EVALUATION OF COASTAL PLAIN CONSERVATION BUFFERS USING THE RIPARIAN ECOSYSTEM MANAGEMENT MODEL1

ABSTRACT: Riparian buffers are increasingly important as watershed management tools and are cost‐shared by programs such as Conservation Reserve that are part of the USDA Conservation Buffer Initiative. Riparian buffers as narrow as 4.6m (15ft) are eligible for cost‐share by USDA. The Riparian Ecosystem Management Model (REMM) provides a tool to judge water quality improvement by buffers and to set design criteria for nutrient and sediment load reduction. REMM was used for a Coastal Plain site to simulate 14 different buffers ranging from 4.6 m to 51.8 m (15 to 170 ft) with three different types of vegetation (hardwood trees, pine trees, and perennial grass) with two water and nutrient loads. The load cases were low sediment/low nutrient‐typical of a well managed agricultural field and low sediment/high nutrient‐typical of liquid manure application to perennial forage crops. Simulations showed that the minimum width buffer (4.6 m) was inadequate for control of nutrients under either load case. The minimum width buffer that is eligible for cost share assistance on a field with known water quality problems (10.7 m, 35 ft) was projected to achieve at least 50 percent reduction of N, P, and sediment in the load cases simulated.     

The potential for citizen science to produce reliable and useful information in ecology

We examined features of citizen science that influence data quality, inferential power, and usefulness in ecology. As background context for our examination, we considered topics such as ecological sampling (probability based, purposive, opportunistic), linkage between sampling technique and statistical inference (design based, model based), and scientific paradigms (confirmatory, exploratory). We distinguished several types of citizen science investigations, from intensive research with rigorous protocols targeting clearly articulated questions to mass-participation internet-based projects with opportunistic data collection lacking sampling design, and examined overarching objectives, design, analysis, volunteer training, and performance. We identified key features that influence data quality: project objectives, design and analysis, and volunteer training and performance. Projects with good designs, trained volunteers, and professional oversight can meet statistical criteria to produce high-quality data with strong inferential power and therefore are well suited for ecological research objectives. Projects with opportunistic data collection, little or no sampling design, and minimal volunteer training are better suited for general objectives related to public education or data exploration because reliable statistical estimation can be difficult or impossible. In some cases, statistically robust analytical methods, external data, or both may increase the inferential power of certain opportunistically collected data. Ecological management, especially by government agencies, frequently requires data suitable for reliable inference. With standardized protocols, state-of-the-art analytical methods, and well-supervised programs, citizen science can make valuable contributions to conservation by increasing the scope of species monitoring efforts. Data quality can be improved by adhering to basic principles of data collection and analysis, designing studies to provide the data quality required, and including suitable statistical expertise, thereby strengthening the science aspect of citizen science and enhancing acceptance by the scientific community and decision makers.     

Re-creating missing population baselines for Pacific reef sharks

Sharks and other large predators are scarce on most coral reefs, but studies of their historical ecology provide qualitative evidence that predators were once numerous in these ecosystems. Quantifying density of sharks in the absence of humans (baseline) is, however, hindered by a paucity of pertinent time-series data. Recently researchers have used underwater visual surveys, primarily of limited spatial extent or nonstandard design, to infer negative associations between reef shark abundance and human populations. We analyzed data from 1607 towed-diver surveys (>1 ha transects surveyed by observers towed behind a boat) conducted at 46 reefs in the central-western Pacific Ocean, reefs that included some of the world's most pristine coral reefs. Estimates of shark density from towed-diver surveys were substantially lower (<10%) than published estimates from surveys along small transects (<0.02 ha), which is not consistent with inverted biomass pyramids (predator biomass greater than prey biomass) reported by other researchers for pristine reefs. We examined the relation between the density of reef sharks observed in towed-diver surveys and human population in models that accounted for the influence of oceanic primary productivity, sea surface temperature, reef area, and reef physical complexity. We used these models to estimate the density of sharks in the absence of humans. Densities of gray reef sharks (Carcharhinus amblyrhynchos), whitetip reef sharks (Triaenodon obesus), and the group "all reef sharks" increased substantially as human population decreased and as primary productivity and minimum sea surface temperature (or reef area, which was highly correlated with temperature) increased. Simulated baseline densities of reef sharks under the absence of humans were 1.1-2.4/ha for the main Hawaiian Islands, 1.2-2.4/ha for inhabited islands of American Samoa, and 0.9-2.1/ha for inhabited islands in the Mariana Archipelago, which suggests that density of reef sharks has declined to 3-10% of baseline levels in these areas.     

Effect of heavy metals (Hg and Zn) on the growth and phosphate solubilising activity in halophilic phosphobacteria isolated from Manakudi mangrove

The diversity of phosphobacteria in Manakudi mangrove ecosystem of Tamil Nadu was carried out in root and rhizosphere soil samples. The counts of phosphobacteria were found higher in root samples than in soil samples particularly in Hymenachene acutigluma. The abundance of phosphobacterial diversity in Manakudi mangrove showed high degree of positive correlation with the content of phosphate in rhizosphere soil of all the mangrove and associated plant species. Nine phosphobacterial species belonging to 7 genera were reported from Manakudi mangrove ecosystem. All the identified bacterial species are sensitive to both the heavy metals (mercury and zinc) in terms of growth and physiology even at lower concentrations. The content of protein and total sugars were increased by the higher concentrations of heavy metals whereas decreased trend was noticed in lower concentrations of heavy metals.     

Selecting pseudo-absence data for presence-only distribution modeling: How far should you stray from what you know?

An important decision in presence-only species distribution modeling is how to select background (or pseudo-absence) localities for model parameterization. The selection of such localities may influence model parameterization and thus, can influence the appropriateness and accuracy of the model prediction when extrapolating the species distribution across time and space. We used 12 species from the Australian Wet Tropics (AWT) to evaluate the relationship between the geographic extent from which pseudo-absences are taken and model performance, and shape and importance of predictor variables using the MAXENT modeling method. Model performance is lower when pseudo-absence points are taken from either a restricted or broad region with respect to species occurrence data than from an intermediate region. Furthermore, variable importance (i.e., contribution to the model) changed such that, models became increasingly simplified, dominated by just two variables, as the area from which pseudo-absence points were drawn increased. Our results suggest that it is important to consider the spatial extent from which pseudo-absence data are taken. We suggest species distribution modeling exercises should begin with exploratory analyses evaluating what extent might provide both the most accurate results and biologically meaningful fit between species occurrence and predictor variables. This is especially important when modeling across space or time—a growing application for species distributional modeling.     

Comparison of natural organic acids and synthetic chelates at enhancing phytoextraction of metals from a multi-metal contaminated soil

Chemically assisted phytoremediation has been developing to induce accumulation of metals by high biomass plants. Synthetic chelates have shown high effectiveness to reach such a goal, but they pose serious drawbacks in field application due to the excessive amount of metals solubilized. We compared the performance of synthetic chelates with naturally occurring low molecular weight organic acids (LMWOA) in enhancing phytoextraction of metals by Indian mustard (Brassica juncea) from multi-metal contaminated soils. Gallic and citric acids were able to induce removal of Cd, Zn, Cu, and Ni from soil without increasing the leaching risk. Net removal of these metals caused by LMWOA can be as much as synthetic chelates. A major reason for this is the lower phytotoxicity of LMWOA. Furthermore, supplying appropriate mineral nutrients increased biomass and metal removal.