Risk assessment in western mosquitofish (Gambusia affinis): do multiple cues have additive effects?

The threat-sensitivity hypothesis predicts that prey individuals will increase antipredator behaviors as apparent predator risk increases. An implicit assumption of the threat-sensitivity hypothesis is that predator risk is additive. In other words, all characteristics of a predator that indicate risk should contribute in an additive way to determine the degree of risk-sensitive behavior. We tested this assumption in the laboratory by presenting live predators (green sunfish, Lepomis cyanellus) to groups of western mosquitofish (Gambusia affinis). We examined effects of predator diet, hunger level, and size on predator avoidance and inspection behavior of mosquitofish. Both predator diet and predator hunger level were significant and additive determinants of distance maintained from a predator, resulting in a graded response to combinations of these predator cues. In contrast, whereas predator diet was the most important determinant of general avoidance distances, predator hunger level was more important in determining mosquitofish vertical distribution and inspection behavior. Thus, the relationship between predator cue and the antipredator behavior that it elicits is dependent on which cues and behaviors are examined. Our data suggest that during risky behaviors, such as predator inspection, mosquitofish rely mainly on visual cues (behavior differences between hungry and satiated predators), whereas general avoidance behavior is determined by additive responses from visual and chemical cues.     

Extended alloparental care in the almost solitary bee Exoneurella eremophila (Hymenoptera: Apidae)

The possibility of extending brood care via the overlapping presence of relatively short lived adults could generate advantages that may have been among the selective forces at the origin of eusociality. In this paper we provide evidence for extended brood care through sib-rearing in the arid-zone allodapine bee, Exoneurella eremophila. Solitary females of the overwintered generation generally die before all their offspring have become independent. In a relatively high proportion of nests, a newly eclosed female invests in her siblings while producing her own offspring in the maternal nest. The sex ratio of the first offspring produced by the overwintered female is highly female biased, but the overall sex ratio of the brood is unbiased. This finding supports the prediction of Bull's 'insurance by protogyny' model of a female bias in the first-produced offspring as a strategy by the mother to ensure extended brood care.     

环境基质中药物残留的固相提取与分析

废水流出物常常不可避免地进入地表水和用于饮用水资源的含水层．因废水再循环常常进入饮用水层,各种废水中的污染物最终会污染饮用水．以往环保部门一直比较注重农药和工业污染物,但最近的研究发现:废水流出物中的某些药物残留已达到了相当令人关注(１μｇ·１－１即ｐｐｂ)的程度．传统的分析技术(如液液萃取和ＧＣ/ＭＳ) 对极性较弱的化合物(ＰＣＢｓ和许多农药)比较有效,但对于极性相对较强的药物污染物而言,固相提取(ＳＰＥ)与ＬＣ/ＭＳ技术更适合于样品提取分析。     

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.     

Advantages of Geographically Weighted Regression for Modeling Benthic Substrate in Two Greater Yellowstone Ecosystem Streams

Stream habitat assessments are commonplace in fish management, and often involve nonspatial analysis methods for quantifying or predicting habitat, such as ordinary least squares regression (OLS). Spatial relationships, however, often exist among stream habitat variables. For example, water depth, water velocity, and benthic substrate sizes within streams are often spatially correlated and may exhibit spatial nonstationarity or inconsistency in geographic space. Thus, analysis methods should address spatial relationships within habitat datasets. In this study, OLS and a recently developed method, geographically weighted regression (GWR), were used to model benthic substrate from water depth and water velocity data at two stream sites within the Greater Yellowstone Ecosystem. For data collection, each site was represented by a grid of 0.1 m² cells, where actual values of water depth, water velocity, and benthic substrate class were measured for each cell. Accuracies of regressed substrate class data by OLS and GWR methods were calculated by comparing maps, parameter estimates, and determination coefficient r ². For analysis of data from both sites, Akaike’s Information Criterion corrected for sample size indicated the best approximating model for the data resulted from GWR and not from OLS. Adjusted r ² values also supported GWR as a better approach than OLS for prediction of substrate. This study supports GWR (a spatial analysis approach) over nonspatial OLS methods for prediction of habitat for stream habitat assessments.     

The distribution and extent of heavy metal accumulation in song sparrows along Arizona’s upper Santa Cruz River

Heavy metals are persistent environmental contaminants, and transport of metals into the environment poses a threat to ecosystems, as plants and wildlife are susceptible to long-term exposure, bioaccumulation, and potential toxicity. We investigated the distribution and cascading extent of heavy metal accumulation in southwestern song sparrows (Melospiza melodia fallax), a resident riparian bird species that occurs along the US/Mexico border in Arizona’s upper Santa Cruz River watershed. This study had three goals: (1) quantify the degree of heavy metal accumulation in sparrows and determine the distributional patterns among study sites, (2) compare concentrations of metals found in this study to those found in studies performed prior to a 2009 international wastewater facility upgrade, and (3) assess the condition of song sparrows among sites with differing potential levels of exposure. We examined five study sites along with a reference site that reflect different potential sources of contamination. Body mass residuals and leukocyte counts were used to assess sparrow condition. Birds at our study sites typically had higher metal concentrations than birds at the reference site. Copper, mercury, nickel, and selenium in song sparrows did exceed background levels, although most metals were below background concentrations determined from previous studies. Song sparrows generally showed lower heavy metal concentrations compared to studies conducted prior to the 2009 wastewater facility upgrade. We found no cascading effects as a result of metal exposure.     

Assessment of long-term wastewater irrigation impacts on the soil geochemical properties and the bioaccumulation of heavy metals to the agricultural products

An extensive field survey was employed for assessing the impacts of long-term wastewater irrigation of forage crops and orange orchards in three suburban agricultural areas in Cyprus (areas I, II, and III), as compared to rainfed agriculture, on the soil geochemical properties and the bioaccumulation of heavy metals (Zn, Ni, Mn, Cu, Co) to the agricultural products. Both ryegrass fields and orange orchards in areas I and II were continuously wastewater irrigated for 10 years, whereas clover fields in area III for 0.5, 4, and 8 years. The results revealed that wastewater reuse for irrigation caused a slight increase in soil salinity and Cl^? content in areas I and II, and a remarkable increase, having strong correlation with the period in which wastewater irrigation was practiced, in area III. Soil salinization in area III was due to the high electrical conductivity (EC) of the wastewater applied for irrigation, attributed to the influx of seawater to the sewage collection network in area III. In addition, the wastewater irrigation practice resulted in a slight decrease of the soil pH values in area III, while a subtle impact was identified regarding the CaCO₃, Fe, and heavy metal content in the three areas surveyed. The heavy metal content quantified in the forage plants’ above-ground parts was below the critical levels of phytotoxicity and the maximum acceptable concentration in dairy feed, whereas heavy metals quantified in orange fruit pulp were below the maximum permissible levels (MPLs). Heavy metal phytoavailability was confined due to soil properties (high pH and clay content), as evidenced by the calculated low transfer factor (TF).