Effect of hyposalinity on the photophysiology of <Emphasis Type="Italic">Siderastrea radians</Emphasis>

Tolerance to hyposalinity of the scleractinian coral S. radians was examined in a mesocosm study. Colonies of S. radians were collected from five basins in Florida Bay, USA, which occur along a northeast-to-southwest salinity gradient. Salinity treatments were based on historical salinity records for these basins. Photophysiology of the endosymbiont Symbiodinium spp. (maximum quantum yield; F _v/F _m) was measured as an indicator of holobiont stress to hyposalinity. Colonies from each basin were assigned four salinity treatments [The Practical Salinity Scale (PSS) was used to determine salinity. Units are not assigned to salinity values because it is a ratio and has no unit as defined by UNESCO (UNESCO Technical papers no. 45, IAPSO Pub. Sci. No. 32, Paris, France, 1985)] (30, 20, 15, and 10) and salinities were reduced 2 per day from ambient (30) to simulate a natural salinity decrease. Colonies treated with salinities of 20 and 15 showed no decrease in F _v/F _m versus controls (i.e. 30), up to 5 days after reaching their target salinity. This indicates a greater ability to withstand reduced salinity for relatively extended periods of time in S. radians compared to other reef species. Within 1 day after salinity of 10 was reached, there was a significant reduction in F _v/F _m, indicating a critical threshold for hyposaline tolerance. At the lowest treatment salinity (10), F _v/F _m for the more estuarine, northeast-basin colonies were significantly higher than the most marine southwest-basin colonies (Twin Key Basin). Our results suggest that historical salinity ranges within basins determine coral population salinity tolerances.     

Formulation and testing of a novel river nitrification model

The nitrification process in many river water quality models has been approximated by a simple first order dependency on the water column ammonia concentration, while the benthic contribution has routinely been neglected. In this study a mathematical framework was developed for sediment bed nitrification based on mass transfer theory and Monod bacterial growth kinetics. The model describes ammonia transport across the boundary layer and consumption within the biofilm to quantify the overall nitrification flux. Model results suggest that nitrification is usually controlled by the boundary layer thickness, and we estimated a nitrification velocity range between 0.14 and 0.97 m d⁻¹, assuming typical boundary thicknesses of 0.1–1.0 mm. These ranges compared favorably with reported literature values, including our own measurements. The model was applied to several river systems of different depths where nitrification rates and river depths were available. Assuming that nitrification is exclusively a benthic process, the average velocity of all the rivers evaluated was 0.85 m d⁻¹ (r² = 0.72).     

A spatial model of white sturgeon rearing habitat in the lower Columbia River,USA

Concerns over the potential effects of in-water placement of dredged materials prompted us to develop a GIS-based model that characterizes in a spatially explicit manner white sturgeon Acipenser transmontanus rearing habitat in the lower Columbia River, USA. The spatial model was developed using water depth, riverbed slope and roughness, fish positions collected in 2002, and Mahalanobis distance (D²). We created a habitat suitability map by identifying a Mahalanobis distance under which >50% of white sturgeon locations occurred in 2002 (i.e., high-probability habitat). White sturgeon preferred relatively moderate to high water depths, and low to moderate riverbed slope and roughness values. The eigenvectors indicated that riverbed slope and roughness were slightly more important than water depth, but all three variables were important. We estimated the impacts that fill might have on sturgeon habitat by simulating the addition of fill to the thalweg, in 3-m increments, and recomputing Mahalanobis distances. Channel filling simulations revealed that up to 9 m of fill would have little impact on high-probability habitat, but 12 and 15 m of fill resulted in habitat declines of ∼12% and ∼45%, respectively. This is the first spatially explicit predictive model of white sturgeon rearing habitat in the lower Columbia River, and the first to quantitatively predict the impacts of dredging operations on sturgeon habitat. Future research should consider whether water velocity improves the accuracy and specificity of the model, and to assess its applicability to other areas in the Columbia River.     

Social network analysis and valid Markov chain Monte Carlo tests of null models

Analyses of animal social networks derived from group-based associations often rely on randomisation methods developed in ecology (Manly, Ecology 76:1109–1115, 1995) and made available to the animal behaviour community through implementation of a pair-wise swapping algorithm by Bejder et al. (Anim Behav 56:719–725, 1998). We report a correctable flaw in this method and point the reader to a wider literature on the subject of null models in the ecology literature. We illustrate the importance of correcting the method using a toy network and use it to make a preliminary analysis of a network of associations among eagle rays.

Animal social networks: an introduction

Network analysis has a long history in the mathematical and social sciences and the aim of this introduction is to provide a brief overview of the potential that it holds for the study of animal behaviour. One of the most attractive features of the network paradigm is that it provides a single conceptual framework with which we can study the social organisation of animals at all levels (individual, dyad, group, population) and for all types of interaction (aggressive, cooperative, sexual etc.). Graphical tools allow a visual inspection of networks which often helps inspire ideas for testable hypotheses. Network analysis itself provides a multitude of novel statistical tools that can be used to characterise social patterns in animal populations. Among the important insights that networks have facilitated is that indirect social connections matter. Interactions between individuals generate a social environment at the population level which in turn selects for behavioural strategies at the individual level. A social network is often a perfect means by which to represent heterogeneous relationships in a population. Probing the biological drivers for these heterogeneities, often as a function of time, forms the basis of many of the current uses of network analysis in the behavioural sciences. This special issue on social networks brings together a diverse group of practitioners whose study systems range from social insects over reptiles to birds, cetaceans, ungulates and primates in order to illustrate the wide-ranging applications of network analysis. This contribution is part of the special issue “Social Networks: new perspectives” (Guest Editors: J. Krause, D. Lusseau and R. James).     

Coregionalization analysis with a drift for multi-scale assessment of spatial relationships between ecological variables 1. Estimation of drift and random components

In two articles, we present ‘coregionalization analysis with a drift’ (CRAD), a method to assess the multi-scale variability of and relationships between ecological variables from a multivariate spatial data set. In phase I of CRAD (the first article), a deterministic drift component representing the large-scale pattern and a random component modeled as a second-order stationary process are estimated for each variable separately. In phase II (this article), a linear model of coregionalization (LMC) is fitted by estimated generalized least squares to the direct and cross experimental variograms of residuals (i.e., after the removal of estimated drifts). Structural correlations and coefficients of determination at smaller scales are then computed from the estimated coregionalization matrices, while the estimated drifts are used to calculate pseudo coefficients at large scale. The performance of five procedures in estimating correlations and coefficients of determination was compared using a Monte Carlo study. In four CRAD procedures, drift estimation was based on local polynomials of order 0, 1, 2 (L₀, L₁, L₂) or a global polynomial with forward selection of the basis functions; the fifth procedure was coregionalization analysis (CRA), in which large-scale patterns were modeled as a supplemental component in the LMC. In bivariate and multivariate analyses, the uncertainty in the estimation of correlations and coefficients of determination could be related to the interference between spatial components within a bounded sampling domain. In the bivariate case, most procedures provided acceptable estimates of correlations. In regionalized redundancy analysis, uncertainty was highest for CRA, while L₁ provided the best results overall. In a forest ecology example, the identification of scale-specific correlations between plant species diversity and soil and topographical variables illustrated the potential of CRAD to provide unique insight into the functioning of complex ecosystems.     

Seasonal changes in movements and habitat preferences of the scalloped hammerhead shark (Sphyrna lewini) while refuging near an oceanic island

Movements and habitat preferences of sharks relative to a central location are widely documented for many species; however, the reasons for such behaviors are currently unknown. Do movements vary spatially or temporally or between individuals? Do sharks have seasonal habitat and environmental preferences or simply perform movements at random at any time of the year? To help understand requirements for the designation of critical habitats for an endangered top predator and to develop zoning and management plans for key habitats, we examined vertical and horizontal movements, and determined habitat and environmental preferences of scalloped hammerhead sharks (Sphyrna lewini). We tracked seven hammerheads for 19–96 h at Wolf Island (1.38ºN, 91.82ºW) between 2007 and 2009 using ultrasonic transmitters with depth and temperature sensors, and we profiled temperature through the water column. Movements of individual hammerheads fell in two classes: constrained (remaining near the island) and dispersive (moving offshore to pelagic environments). The central activity space or kernel off the southeast side of Wolf Island was small and common to most, but the area varied among individuals (mean ± SE 0.25 ± 0.2 km²), not exceeding 0.6 km² for any of the sharks, and not changing significantly between seasons. In general, hammerheads showed preference for the up-current habitat on the eastern side of Wolf Island in both the warm and cold seasons. However, the depth of sharks varied with season, apparently in response to seasonal changes in the vertical structure of temperature. Hammerheads performed frequent vertical excursions above the thermocline during offshore movements and, in general, were observed to prefer temperatures of 23–26 °C found above the thermocline. At times, though individuals moved into the thermocline and made brief dives below it. Our results provided evidence that hammerheads (1) are highly selective of location (i.e., habitat on up-current side of island) and depth (i.e., top of the thermocline) while refuging, where they may carry out essential activities such as cleaning and thermoregulation, and (2) perform exploratory vertical movements by diving the width of the mixed layer and occasionally diving below the thermocline while moving offshore, most likely for foraging.     

Growth response of an early successional assemblage of coralline algae and benthic diatoms to ocean acidification

The sustained absorption of anthropogenically released atmospheric CO₂ by the oceans is modifying seawater carbonate chemistry, a process termed ocean acidification (OA). By the year 2100, the worst case scenario is a decline in the average oceanic surface seawater pH by 0.3 units to 7.75. The changing seawater carbonate chemistry is predicted to negatively affect many marine species, particularly calcifying organisms such as coralline algae, while species such as diatoms and fleshy seaweed are predicted to be little affected or may even benefit from OA. It has been hypothesized in previous work that the direct negative effects imposed on coralline algae, and the direct positive effects on fleshy seaweeds and diatoms under a future high CO₂ ocean could result in a reduced ability of corallines to compete with diatoms and fleshy seaweed for space in the future. In a 6-week laboratory experiment, we examined the effect of pH 7.60 (pH predicted to occur due to ocean acidification just beyond the year 2100) compared to pH 8.05 (present day) on the lateral growth rates of an early successional, cold-temperate species assemblage dominated by crustose coralline algae and benthic diatoms. Crustose coralline algae and benthic diatoms maintained positive growth rates in both pH treatments. The growth rates of coralline algae were three times lower at pH 7.60, and a non-significant decline in diatom growth meant that proportions of the two functional groups remained similar over the course of the experiment. Our results do not support our hypothesis that benthic diatoms will outcompete crustose coralline algae under future pH conditions. However, while crustose coralline algae were able to maintain their presence in this benthic rocky reef species assemblage, the reduced growth rates suggest that they will be less capable of recolonizing after disturbance events, which could result in reduced coralline cover under OA conditions.     

Price controls and banking in emissions trading: An experimental evaluation

We present results from laboratory emissions markets designed to investigate the effects of price controls and permit banking on limiting permit price risk. While both instruments reduce between-period price volatility and within-period price dispersion, combining price controls and permit banking yields important benefits. Banking alone produces high permit prices in earlier periods that fall over time, but the combined policy produces lower initial prices and lower volatility. However, banking, price controls, and the combination all produce higher between-period emissions volatility. Hence, for emissions markets that seek to control flow pollutants with strictly convex damages, efforts to limit permit price risk can result in higher expected damage.     

A new meta-analysis on the WTP/WTA disparity

This study reports a new meta-analysis of papers that elicit willingness-to-pay (WTP) and willingness-to-accept compensation (WTA) measures of value for the same good. We investigate the effects of type of good and several survey-design features on the WTP/WTA disparity, measured as the logarithm of the ratio of mean WTA to mean WTP. Confirming Horowitz and McConnell?s (2002) pioneering meta-analysis, we find the disparity is smaller for ordinary private goods than for public and non-market goods, that it is not solely an artifact of using hypothetical transactions or other weak experimental or survey methods, and that it is smaller for studies using student subjects. In addition, we find that the disparity is smaller when subjects have experience valuing the good in real markets or through repeated experimental trials. In contrast to Horowitz and McConnell, we find the disparity is significantly smaller in studies using incentive-compatible elicitation mechanisms. The disparity is smaller in more recent studies, an effect that is attributable only in part to changes in study characteristics.