A tool for site prioritisation of marine protected areas under data poor conditions

A challenge of managing data poor fisheries lies in overcoming uncertainties associated with a lack of information on biological and socio-economic conditions. This paper focuses on site prioritisation for marine protected areas, a process that usually imposes moderate to heavy demands on data, time, local expertise, and funds. A fuzzy logic decision support tool for zoning marine areas that is suitable for use in data poor conditions is developed. This tool, the Protected Area Suitability Index (PASI), assesses the suitability of sites for protection based on fishers’ preferences for that site and the site’s conservation value. Only eight input attributes are required to run the PASI, which operates on a series of heuristic rules to estimate a site suitability score that ranges from 0 to 10, where 10 indicates that a site is highly suitable for being protected from fishing. Sensitivity analysis reveals that the PASI is relatively robust, and produces reliable results even as the system is degraded by the loss of data. Eighteen actively fished sites and 11 sites that are closed to fishing are assessed to evaluate how well the PASI is able to distinguish differences between sites. The estimated scores are significantly different (p<0.05), whereby non-fished sites are scored as being more suitable for protection than fished sites. The PASI can be used as a decision support tool to facilitate systematic marine spatial management under data poor conditions, especially in the task of identifying suitable sites for protection.     

Spatial patterns of sub-tidal seagrasses and their tissue nutrients in the Torres Strait,northern Australia: Implications for management

The distribution and nutritional profiles of sub-tidal seagrasses from the Torres Strait were surveyed and mapped across an area of 31,000 km². Benthic sediment composition, water depth, seagrass species type and nutrients were sampled at 168 points selected in a stratified representative pattern. Eleven species of seagrass were present at 56 (33.3%) of the sample points. Halophila spinulosa, Halophila ovalis, Cymodocea serrulata and Syringodium isoetifolium were the most common species and these were nutrient profiled. Sub-tidal seagrass distribution (and associated seagrass nutrient concentrations) was generally confined to northern-central and south-western regions of the survey area (<longitude 142.60), where mean water depth was relatively shallow (approximately 13 m below MSL) and where sediments were comprised primarily muddy sand to gravelly sand. Seagrass nitrogen and starch content, the most important nutrients for marine herbivores, were significantly correlated with species and with the plant component (above or below ground). For all seagrass species, the above-ground component (shoots and leaves) possessed greater nitrogen concentrations than the below-ground component (roots and rhizomes), which possessed greater starch concentrations. S. isoetifolium had the highest total nitrogen concentrations (1.40±0.05% DW). However, it also had higher fibre concentrations (38.2±0.68% DW) relative to the other four species. H. ovalis possessed the highest starch concentrations (2.76±0.12% DW) and highest digestibility (83.24±0.66% DW) as well as the lowest fibre (27.2±0.66% DW). The high relative abundance (found at 55% of the sites that had seagrass) and nutrient quality characteristics of H. ovalis make it an important source of energy to marine herbivores that forage sub-tidally in the Torres Strait. There were two regions in Torres Strait (north-central and south-western) where sub-tidal seagrass meadows were prevalent and of relatively higher nutritional value. This spatial and nutritional information can be used by local agencies to manage and to protect the ecological, economic and cultural values of the sub-tidal seagrass ecosystems and associated fisheries of the Torres Strait.     

On the correlation of certain lower Dalradian successions in northwest Donegal

Within the Dalradian Series of Donegal, the Creeslough, Maas and Fintown successions, which have hitherto been regarded as stratigraphically distinct, are correlated. A standard terminology for this sequence is proposed and a detailed correlation is made with the Ballachulish Succession, which thus forms all the country around the Donegal Granites, northwest of the faults and thrusts which separate it from the Islay Succession.     

CryoSheds: a GIS modeling framework for delineating land-ice watersheds for the Greenland Ice Sheet

Choice of watershed delineation technique is an important source of uncertainty for cryo-hydrologic studies of the Greenland Ice Sheet (GrIS), with different methods yielding different watersheds for a common pour point. First, this paper explores this uncertainty for the Akuliarusiarsuup Kuua River Northern Tributary, Western Greenland. Next, a standardized, semi-automated modeling framework for generating land-ice watersheds for GrIS land-terminating ice (henceforth referred to as CryoSheds) using geographic information systems (GIS) hydrologic modeling tools is presented. The framework uses ArcGIS and the ArcPy geoprocessing library to delineate two types of land-ice watersheds, namely those defined by: (1) a hydraulic pressure potential with varying water to ice overburden pressure ratios (k-value), which determines theoretical flow paths from the hydrostatic equation, using surface and bedrock digital elevation models (DEMs) and (2) a surface topography DEM alone. Lastly, a demonstration of the CryoSheds method is presented for seven remotely sensed proglacial pour points along the Aussivigssuit River (AR), Western Greenland, and its largest tributaries. GrIS meltwater runoff from these seven nested land-ice watersheds is estimated using Modele Atmospherique Regional (MAR) v.3.2 and runoff uncertainties due to watershed delineation parameter selection is estimated.     

Saldanha Bay,South Africa II: estimating bay productivity

Saldanha Bay is a narrow-mouth bay on the west coast of South Africa linked to the southern Benguela upwelling system. Bay productivity was investigated by use of the conventional light-and-dark bottle oxygen method, and, for comparison, through assimilation of the stable isotope tracer ¹³C. Gross community production GCP and net community production NCP, as determined from the oxygen method, were respectively 2.6 and 2.4 times higher than estimates determined from the stable isotope method. Chlorophyll a (Chl a) concentrations increased with the onset of spring and well-defined subsurface maxima developed in association with increasingly stratified conditions (mean water column Chl a concentrations ranged from 5.4 to 31.5?mg m^?3 [mean 15.5?mg m^?3; SD 7.6]). A sharp decline in photosynthetic rates P* (GCP normalised to Chl a concentration) with depth was attributed to light limitation, as demonstrated by the high vertical attenuation coefficients for downward irradiance K_d, which varied from 0.29 to 0.70?m^?1 (mean 0.48?m^?1; SD 0.12). Productivity maxima were consequently near-surface despite the presence of deeper subsurface biomass maxima. The community compensation depth Z_cc, where gross community production balances respiratory carbon loss for the entire community, ranged from 2.9 to 9.2?m (mean 5.8?m; SD 2.2), and was typically shallower than the 1% light depth for PAR (photosynthetically available radiation), Z1%PAR, which is traditionally assumed to be the depth of the euphotic zone and which ranged from 6.6 to 15.9?m (mean 9?m; SD 2.6). Autotrophic communities, where organic matter is produced in excess of respiratory demand, were confined on average to the upper 5.8?m of the water column, and often excluded the bulk of the phytoplankton community, where light limitation is considered to lead to heterotrophic community metabolism. Estimates of integrated water column productivity ranged from 0.84 to 8.46?g C m–2 d^?1 (mean 3.35?g C m^?2 d^?1; SD 1.9).     

A population health model for integrated assessment models

In this paper we present the initial results from a project to develop a population health model so we can extend the scenarios included in the IPCC’s Special Report on Emission Scenarios to include population health status. Our initial hypothesis was that some climatic variable, particularly temperature, would have a significant impact on health outcomes. After experiments – using the Global Burden of Disease (GBD) data on Years of Life Lost (YLL) and Years Lived with disability (YLD) both by WHO region and by five degree latitude band as outcome variables – failed, we settled on life expectancy (LE) as the best measure of health status. We discovered that there is a solid relationship between LE and the GBD data from our first experiments, allowing us to extend the results from the LE model. The LE model used cross section data on LE for 91 countries and included temperature, per capita income, access to clean water and sanitation, literacy, simple medical attention, nutrition, per capita medical expenditure, electricity use per capita, and automobiles per capita as independent variables. While all were individually associated with LE, our model of choice included literacy, access to clean water and sanitation, simple medical attention, an indictor variable for Sub-Saharan Africa and purchasing-power parity per capita income. Note that neither temperature nor calories enter into this model. The fit between life expectancy, as predicted by this model, and actual life expectancy was quite good (R ² =0.90), except for Rwanda, Uganda, and Madagascar; these countries accounted for one half of the unexplained variation in the model. The LE model was then used to develop trajectories of life expectancy in India for the four IPCC SRES storylines, where values for the independent variables were extrapolated based on the story line content. YLL and YLD estimates were created using the current cross relationship of these outcomes to LE. Given the lack of a general role for climate in our LE model, future work is planned to explore how to add detailed climate related impacts, to explore alternative nutritional variables, as well as extend the data set to allow a cross-section time-series approach.     

Fisheries: Hope or despair?

Recent work suggesting that fisheries depletions have turned the corner is misplaced because analysis was based largely on fisheries from better-managed developed-world fisheries. Some indicators of status show improvements in the minority of fisheries subjected to formal assessment. Other indicators, such as trophic level and catch time series, have been controversial. Nevertheless, several deeper analyses of the status of the majority of world fisheries confirm the previous dismal picture: serious depletions are the norm world-wide, management quality is poor, catch per effort is still declining. The performance of stock assessment itself may stand challenged by random environmental shifts and by the need to accommodate ecosystem-level effects. The global picture for further fisheries species extinctions, the degradation of ecosystem food webs and seafood security is indeed alarming. Moreover, marine ecosystems and their embedded fisheries are challenged in parallel by climate change, acidification, metabolic disruptors and other pollutants. Attempts to remedy the situation need to be urgent, focused, innovative and global.