Species Distribution Models of Freshwater Stream Fishes in Maryland and Their Implications for Management

Species distribution models (SDMs) are often used in conservation planning, but their utility can be improved by assessing the relationships between environmental and species response variables. We constructed SDMs for 30 stream fishes of Maryland, USA, using watershed attributes as environmental variables and presence/absence as species responses. SDMs showed substantial agreement between observed and predicted values for 17 species. Most important variables were natural attributes (e.g., ecoregion, watershed area, latitude/longitude); land cover (e.g., %impervious, %row crop) was important for three species. Focused analyses on four representative species (central stoneroller, creek chub, largemouth bass, and white sucker) showed the probability of presence of each species increased non-linearly with watershed area. For these species, SDMs built to predict absent, low, and high densities were similar to presence/absence predictions but provided probable locations of high densities (e.g., probability of high-density creek chub decreased rapidly with watershed area). We applied SDMs to predict suitability of watersheds within the study area for each species. Maps of suitability and the environmental and species response relationships can help develop better management plans.     

Evaluation of concentration efficiency of the Pseudomonas aeruginosa phage PP7 in various water matrixes by different methods

Enteric viruses monitoring in surface waters requires the concentration of viruses before detection assays. The aim of this study was to evaluate different methods in terms of recovery efficiencies of bacteriophage PP7 of Pseudomonas aeruginosa, measured by real-time PCR, using it as a viral control process in water analysis. Different nucleic acid extraction methods (silica–guanidinium thiocyanate, a commercial kit (Qiagen Viral RNA Kit) and phenol–chloroform with alcohol precipitation) exhibited very low recovery efficiencies (0.08–4.18 %), being the most efficient the commercial kit used for subsequent experiments. To evaluate the efficiency of three concentration methods, PBS (as model for clean water) and water samples from rivers were seeded to reach high (HC, 10⁶ pfu ml^?1) and low concentrations (LC, 10⁴ pfu ml^?1) of PP7. Tangential ultrafiltration proved to be more efficient (50.36?±?12.91, 17.21?±?9.22 and 12.58?±?2.35 % for HC in PBS and two river samples, respectively) than adsorption–elution with negatively charged membranes (1.00?±?1.34, 2.79?±?2.62 and 0.05?±?0.08 % for HC in PBS and two river samples, respectively) and polyethylene glycol precipitation (15.95?±?7.43, 4.01?±?1.12 and 3.91?±?0.54 %, for HC in PBS and two river samples, respectively), being 3.2–50.4 times more efficient than the others for PBS and 2.7–252 times for river samples. Efficiencies also depended on the initial virus concentration and aqueous matrixes composition. In consequence, the incorporation of an internal standard like PP7 along the process is useful as a control of the water concentration procedure, the nucleic acid extraction, the presence of inhibitors and the variability of the recovery among replicas, and for the calculation of the sample limit of detection. Thus, the use of a process control, as presented here, is crucial for the accurate quantification of viral contamination.     

Predicting System-Scale Impacts of Oyster Clearance on Phytoplankton Productivity in a Small Subtropical Estuary

Oyster populations in south Florida estuaries have declined in part through altered salinity driven by anthropogenic changes in freshwater inputs. In particular, the St. Lucie Estuary (SLE) in southeastern Florida has suffered widespread loss of oyster habitat. With efforts underway to improve water quality and oyster habitat in the SLE, the goal of this study was to develop a model to assess ecosystem level impacts of oyster restoration. Phytoplankton and oyster biomass modeling targets were established from observational data collected from 2005 to 2009. Modeled oyster biomass production and filtration fluctuated with temperature, salinity, and total suspended solids from a combination of observational and predicted input functions in 10-year simulations (1998–2007). Model estimates of oyster biomass fluctuated with salinity from near zero after extreme freshwater discharge in 2002–2003 and 2004–2005 to maximum values near 150.0 and 200.0 g?C?m^?2 in spring 1999 and fall 2006. There was potential for algal blooms as turnover time for the phytoplankton standing stock (15.6 days) was faster than water mass turnover (21.0 days). While >1,000 days were required for 50 ha of oyster habitat to filter the entire volume of the estuarine segment, filter time reduced to <20 days with an estimated fivefold increase in net consumption of phytoplankton if the oyster habitat was increased to 300 ha. Re-establishment of biologically desirable salinity envelopes would stabilize oyster survival allowing the possibility for successful habitat restoration to benefit water quality and faunal attributes of the St. Lucie Estuary.     

Climate anomalies, Indonesian vegetation fires and terrestrial carbon emissions

There was a widespread misconception about the causes of vegetation and land fires in Indonesia. At a certain point, the public perceived that fires and the associated haze pollution were primarily caused by smallholders' agricultural activities. In fact, there was a variety of land-use activities including large-scale land clearing following deforestation for further land development. El Niño events and the associated dry weather were sometimes quoted by officials and the media as the cause of fires. The fire episodes from 1980 to 2000 were analysed in connection with climate anomalies and the implementation of land-use policies related to forest conversions. The analysis employs long-term climatic and sea surface temperature data to reconstruct climate distributions and anomalies including Southern Oscillation Index (SOI), Sea Surface Temperature (SST) and Outgoing Long-wave Radiation (OLR). In this study, the terrestrial carbon emissions from vegetation fires were estimated based on official statistical data on area burnt. The possible incentives for sustainable land management were discussed in the light of fire prevention. The underlying cause neglected in the discussion of Indonesian vegetation fires was forest and land development policy. Legitimated in the early 1980s, it drove massive forest conversions and the use of fires for land clearing. El Niño Southern Oscillation (ENSO) provided dry weather suitable for biomass burning and widespread fire, but it was hardly the cause of fires. The estimate of area burnt in the big fires in 1997 was about 11.6 Mha, resulting in carbon release of 1.45 Gt, equivalent to 0.73 ppmv of CO₂, or almost half the annual global atmospheric CO₂ growth. Based on the current carbon market price such emissions by the 1997 fire episode were worth around US$ 3.6 billion.     

Simulation of soil loss processes based on rainfall runoff and the time factor of governance in the Jialing River Watershed,China

Jialing River is the largest tributary in the catchment area of Three Gorges Reservoir, and it is also one of the important areas of sediment yield in the upper reaches of the Yangtze River. In recent years, significant changes of water and sediment characteristics have taken place. The "Long Control" Project implemented since 1989 had greatly changed the surface appearance of the Jialing River Watershed (JRW), and it had made the environments of the watershed sediment yield and sediment transport change significantly. In this research, the Revised Universal Soil Loss Equation was selected and used to predict the annual average amount of soil erosion for the special water and sediment environments in the JRW after the implementation of the "Long Control" Project, and then the rainfall–runoff modulus and the time factor of governance were both considered as dynamic factors, the dynamic sediment transport model was built for soil erosion monitoring and forecasting based on the average sediment yield model. According to the dynamic model, the spatial and temporal distribution of soil erosion amount and sediment transport amount of the JRW from 1990 to 2007 was simulated using geographic information system (GIS) technology and space-grid algorithm. Simulation results showed that the average relative error of sediment transport was less than 10% except for the extreme hydrological year. The relationship between water and sediment from 1990 to 2007 showed that sediment interception effects of the soil and water conservation projects were obvious: the annual average sediment discharge reduced from 145.3 to 35 million tons, the decrement of sediment amount was about 111 million tons, and decreasing amplitude was 76%; the sediment concentration was also decreased from 2.01 to 0.578 kg/m³. These data are of great significance for the prediction and estimation of the future changing trends of sediment storage in the Three Gorges Reservoir and the particulate non-point source pollution load carried by sediment transport from watershed surface.     

Assessment of Spatiotemporal Varying Relationships Between Rainfall,Land Cover and Surface Water Area Using Geographically Weighted Regression

Traditional regression techniques such as ordinary least squares (OLS) are often unable to accurately model spatially varying data and may ignore or hide local variations in model coefficients. A relatively new technique, geographically weighted regression (GWR) has been shown to greatly improve model performance compared to OLS in terms of higher R ² and lower corrected Akaike information criterion (AIC_C). GWR models have the potential to improve reliabilities of the identified relationships by reducing spatial autocorrelations and by accounting for local variations and spatial non-stationarity between dependent and independent variables. In this study, GWR was used to examine the relationship between land cover, rainfall and surface water habitat in 149 sub-catchments in a predominately agricultural region covering 2.6 million ha in southeast Australia. The application of the GWR models revealed that the relationships between land cover, rainfall and surface water habitat display significant spatial non-stationarity. GWR showed improvements over analogous OLS models in terms of higher R ² and lower AIC_C. The increased explanatory power of GWR was confirmed by the results of an approximate likelihood ratio test, which showed statistically significant improvements over analogous OLS models. The models suggest that the amount of surface water area in the landscape is related to anthropogenic drainage practices enhancing runoff to facilitate intensive agriculture and increased plantation forestry. However, with some key variables not present in our analysis, the strength of this relationship could not be qualified. GWR techniques have the potential to serve as a useful tool for environmental research and management across a broad range of scales for the investigation of spatially varying relationships.     

A moving target—incorporating knowledge of the spatial ecology of fish into the assessment and management of freshwater fish populations

Freshwater fish move vertically and horizontally through the aquatic landscape for a variety of reasons, such as to find and exploit patchy resources or to locate essential habitats (e.g., for spawning). Inherent challenges exist with the assessment of fish populations because they are moving targets. We submit that quantifying and describing the spatial ecology of fish and their habitat is an important component of freshwater fishery assessment and management. With a growing number of tools available for studying the spatial ecology of fishes (e.g., telemetry, population genetics, hydroacoustics, otolith microchemistry, stable isotope analysis), new knowledge can now be generated and incorporated into biological assessment and fishery management. For example, knowing when, where, and how to deploy assessment gears is essential to inform, refine, or calibrate assessment protocols. Such information is also useful for quantifying or avoiding bycatch of imperiled species. Knowledge of habitat connectivity and usage can identify critically important migration corridors and habitats and can be used to improve our understanding of variables that influence spatial structuring of fish populations. Similarly, demographic processes are partly driven by the behavior of fish and mediated by environmental drivers. Information on these processes is critical to the development and application of realistic population dynamics models. Collectively, biological assessment, when informed by knowledge of spatial ecology, can provide managers with the ability to understand how and when fish and their habitats may be exposed to different threats. Naturally, this knowledge helps to better evaluate or develop strategies to protect the long-term viability of fishery production. Failure to understand the spatial ecology of fishes and to incorporate spatiotemporal data can bias population assessments and forecasts and potentially lead to ineffective or counterproductive management actions.     

Modeling Large Fire Frequency and Burned Area in Canadian Terrestrial Ecosystems with Poisson Models

Large wildland fires are major disturbances that strongly influence the carbon cycling and vegetation dynamics of Canadian boreal ecosystems. Although large wildland fires have recently received much scrutiny in scientific study, it is still a challenge for researchers to predict large fire frequency and burned area. Here, we use monthly climate and elevation data to quantify the frequency of large fires using a Poisson model, and we calculate the probability of burned area exceeding a certain size using a compound Poisson process. We find that the Poisson model simulates large fire occurrence well during the fire season (May through August) using monthly climate, and the threshold probability calculated by the compound Poisson model agrees well with historical records. Threshold probabilities are significantly different among different Canadian ecozones, with the Boreal Shield ecozone always showing the highest probability. The fire prediction model described in this study and the derived information will facilitate future quantification of fire risks and help improve fire management in the region.     

Cytogenetic biomonitoring of oral mucosa cells of crack cocaine users

The aim of the present study was to comparatively evaluate genomic damage (micronucleus) and cellular death (pyknosis, karyolysis, and karyorrhexis) in exfoliated oral mucosa cells from crack cocaine users by micronucleus test. A total of 30 crack cocaine users and 30 health controls (non-exposed individuals) were included in this setting. Individuals had epithelial cells from cheek mechanically exfoliated, placed in fixative, and dropped in clean slides, which were checked for the above nuclear phenotypes. The results pointed out significant statistical differences (p?<?0.05) of micronucleated oral mucosa cells from crack cocaine users. Exposure to crack cocaine caused an increase of other nuclear alterations closely related to cytotoxicity such as karyolysis in oral cells as well. In summary, these data indicate that crack cocaine is able to induce chromosomal breakage and cellular death in oral mucosa cells of users.