Easy-to-use program to predict cumulative light and temperature stress on seagrass Software predictions made from a new process-based model of tropical seagrass decline Model suggests net carbon loss rate controls shoot density decline rate in seagrass Model calibrated to data via two posterior-computation methods for Bayesian inference New generalisable cumulative stress index forecasted by model, including uncertainty
Harmonization exercises organized by the European Communities in the 1970s on biological water assessment methods for running waters, because the usual methods were difficult or impossible to apply, explicitly stressed the need for development of standardized sampling procedures for monitoring large and deep rivers and canals. To meet this objective, an extensive monitoring campaign was organized in Belgium and The Netherlands to test the efficiency of artificial substrates colonized by macroinvertebrates as an alternative for natural communities sampled with a handnet. Two types of artificial substrates were tested: a Belgian substrate, composed of a plastic netting filled with medium-sized pieces of brick, and a Dutch substrate consisting of a stainless steel box filled with marbles. The collected biocoenoses were compared qualitatively and quantitatively. Water quality was assessed by means of several biotic indexes. The results show that both the Belgian and the Dutch artificial substrate sampler can replace the usual samples obtained by means of a handnet, and provide a correct assessment. A major drawback of the use of artificial substrates in uncontrolled monitoring sites remains the unforeseen losses. For that reason the cost price of the substrates may have to be considered when making a selection.
Catchment degradation causing increased sediment flow is one of the key stressors facing Great Barrier Reef (GBR) habitats. Ecologically relevant targets (ERTs) for sediment and nutrient loads have been previously proposed based on seagrass light requirements, the next step is to connect these to ecological response. The overarching goal of the present work is to recommend preliminary thresholds that can be used in the development of more refined ERTs. To achieve this, we perform statistical analysis on datasets for catchment flows and sediment loads and condition of the adjacent seagrass habitat, to identify what might be the direct impacts of catchment discharge on seagrass and the associated timescales of ecological response. Our case study focuses on Cleveland Bay, which is located in the central GBR, and has important seagrass habitat that is affected by discharge from the Burdekin River. Annual monitoring of seagrass biomass and area has been undertaken since 2007. We compare these ecological time-series with data for Burdekin River annual flow and total sediment load from 2005 onwards. Annual Burdekin River flow varied by nearly 40-fold within the 2005-2018 study period, and declines in biomass and area of both subtidal and intertidal seagrasses were associated with high flows and loads from the Burdekin. Subtidal seagrasses appeared more sensitive to changes in catchment discharges than intertidal seagrasses, exhibiting a 3 year timeframe for recovery, following high annual flows and loads. Based on our results, a linear model relating change in seagrass biomass to Burdekin River metrics was used to calculate predicted thresholds below which seagrass biomass was likely to increase, and above which biomass was likely to decline. For seagrass area, a growth threshold, below which seagrass area expanded; and a decline threshold, above which seagrass area fell, were defined for annual Burdekin River flow, and sediment load. Overall these thresholds provide the first steps towards refining ERTs based on ecological condition, which can directly inform the management of the GBR to protect its iconic seagrass habitats and associated communities. The next step is to examine whether the relationship between river discharge and sediment load was the primary cause of seagrass decline.
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