Imperfectly optimal animals

Summary We consider models of behavior that apply to two different problems: when a predator should leave a foraging site and how a female should choose the best available male. In each case we derive rules for an optimal solution to the problem. We also derive models based on very simple, plausible rules of behavior that we suspect animals may actually use. Although the expected payoffs from optimality models always exceed the expected payoffs from our simpler behavioral models, under certain conditions the difference is not large. When good foraging sites last but a short time and when females' mobility in their habitat is limited, the results of simple models and optimal models are very close indeed.Because of the difficulty of distinguishing between the results of each type of model and because natural selection will presumably provide a best mix of solutions to a range of problems rather than a best solution to any one problem, we suggest that behavioral ecologists expend more effort on simple, plausible models of animal behavior. Such models provide ready-made testable hypotheses about the animal's approximation to optimality and about the actual mechanisms of behavior.     

Human preferences for facial masculinity change with relationship type and environmental harshness

In humans (Homo sapiens), sexual dimorphism in face shape has been proposed to be linked to quality in both men and women. Although preferences for high-quality mates might be expected, previous work has suggested that high quality may be associated with decreased investment in partnerships. In line with a trade-off between partner quality and investment, human females have been found to prefer higher levels of masculinity when judging under conditions where the benefits of quality would be maximised and the costs of low investment would be minimised. In this study, we examined facultative preferences for masculinity/femininity under hypothetical high and low environmental harshness in terms of resource availability in which participants were asked to imagine themselves in harsh/safe environments. We demonstrate that environmental harshness influences preferences for sexual dimorphism differently according to whether the relationship is likely to be short or long term. Women prefer less-masculine male faces and men prefer less-feminine female faces for long-term than short-term relationships under conditions of environmental harshness. Such findings are consistent with the idea that high-quality partners may be low investors and suggest that under harsh ecological conditions, both men and women favour a low-quality/high-investment partner for long-term relationships. For short-term relationships, where investment is not an important variable, preferences for sexual dimorphism were similar for the low and high environmental harshness conditions. These results provide experimental evidence that human preferences may be contingent on the environment an individual finds itself inhabiting.     

Estimating the abundance of mouse populations of known size: promises and pitfalls of new methods.

Knowledge of animal abundance is fundamental to many ecological studies. Frequently, researchers cannot determine true abundance, and so must estimate it using a method such as mark-recapture or distance sampling. Recent advances in abundance estimation allow one to model heterogeneity with individual covariates or mixture distributions and to derive multimodel abundance estimators that explicitly address uncertainty about which model parameterization best represents truth. Further, it is possible to borrow information on detection probability across several populations when data are sparse. While promising, these methods have not been evaluated using mark-recapture data from populations of known abundance, and thus far have largely been overlooked by ecologists. In this paper, we explored the utility of newly developed mark-recapture methods for estimating the abundance of 12 captive populations of wild house mice (Mus musculus). We found that mark-recapture methods employing individual covariates yielded satisfactory abundance estimates for most populations. In contrast, model sets with heterogeneity formulations consisting solely of mixture distributions did not perform well for several of the populations. We show through simulation that a higher number of trapping occasions would have been necessary to achieve good estimator performance in this case. Finally, we show that simultaneous analysis of data from low abundance populations can yield viable abundance estimates.     

Urea Fluctuations in Stream Baseflow across Land Cover Gradients and Seasons in a Coastal Plain River System

Urea‐N is a component of bioavailable dissolved organic nitrogen (DON) that contributes to coastal eutrophication. In this study, we assessed urea‐N in baseflow across land cover gradients and seasons in the Manokin River Basin on the Delmarva Peninsula. From March 2010 to June 2011, we conducted monthly sampling of 11 streams (4 tidal and 7 nontidal), 2 wastewater treatment plants, an agricultural drainage ditch, and groundwater underlying a cropped field. At each site, we measured urea‐N, DON, dissolved organic carbon (DOC), total dissolved nitrogen (TDN), NO₃^?‐N, and NH₄⁺‐N. In general, urea‐N comprised between 1% and 6% of TDN, with the highest urea‐N levels in drainage ditches (0.054 mg N/L) and wetland‐dominated streams (0.035–0.045 mg N/L). While urea‐N did not vary seasonally in tidal rivers, nontidal streams saw distinct urea‐N peaks in summer (0.038 mg N/L) that occurred several months after cropland fertilization in spring. Notably, the proportion of wetlands explained 78% of the variance in baseflow urea‐N levels across the Manokin watershed. In wetland‐dominated basins, we found urea‐N was positively related to water temperature and negatively related to DOC:DON ratios, indicating short‐term urea‐N dynamics at baseflow were more likely influenced by instream and wetland‐driven processes than by recent agricultural urea‐N inputs. Findings demonstrate important controls of wetlands on baseflow urea‐N concentrations in mixed land‐use basins.     

Potential Impacts of Highway Median Barriers on Wildlife: State of the Practice and Gap Analysis

Median barriers separate lanes of traffic moving in opposite directions on multilane highways. Such traffic safety devices can reduce head-on collisions but also have the potential to reduce landscape permeability by impeding wildlife movements across highways. Median barriers may also increase the risk of wildlife–vehicle collisions if an animal becomes trapped or confused amid barriers searching for a place to cross. A 2002 Transportation Research Board report highlighted the need to better understand the potential impacts of highway median barriers on wildlife. This lack of information can cause significant project delays and increase transportation project costs. This study represents the first attempt in North America to bring together information about highway median and roadside barriers and wildlife and provide preliminary guidelines to balance the needs of motorist safety and wildlife movements.     

Physicochemical quality of an urban municipal wastewater effluent and its impact on the receiving environment

The physicochemical qualities of the final effluents of an urban wastewater treatment plant in South Africa were assessed between August 2007 and July 2008 as well as their impact on the receiving watershed. The pH values across all sampling points ranged between 6.8 and 8.3, while the temperature varied from 18°C to 25°C. Electrical conductivity (EC) of the samples was in the range of 29–1,015 μS/cm, and turbidity varied between 2.7 and 35 NTU. Salinity and total dissolved solids (TDS) varied from 0.36 to 35 psu and 16 to 470 mg/L, respectively. The concentrations of the other physicochemical parameters are as follows: chemical oxygen demand (COD, 48–1,180 mg/L); dissolved oxygen (DO, 3.9–6.6 mg/L); nitrate (0.32–6.5 mg NO $_{3}^{-}$ as N/L); nitrite (0.06–2.4 mg NO $_{2}^{-}$ as N/L); and phosphate (0.29–0.54 mg PO $_{4}^{3-}$ as P/L). pH, temperature, EC, turbidity, TDS, DO, and nitrate varied significantly with season and sampling point (P?<?0.05 and P?<?0.01, respectively), while salinity varied significantly with sampling point (P?<?0.01) and COD and nitrite varied significantly with season (P?<?0.05). Although the treated effluent fell within the recommended water quality standard for pH temperature, TDS, nitrate and nitrite, it fell short of stipulated standards for other parameters. The result generally showed a negative impact of the discharged effluent on the receiving watershed and calls for a regular and consistent monitoring program by the relevant authorities to ensure best practices with regard to treatment and discharge of wastewater into the receiving aquatic milieu in South Africa.     

Effect of Classification Procedure on the Performance of Numerically Defined Ecological Regions

Ecological regionalizations define geographic regions exhibiting relative homogeneity in ecological (i.e., environmental and biotic) characteristics. Multivariate clustering methods have been used to define ecological regions based on subjectively chosen environmental variables. We developed and tested three procedures for defining ecological regions based on spatial modeling of a multivariate target pattern that is represented by compositional dissimilarities between locations (e.g., taxonomic dissimilarities). The procedures use a “training dataset” representing the target pattern and models this as a function of environmental variables. The model is then extrapolated to the entire domain of interest. Environmental data for our analysis were drawn from a 400 m grid covering all of Switzerland and consisted of 12 variables describing climate, topography and lithology. Our target patterns comprised land cover composition of each grid cell that was derived from interpretation of aerial photographs. For Regionalization 1 we used conventional cluster analysis of the environmental variables to define 60 hierarchically organized levels comprising from 5 to 300 regions. Regionalization 1 provided a base-case for comparison with the model-based regionalizations. Regionalization 2, 3 and 4 also comprised 60 hierarchically organized levels and were derived by modeling land cover composition for 4000 randomly selected “training” cells. Regionalization 2 was based on cluster analysis of environmental variables that were transformed based on a Generalized Dissimilarity Model (GDM). Regionalization 3 and 4 were defined by clustering the training cells based on their land cover composition followed by predictive modeling of the distribution of the land cover clusters using Classification and Regression Tree (CART) and Random Forest (RF) models. Independent test data (i.e. not used to train the models) were used to test the discrimination of land cover composition at all hierarchical levels of the regionalizations using the classification strength (CS) statistic. CS for all the model-based regionalizations was significantly higher than for Regionalization 1. Regionalization 3 and 4 performed significantly better than Regionalization 2 at finer hierarchical levels (many regions) and Regionalization 4 performed significantly better than Regionalization 3 for coarse levels of detail (few regions). Compositional modeling can significantly increase the performance of numerically defined ecological regionalizations. CART and RF-based models appear to produce stronger regionalizations because discriminating variables are able to change at each hierarchic level.     

Effects of a chelating resin on metal bioavailability and toxicity to estuarine invertebrates: Divergent results of field and laboratory tests

Benthic invertebrates can uptake metals through diffusion of free ion solutes, or ingestion of sediment-bound forms. This study investigated the efficacy of the metal chelating resin SIR 300™ in adsorbing porewater metals and isolating pathways of metal exposure. A field experiment (Botany Bay, Sydney, Australia) and a laboratory toxicity test each manipulated the availability of porewater metals within contaminated and uncontaminated sediments. It was predicted that within contaminated sediments, the resin would adsorb porewater metals and reduce toxicity to invertebrates, but in uncontaminated sediments, the resin would not significantly affect these variables. Whereas in the laboratory, the resin produced the predicted results, in the field the resin increased porewater metal concentrations of contaminated sediments for at least 34 days and decreased abundances of four macroinvertebrate groups, and richness in all sediments. These contrasting findings highlight the limits of extrapolating the results of laboratory experiments to the field environment.     

A conceptual framework for analyzing deltas as coupled social–ecological systems: an example from the Amazon River Delta

At the nexus of watersheds, land, coastal areas, oceans, and human settlements, river delta regions pose specific challenges to environmental governance and sustainability. Using the Amazon Estuary-Delta region (AD) as our focus, we reflect on the challenges created by the high degree of functional interdependencies shaping social–ecological dynamics of delta regions. The article introduces the initial design of a conceptual framework to analyze delta regions as coupled social–ecological systems (SES). The first part of the framework is used to define a delta SES according to a problem and/or collective action dilemma. Five components can be used to define a delta SES: social–economic systems, governance systems, ecosystems-resource systems, topographic-hydrological systems, and oceanic-climate systems. These components are used in association with six types of telecoupling conditions: socio-demographic, economic, governance, ecological, material, and climatic-hydrological. The second part of the framework presents a strategy for the analysis of collective action problems in delta regions, from sub-delta/local to delta to basin levels. This framework is intended to support both case studies and comparative analysis. The article provides illustrative applications of the framework to the AD. First, we apply the framework to define and characterize the AD as coupled SES. We then utilize the framework to diagnose an example of collective action problem related to the impacts of urban growth, and urban and industrial pollution on small-scale fishing resources. We argue that the functional interdependencies characteristic of delta regions require new approaches to understand, diagnose, and evaluate the current and future impacts of social–ecological changes and potential solutions to the sustainability dilemmas of delta regions.