying water quality data to define suitability of specific sites as habitats for SAV survival in diverse coastal environments worldwide.

show abstract

Seagrass depth range and water quality in southern Moreton Bay, Queensland, Australia

Cited by 130 publications

References 0 publications

Mapping the distribution, biomass and tissue nutrient levels of a marine benthic cyanobacteria bloom (Lyngbya majuscula)

Mapping the distribution, biomass and tissue nutrient levels of a marine benthic cyanobacteria bloom (Lyngbya majuscula)

Bioindicators of changes in water quality on coral reefs: review and recommendations for monitoring programmes

Habitat requirements for submerged aquatic vegetation in Chesapeake Bay: Water quality, light regime, and physical-chemical factors

Contact Info

Product

Resources

About