Shunning the night to elude the hunter: diurnal fireflies and the “femmes fatales”

Summary. Lucidota atra, a diurnal firefly, shares possession of defensive steroids (lucibufagins or LBGs) with nocturnal fireflies of the genus Photinus. Photinus are protected against predators by their LBGs, but not against fireflies of the genus Photuris, the so-called firefly femmes fatales, which prey upon Photinus, thereby acquiring LBGs for their own defense. We propose that L. atra may have been prompted evolutionarily to become diurnal by the opportunity to avoid, thereby, being hunted by Photuris. Indeed, L. atra, if offered to Photuris, were eagerly devoured by the latter, which sequestered their LBG’s. In feeding on L. atra, Photuris may be driven by a gustatory affinity for LBGs. Persistent nocturnality might therefore have put L. atra at risk vis à vis Photuris. Diurnality freed the firefly from that risk, without compromising its defended status with respect to other predators. Possession of LBGs may in fact account for L. atra’s unacceptability to birds and spiders.     

Spatial statistical models that use flow and stream distance

We develop spatial statistical models for stream networks that can estimate relationships between a response variable and other covariates, make predictions at unsampled locations, and predict an average or total for a stream or a stream segment. There have been very few attempts to develop valid spatial covariance models that incorporate flow, stream distance, or both. The application of typical spatial autocovariance functions based on Euclidean distance, such as the spherical covariance model, are not valid when using stream distance. In this paper we develop a large class of valid models that incorporate flow and stream distance by using spatial moving averages. These methods integrate a moving average function, or kernel, against a white noise process. By running the moving average function upstream from a location, we develop models that use flow, and by construction they are valid models based on stream distance. We show that with proper weighting, many of the usual spatial models based on Euclidean distance have a counterpart for stream networks. Using sulfate concentrations from an example data set, the Maryland Biological Stream Survey (MBSS), we show that models using flow may be more appropriate than models that only use stream distance. For the MBSS data set, we use restricted maximum likelihood to fit a valid covariance matrix that uses flow and stream distance, and then we use this covariance matrix to estimate fixed effects and make kriging and block kriging predictions. Received: July 2005 / Revised: March 2006     

Rank differences in energy intake rates in white-faced capuchin monkeys, Cebus capucinus: the effects of contest competition

The effect of aggressive competition over food resources on energy intake rate is analyzed for individuals of three groups of 25–35 white-faced capuchin monkeys, Cebus capucinus, living in and near Lomas Barbudal Biological Reserve, Costa Rica. An individuals energy intake rate on a given food species was affected by its rank and the number of agonistic interactions within the feeding tree. Dominant group members had higher energy intake rates relative to subordinate group members whether or not there was agonism within the feeding tree. Low- and mid-ranked individuals had lower energy intake rates in trees with higher amounts of aggression, while energy intake rate of high-ranked individuals was not affected by the amount of aggression in the feeding tree. Energy intake was not influenced by the sex of the individual when rank was held constant statistically. Energy intake was positively correlated with total crown energy (measured in kilojoules) within the feeding tree for two of three study groups. This difference may be explained by the quality of each groups territory. Finally, high-ranked individuals are responsible for the majority of agonism within feeding trees and target middle- and low-ranked individuals equally. These findings fit the predictions of current socioecological models for within-group contest competition over food resources. The results of this study suggest that within-group competition affects energy intake rate in white-faced capuchin monkeys.     

Beyond opportunity costs: who bears the implementation costs of reducing emissions from deforestation and degradation?

Reducing Emissions from Deforestation and Degradation (REDD+) in developing countries is based on the premise that conserving tropical forests is a cost-effective way to reduce carbon emissions and therefore can be fully funded by international actors with obligations or interests in reducing emissions. However, concerns have repeatedly been raised about whether stakeholders in REDD+ host countries will actually end up bearing the costs of REDD+. Most prior analyses of the costs of REDD+ have focused on the opportunity costs of foregone alternative uses of forest land. We draw on a pan-tropical study of 22 subnational REDD+ initiatives in five countries to explore patterns in implementation costs, including which types of organizations are involved and which are sharing the costs of implementing REDD+. We find that many organizations involved in the implementation of REDD+, particularly at the subnational level and in the public sector, are bearing implementation costs not covered by the budgets of the REDD+ initiatives. To sustain this level of cost-sharing, REDD+ must be designed to deliver local as well as global forest benefits.     

Stable isotopes provide new insights into vestimentiferan physiological ecology at Gulf of Mexico cold seeps

On the otherwise low-biomass seafloor of the Gulf of Mexico (GoM) continental slope, natural oil and gas seeps are oases of local primary production that support lush animal communities. Hundreds of seep communities have been documented on the continental slope, and nutrition derived from seeps could be an important link in the overall GoM food web. Here, we present a uniquely large and cohesive data set of δ(13)C, δ(15)N, and δ(34)S compositions of the vestimentiferan tubeworms Escarpia laminata and Lamellibrachia sp. 1, which dominate biomass at GoM seeps and provide habitat for hundreds of other species. Our sampling design encompassed an entire region of the GoM lower slope, allowing us for the first time to assess spatial variability in isotope compositions and to robustly address long-standing hypotheses about how vestimentiferans acquire and cycle nutrients over their long lifespan (200+?years). Tissue δ(13)C values provided strong evidence that larger adult vestimentiferans use their buried roots to take up dissolved inorganic carbon from sediment pore water, while very small individuals use their plume to take up carbon dioxide from the seawater. δ(34)S values were extremely variable among individuals of the same species within one location (<1?m(2) area), indicating high variability in the inorganic sulfur pools on a very small spatial scale. This finding supports the hypothesis that vestimentiferans use their roots to cycle sulfate and sulfide between their symbionts and free-living consortia of sulfate-reducing archaea in the sediment. Finally, consistent differences in δ(15)N between two cooccurring vestimentiferan species provided the first strong evidence for partitioning of inorganic resources, which has significant implications for the ecology and evolution of this taxonomic group.     

SCRAM: A scoring and ranking system for persistent, bioaccumulative, and toxic substances for the North American Great Lakes

Hundreds of chemical contaminants have been identified in the Great Lakes System of North America. Depending on the agency or organization, various subset lists of these contaminants have been identified as chemicals of potential concern. However, there is no agreement on the method that should be used to make management decisions. Except for consensus on approximately 40 chemicals that most North American agencies agree can cause deleterious effects if released into the environment, no agreement has been reached regarding the priority that contaminants should receive for further action. That leaves hundreds of chemicals that have been, are being, or potentially could be released into the environment that have not been evaluated yet. A profile for potential chemicals of concern is generally thought to include persistence in the environment, potential to bioaccumulate, and ability to cause toxic effects at environmentally relevant concentrations. Except for the International Joint Commission’s definition of persistence (> 8 weeks residence time in air, water, soil or sediment), there is little concurrence about what defines these characteristics. For instance, the State of Michigan currently has no established definitions or profiles of persistent, bioaccumulative, toxic substances. Furthermore, there is no standard process to rank chemicals relative to these characteristics. The Chemical Scoring and Ranking Assessment Model (SCRAM) has been developed to provide a process to rank-order chemicals based on these characteristics. The SCRAM system was developed primarily for use in the Great Lakes region of North America and particularly in Michigan, but it is not site-specific. Use of this system may assist in pollution prevention activities and other future chemical control efforts, allowing attention to be focused first on those chemicals likely to present the greatest hazard.     

Patterns of Spatial Autocorrelation in Stream Water Chemistry

Geostatistical models are typically based on symmetric straight-line distance, which fails to represent the spatial configuration, connectivity, directionality, and relative position of sites in a stream network. Freshwater ecologists have explored spatial patterns in stream networks using hydrologic distance measures and new geostatistical methodologies have recently been developed that enable directional hydrologic distance measures to be considered. The purpose of this study was to quantify patterns of spatial correlation in stream water chemistry using three distance measures: straight-line distance, symmetric hydrologic distance, and weighted asymmetric hydrologic distance. We used a dataset collected in Maryland, USA to develop both general linear models and geostatistical models (based on the three distance measures) for acid neutralizing capacity, conductivity, pH, nitrate, sulfate, temperature, dissolved oxygen, and dissolved organic carbon. The spatial AICC methodology allowed us to fit the autocorrelation and covariate parameters simultaneously and to select the model with the most support in the data. We used the universal kriging algorithm to generate geostatistical model predictions. We found that spatial correlation exists in stream chemistry data at a relatively coarse scale and that geostatistical models consistently improved the accuracy of model predictions. More than one distance measure performed well for most chemical response variables, but straight-line distance appears to be the most suitable distance measure for regional geostatistical modeling. It may be necessary to develop new survey designs that more fully capture spatial correlation at a variety of scales to improve the use of weighted asymmetric hydrologic distance measures in regional geostatistical models.     

Near-field loading dynamics of total phosphorus and short-term water quality variations at a rainbow trout cage farm in Lake Huron

Aquatic total phosphorus (Tot-P) is measured at fish-cages in Lake Huron for environmental regulatory compliance. An improved understanding of how Tot-P is manifested in the near-field (相似文献