The impact of behavioral and physiological maternal effects on offspring sex ratio in the common snapping turtle,<Emphasis Type="Italic"> Chelydra serpentina</Emphasis>

Theory suggests that maternal effects are especially important in organisms with environmentally-sensitive sex-determining mechanisms. However, there is no substantive body of empirical evidence to confirm this conjecture. We integrated field and laboratory studies to jointly evaluate the significance of behavioral (nest-site choice) and physiological (yolk hormone allocation) maternal effects on offspring sex ratio in the common snapping turtle (Chelydra serpentina), a species with temperature-dependent sex determination (TSD). Of the 16 microhabitat variables measured, only three (south, east, and total overstory vegetation cover) were significantly correlated with nest temperature: cooler nests were located under more vegetation cover. In turn, these microhabitat predictors of nest temperature, and nest temperature itself, may influence nest sex ratio: shadier, cooler nests were more likely to produce a higher proportion of male offspring than less shady, warmer nests. Analysis of eggs from these same nests incubated in a common garden design in the laboratory revealed that clutch sex ratio was unaffected by levels of yolk estradiol, yolk testosterone, or their interaction. Examination of both behavioral and physiological maternal effects revealed no concordant impact on offspring sex ratio. However, eggs from nests that produced male-biased sex ratios in the field yielded higher proportions of males under constant-temperature conditions in the laboratory. Our study confirms the importance of behavioral maternal effects in nature on offspring sex ratios in species with TSD, while also revealing the potential presence of a predisposition for sex-ratio production underlying TSD in this system.Communicated by S. Krackow     

Eggshell colour does not predict measures of maternal investment in eggs of <Emphasis Type="Italic">Turdus</Emphasis> thrushes

The striking diversity of avian eggshell colour has long fascinated biologists. Recently, it has been proposed that the blue-green colour of some eggs may function as a post-mating sexually selected signal of female phenotypic quality to their mates to induce higher allocation of paternal care. It has been suggested that maternally deposited yolk carotenoids may be the specific aspect of reproductive quality that the female is signalling via eggshell colour. We use the known properties of the thrush visual system (Turdus sp.) to calculate photon capture for the four single cone photoreceptors, and the principal member of the double cone class for eggs in clutches of two introduced European thrush species (Turdus merula and Turdus philomelos) in New Zealand. We show that differences in the avian-perceived colours of individual eggs are not consistently correlated with different measures of maternal investment in the egg. Given the growing extent of the knowledge between maternal quality, parental investment and eggshell pigmentation across avian taxa, we encourage the use of avian perceptual modelling for testing alternative non-signalling explanations for the structural and physiological basis of these relationships.     

Spatial attributes and reserve design models: A review

A variety of decision models have been formulated for the optimal selection of nature reserve sites to represent a diversity of species or other conservation features. Unfortunately, many of these models tend to select scattered sites and do not take into account important spatial attributes such as reserve shape and connectivity. These attributes are likely to affect not only the persistence of species but also the general ecological functioning of reserves and the ability to effectively manage them. In response, researchers have begun formulating reserve design models that improve spatial coherence by controlling spatial attributes. We review the spatial attributes that are thought to be important in reserve design and also review reserve design models that incorporate one or more of these attributes. Spatial modeling issues, computational issues, and the trade-offs among competing optimization objectives are discussed. Directions for future research are identified. Ultimately, an argument is made for the development of models that capture the dynamic interdependencies among sites and species populations and thus incorporate the reasons why spatial attributes are important.     

Optimisation of sampling for the temporal monitoring of technetium-99 in the Arctic marine environment

Monitoring of the marine environment for radioactivity, for both radiological protection and oceanographic purposes, remains an expensive and labour intensive activity due to the large sample volumes needed and the complex and lengthy analytical procedures required to measure low levels of contamination. Because of this, some consideration must be given to the design of sampling plans to ensure effective and efficient sampling that can be defended on the basis of scientific rationale. This article tests the hypothesis that geostatistical techniques may prove of use in the optimisation and design of sampling regimes for the monitoring of temporal fluctuations in the levels of technetium at a location in the Norwegian Arctic marine environment. The level of temporal correlation exhibited by two relevant time series was investigated and the information used to observe the effect of sampling frequency on the production of monthly estimates of activity of technetium in both seawater and seaweed. The results indicate that reduced sampling frequency allows production of estimates that acceptably replicate the actual data and that use of geostatistical procedures may offer advantages in the planning of monitoring systems for marine radioactivity. The use of an oceanographic model was also investigated as a means of assessing the temporal correlation prior to actual sampling, an approach that may offer significant advantages by reducing the need to have lengthy time series prior to designing sampling regimes.     

Effectiveness of a fixed-depth sensor deployed from a buoy to estimate water-column cyanobacterial biomass depends on wind speed

Water quality sondes have the advantage of containing multiple sensors, extended deployment times, high temporal resolution, and telecommunication with stakeholder accessible data portals. However, sondes that are part of buoy deployments often suffer from typically being fixed at one depth. Because water treatment plants are interested in water quality at a depth of the water intake and other stakeholders (ex. boaters and swimmers) are interested in the surface, we examined whether a fixed depth of approximately 1 m could cause over- or under-estimation of cyanobacterial biomass. We sampled the vertical distribution of cyanobacteria adjacent to a water quality sonde buoy in the western basin of Lake Erie during the summers of 2015–2017. A comparison of buoy cyanobacteria RFU (Relative Fluorescence Unit) at 1 m to cyanobacteria chlorophyll a (chla) measured throughout the water column showed occurrences when the buoy both under and overestimated the cyanobacteria chla at specific depths. Largest differences between buoy measurements and at-depth grab samples occurred during low wind speeds (< 4.5 m/sec) because low winds allowed cyanobacteria to accumulate at the surface above the buoy's sonde. Higher wind speeds (> 4.5 m/sec) resulted in better agreement between the buoy and at-depth measurements. Averaging wind speeds 12 hr before sample collection decreased the difference between the buoy and at-depth samples for high wind speeds but not low speeds. We suggest that sondes should be placed at a depth of interest for the appropriate stakeholder group or deploy sondes with the ability to sample at various depths.     

Prey risk allocation in a grazing ecosystem.

Understanding the behaviorally mediated indirect effects of predators in ecosystems requires knowledge of predator-prey behavioral interactions. In predator-ungulate-plant systems, empirical research quantifying how predators affect ungulate group sizes and distribution, in the context of other influential variables, is particularly needed. The risk allocation hypothesis proposes that prey behavioral responses to predation risk depend on background frequencies of exposure to risk, and it can be used to make predictions about predator-ungulate-plant interactions. We determined non-predation variables that affect elk (Cervus elaphus) group sizes and distribution on a winter range in the Greater Yellowstone Ecosystem (GYE) using logistic and log-linear regression on surveys of 513 1-km2 areas conducted over two years. Employing model selection techniques, we evaluated risk allocation and other a priori hypotheses of elk group size and distributional responses to wolf (Canis lupus) predation risk while accounting for influential non-wolf-predation variables. We found little evidence that wolves affect elk group sizes, which were strongly influenced by habitat type and hunting by humans. Following predictions from the risk allocation hypothesis, wolves likely created a more dynamic elk distribution in areas that they frequently hunted, as elk tended to move following wolf encounters in those areas. This response should dilute elk foraging pressure on plant communities in areas where they are frequently hunted by wolves. We predict that this should decrease the spatial heterogeneity of elk impacts on grasslands in areas that wolves frequently hunt. We also predict that this should decrease browsing pressure on heavily browsed woody plant stands in certain areas, which is supported by recent research in the GYE.     

Restoring habitat corridors in fragmented landscapes using optimization and percolation models

Landscape fragmentation and habitat loss are significant threats to the conservation of biological diversity. Creating and restoring corridors between isolated habitat patches can help mitigate or reverse the impacts of fragmentation. It is important that restoration and protection efforts be undertaken in the most efficient and effective way possible because conservation budgets are often severely limited. We address the question of where restoration should take place to efficiently reconnect habitat with a landscape-spanning corridor. Building upon findings in percolation theory, we develop a shortest-path optimization methodology for assessing the minimum amount of restoration needed to establish such corridors. This methodology is applied to large numbers of simulated fragmented landscapes to generate mean and variance statistics for the amount of restoration needed. The results provide new information about the expected level of resources needed to realize different corridor configurations under different degrees of fragmentation and different characterizations of habitat connectivity (“neighbor rules”). These results are expected to be of interest to conservation planners and managers in the allocation of conservation resources to restoration projects.     

Counterpart Models in Facility Location Science and Reserve Selection Science

Five classes of zero–one programming models for discrete facility location problems are compared to counterpart models for the selection of conservation reserves. The basic problem of siting facilities to cover demand for services is analogous to the problem of selecting reserves to support species diversity. The classes of models include the set covering and maximal covering models, as well as models for backup and redundant coverage. Issues of reliability and uncertainty are addressed by chance constrained covering models and maximal expected covering models. Exact and heuristic solution approaches are discussed. Multi-objective and economic issues are considered.     

Neighbourhood characteristics and urban gardens in the Toledo metropolitan area: staffing and voluntarism,food production,infrastructure, and sustainability practices

Urban gardens are important sources of sustenance for communities with limited access to food. Hence, this study focuses on food production in gardens in the Toledo metropolitan area in Northwest Ohio. We administered surveys to 150 garden managers from November 2014 to February 2015 in our attempt to better understand how neighbourhood racial composition and poverty levels are related to staffing and voluntarism, food production and distribution, the development of infrastructure, and the adoption of sustainability practices in urban gardens. The results from 30 gardens are presented in this paper. We used Geographic Information Systems to map the gardens and overlay the map with 2010 census data so that we could conduct demographic analyses of the neighbourhoods in which the gardens were located. Though the gardens were small – two acres or less – up to 46 varieties of food were grown in a single garden. Gardens also operated on small budgets. Food from the gardens was gifted or shared with friends, family, and neighbourhood residents. Gardens in predominantly minority neighbourhoods tended to have fewer institutional partners, less garden infrastructure, and had adopted fewer sustainable practices than gardens in predominantly White neighbourhoods. Nonetheless, residents of predominantly minority and high-poverty neighbourhoods participated in garden activities and influenced garden operations. Volunteering and staffing were racialised and gendered.     

What drives visitors to tourist sites to choose “green” accommodation facilities?

Environment, Development and Sustainability - Our aim is to determine the factors influencing a visitor’s decision to stay in a green accommodation facility. Visitors from six tourist sites...