Non-target Impacts to Eelgrass from Treatments to Control Spartina in Willapa Bay, Washington

Four methods to control the smooth cordgrass Spartina (Spartina alterniflora) and the footwear worn by treatment personnelat several sites in Willapa Bay, Washington were evaluatedto determine the non-target impacts to eelgrass (Zostera japonica). Clone-sized infestations of Spartina were treated bymowing or a single hand-spray application of Rodeo® formulatedat 480 g L-1acid equivalence (ae) of the isopropylaminesalt of glyphosate (Monsanto Agricultural Co., St. Louis, MO;currently Dow AgroSciences, Indianapolis, IN) with the nonionic surfactant LI 700® (2% v/v) or a combination of mowing and hand spraying. An aerial application of Rodeo® with X-77 Spreader® (0.13% v/v) to a 2-ha meadow was also investigated. Monitoring consisted of measuring eelgrass shoot densities and percent cover pre-treatment and 1-yr post-treatment. Impacts to eelgrass adjacent to treated clones were determined 1 m from the clones and compared to a control 5-m away. Impacts from footwear were assessed at 5 equidistant intervals along a 10-m transect on mudflat and an untreated control transect at each of the three clone treatment sites. Impacts from the aerial application were determined by comparing shoot densities and percent cover 1, 3 and 10 m from the edge of the treated Spartina meadow to that at comparable distances from an untreated meadow. Methods utilized to control Spartina clones did not impact surrounding eelgrass at two of three sites. Decreases in shoot densities observed at the third site were consistent across treatments. Most impacts to eelgrass from the footwear worn by treatment personnel were negligible and those that were significant were limited to soft mud substrate. The aerial application of the herbicide was associated with reductions in eelgrass (shoot density and percent cover) at two of the three sampling distances, but reductions on the control plot were greater. We conclude that the unchecked spread of Spartina is a far greater threat to the survival and health of eelgrass than that from any of the control measures we studied. The basis for evaluating control measures for Spartina should be efficacy and logistical constraints and not impacts to eelgrass. PDF is 7 pages.

From fossil molluscs to salmon

On 9 April 1897 Wilfrid Hudleston, an eminent geologist, purchased the West Holme Estate, comprising some 1500 acres on the edge of the Isle of Purbeck in Dorset, where he could enjoy his sporting interest in shooting and fishing. In doing so, he established a link between himself, The Malacological Society of London, and the Freshwater Biological Association. Hudleston was a keen field geologist who built up a personal collection of several thousand fossils. In 1893 Hudleston took the chair at a meeting, held at the Natural History Museum, which founded The Malacological Society of London. The site on which the Freshwater Biological Association's River Laboratory now stands was formerly part of the West Holme Estate. It purchased the fishing rights to the East Stoke mill stream prior to building the laboratory, in 1957.

Rapid changes in the vegetation of a shallow pond in Epping Forest, related to recent droughts

Over much of Britain, 1995 and 1996 have been perceived as drought years. To evaluate the impact that local climatic conditions are having upon successional changes in higher vegetation (macrophytes), Speakmans Pond in Epping Forest was surveyed and mapped in 1996. The results are related to previous vegetation surveys carried out in 1989 and 1991. In 1989 the dominant marginal vegetation was floating sweet-grass Glyceria fluitans, which also covered a major part of the main body of the pond. Other abundant species included soft rush Juncus effusus, reed mace Typha latifolia and yellow flag Iris pseudocorus. A small (central) area of open water contained bladderwort Utricularia vulgaris and white water-lily Nymphaea alba. A similar plant coverage was found in 1991, with a dominance of floating sweet-grass along the shallow eastern edge. A marked change in the pond was found during the 1996 survey of vegetation in July, when the pool was dry. The major plant cover now consisted of creeping bent Agrostis stolonifera, with isolated clumps of Yorkshire fog Holcus lanatus around the edges; both are terrestrial grasses found on land surrounding the pond. Rushes (Juncus) had increased their distribution round the margins of the pond, and the patch of yellow flag noted in 1989 and 1991 was not found in 1996. The deeper trenches were also dry, but a small patch of white water-lily remained adjacent to one of the trenches.

Littoral vegetation of Lake Tohopekaliga: community descriptions prior to a large-scale fisheries habitat-enhancement project

An extreme dry-down and muck-removal project was conducted at Lake Tohopekaliga, Florida, in 2003-2004, to remove dense vegetation from inshore areas and improve habitat degraded by stabilized water levels. Vegetation was monitored from June 2002 to December 2003, to describe the pre-existing communities in terms of composition and distribution along the environmental gradients. Three study areas (Treatment-Selection Sites) were designed to test the efficacy of different treatments in enhancing inshore habitat, and five other study areas (Whole-Lake Monitoring Sites) were designed to monitor the responses of the emergent littoral vegetation as a whole. Five general community types were identified within the study areas by recording aboveground biomasses and stem densities of each species. These communities were distributed along water and soils gradients, with water depth and bulk density explaining most of the variation. The shallowest depths were dominated by a combination of Eleocharis spp., Luziola fluitans, and Panicum repens; while the deeper areas had communities of Nymphaea odorata and Nuphar luteum; Typha spp.; or Paspalidium geminatum and Hydrilla verticillata. Mineralized soils were common in both the shallow and deep-water communities, while the intermediate depths had high percentages of organic material in the soil. These intermediate depths (occurring just above and just below low pool stage) were dominated by Pontederia cordata, the main species targeted by the habitat enhancement project. This emergent community occurred in nearly monocultural bands around the lake (from roughly 60–120 cm in depth at high pool stage) often having more diverse floating mats along the deep-water edge. The organic barrier these mats create is believed to impede access of sport fish to shallow-water spawning areas, while the overall low diversity of the community is evidence of its competitive nature in stabilized waters. With continued monitoring of these study areas long-term effects of the restoration project can be assessed and predictive models may be created to determine the efficacy and legitimacy of such projects in the future.

Mapping reef fish and the seascape: using acoustics and spatial modeling to guide coastal management

Reef fish distributions are patchy in time and space with some coral reef habitats supporting higher densities (i.e., aggregations) of fish than others. Identifying and quantifying fish aggregations (particularly during spawning events) are often top priorities for coastal managers. However, the rapid mapping of these aggregations using conventional survey methods (e.g., non-technical SCUBA diving and remotely operated cameras) are limited by depth, visibility and time. Acoustic sensors (i.e., splitbeam and multibeam echosounders) are not constrained by these same limitations, and were used to concurrently map and quantify the location, density and size of reef fish along with seafloor structure in two, separate locations in the U.S. Virgin Islands. Reef fish aggregations were documented along the shelf edge, an ecologically important ecotone in the region. Fish were grouped into three classes according to body size, and relationships with the benthic seascape were modeled in one area using Boosted Regression Trees. These models were validated in a second area to test their predictive performance in locations where fish have not been mapped. Models predicting the density of large fish (≥29 cm) performed well (i.e., AUC = 0.77). Water depth and standard deviation of depth were the most influential predictors at two spatial scales (100 and 300 m). Models of small (≤11 cm) and medium (12–28 cm) fish performed poorly (i.e., AUC = 0.49 to 0.68) due to the high prevalence (45–79%) of smaller fish in both locations, and the unequal prevalence of smaller fish in the training and validation areas. Integrating acoustic sensors with spatial modeling offers a new and reliable approach to rapidly identify fish aggregations and to predict the density large fish in un-surveyed locations. This integrative approach will help coastal managers to prioritize sites, and focus their limited resources on areas that may be of higher conservation value.

A habitat-use model to determine essential fish habitat for juvenile brown shrimp (Farfantepenaeus aztecus) in Galveston Bay, Texas

A density prediction model for juvenile brown shrimp (Farfantepenaeus aztecus) was developed by using three bottom types, five salinity zones, and four seasons to quantify patterns of habitat use in Galveston Bay, Texas. Sixteen years of quantitative density data were used. Bottom types were vegetated marsh edge, submerged aquatic vegetation, and shallow nonvegetated bottom. Multiple regression was used to develop density estimates, and the resultant formula was then coupled with a geographical information system (GIS) to provide a spatial mosaic (map) of predicted habitat use. Results indicated that juvenile brown shrimp (<100 mm) selected vegetated habitats in salinities of 15−25 ppt and that seagrasses were selected over marsh edge where they co-occurred. Our results provide a spatially resolved estimate of high-density areas that will help designate essential fish habitat (EFH) in Galveston Bay. In addition, using this modeling technique, we were able to provide an estimate of the overall population of juvenile brown shrimp (<100 mm) in shallow water habitats within the bay of approximately 1.3 billion. Furthermore, the geographic range of the model was assessed by plotting observed (actual) versus expected (model) brown shrimp densities in three other Texas bays. Similar habitat-use patterns were observed in all three bays—each having a coefficient of determination >0.50. These results indicate that this model may have a broader geographic application and is a plausible approach in refining current EFH designations for all Gulf of Mexico estuaries with similar geomorphological and hydrological characteristics.