A Multi-scale Spatial Analysis of Native and Exotic Plant Species Richness Within a Mixed-Disturbance Oak Savanna Landscape

Impacts of human land use pose an increasing threat to global biodiversity. Resource managers must respond rapidly to this threat by assessing existing natural areas and prioritizing conservation actions across multiple spatial scales. Plant species richness is a useful measure of biodiversity but typically can only be evaluated on small portions of a given landscape. Modeling relationships between spatial heterogeneity and species richness may allow conservation planners to make predictions of species richness patterns within unsampled areas. We utilized a combination of field data, remotely sensed data, and landscape pattern metrics to develop models of native and exotic plant species richness at two spatial extents (60- and 120-m windows) and at four ecological levels for northwestern Ohio’s Oak Openings region. Multiple regression models explained 37–77 % of the variation in plant species richness. These models consistently explained more variation in exotic richness than in native richness. Exotic richness was better explained at the 120-m extent while native richness was better explained at the 60-m extent. Land cover composition of the surrounding landscape was an important component of all models. We found that percentage of human-modified land cover (negatively correlated with native richness and positively correlated with exotic richness) was a particularly useful predictor of plant species richness and that human-caused disturbances exert a strong influence on species richness patterns within a mixed-disturbance oak savanna landscape. Our results emphasize the importance of using a multi-scale approach to examine the complex relationships between spatial heterogeneity and plant species richness.     

Modelling landscape effects on density-contact rate relationships of deer in eastern Alberta: Implications for chronic wasting disease

Managing wildlife diseases requires an understanding of disease transmission, which may be strongly affected by host population density and landscape features. Transmission models are typically fit from time-series disease prevalence data and modelled based on how the contact rate among hosts is affected by density, which is often assumed to be a linear (density-dependent transmission) or constant (frequency-dependent transmission) relationship. However, long-term time-series data is unavailable for emerging diseases, and this approach cannot account for independent effects of landscape. We developed a mechanistic model based on ecological data to empirically derive the contact rate-density relationship in white-tailed and mule deer in an enzootic region of chronic wasting disease (CWD) in Alberta, Canada and to determine whether it was affected by landscape. Using data collected from aerial surveys and GPS-telemetry, we developed empirical relationships predicting deer group size, home range size, and habitat selection to iteratively simulate deer distributions across a range of densities and landscapes. We calculated a relative measure of total per-capita contact rate, which is proportional to the number of other deer contacted per individual per unit time, for each distribution as the sum of pairwise contact rates between a target deer and all other individuals. Each pairwise contact rate was estimated from an empirical relationship developed from GPS-telemetry data predicting pairwise contact rates as a function of home range overlap and landscape structure. Total per-capita contact rates increased as a saturating function of density, supporting a transmission model intermediate between density- and frequency-dependent transmission. This pattern resulted from group sizes that reached an asymptote with increasing deer density, although this relationship was mediated by tree and shrub coverage in the landscape, such that in heavily wooded areas, the contact rate saturated at much lower densities. These results suggest that CWD management based on herd reductions, which require a density-dependent contact rate to be effective, may have variable effects on disease across a single management region. The novel mechanistic approach we employed for estimating effects of density and landscape on transmission is a powerful complement to typical data-fitting approaches for modelling disease transmission.     

Does energy consumption,economic growth,urbanization, and population growth influence carbon emissions in the BRICS? Evidence from panel models robust to cross-sectional dependence and slope heterogeneity

Environmental Science and Pollution Research - This paper examined the nexus between economic growth, energy consumption, urbanization, population growth, and carbon emissions in the BRICS...     

Cavity excavation and enlargement as mechanisms for indirect interactions in an avian community

Direct and indirect species interactions within ecological communities may play a strong role in influencing or maintaining community structure. Complex community interactions pose a major challenge to predicting ecosystem responses to environmental change because predictive frameworks require identification of mechanisms by which community interactions arise. Cavity-nesting communities are well suited for mechanistic studies of species interactions because cavity nesters interact through the creation of and competition for cavity-nest sites. In this study, we use a cavity-nest web as a predictive framework for identifying potential indirect species interactions within a cavity-nesting community. From 2002 to 2005, we monitored abundance and nests of cavity-nesting birds in the longleaf pine (Pinus palustris) ecosystem. Using a nest-web approach, we identified a potential indirect interaction between the Red-cockaded Woodpecker (Picoides borealis) and large secondary cavity nesters, mediated by the Northern Flicker (Colaptes auratus). We used structural equation modeling to test a path model of this interaction, using cavity excavation and enlargement as mechanisms which drive the relationship between these species. Through experimental manipulation of cavity availability, we blocked links described in our model, confirming cavity creation and enlargement as processes that influence community structure. We found that a single-species management technique could potentially disrupt this indirect relationship by affecting Northern Flicker cavity-excavation behavior. This study is the first demonstration of how experimental cavity manipulation can be used to test inferred processes derived from a nest web and highlights the need to understand how mechanisms underlying species interactions can complicate ecosystem responses to environmental change.     

Inferring linear feature use in the presence of GPS measurement error

Global Positioning System (GPS) collars are increasingly used to study animal movement and habitat use. Measurement error is defined as the difference between the observed and true value being measured. In GPS data measurement error is referred to as location error and leads to misclassification of observed locations into habitat types. This is particularily true when studying habitats of small spatial extent with large amounts of edge, such as linear features (e.g. roads and seismic lines). However, no consistent framework exists to address the effect of measurement error on habitat classification of observed locations and resulting biological inference. We developed a mechanistic, empirically-based method for buffering linear features that minimizes the underestimation of animal use introduced by GPS measurement error. To do this we quantified the distribution of measurement error and derived an explicit formula for buffer radius which incorporated the error distribution, the width of the linear feature, and a predefined amount of acceptable type I error in location classification. In our empirical study we found the GPS measurement error of the Lotek GPS_3300 collar followed a bivariate Laplace distribution with parameter ρ = 0.1123. When we applied our method to a simulated landscape, type I error was reduced by 57%. This study highlights the need to address the effect of GPS measurement error in animal location classification, particularily for habitats of small spatial extent.     

Database-driven models of the world's Large Marine Ecosystems

We present a new methodology for database-driven ecosystem model generation and apply the methodology to the world's 66 currently defined Large Marine Ecosystems. The method relies on a large number of spatial and temporal databases, including FishBase, SeaLifeBase, as well as several other databases developed notably as part of the Sea Around Us project. The models are formulated using the freely available Ecopath with Ecosim (EwE) modeling approach and software. We tune the models by fitting to available time series data, but recognize that the models represent only a first-generation of database-driven ecosystem models. We use the models to obtain a first estimate of fish biomass in the world's LMEs. The biggest hurdles at present to further model development and validation are insufficient time series trend information, and data on spatial fishing effort.     

Assessing the Potential for Salmon Recovery via Floodplain Restoration: A Multitrophic Level Comparison of Dredge-Mined to Reference Segments

Pre-restoration studies typically focus on physical habitat, rather than the food-base that supports aquatic species. However, both food and habitat are necessary to support the species that habitat restoration is frequently aimed at recovering. Here we evaluate if and how the productivity of the food-base that supports fish production is impaired in a dredge-mined floodplain within the Yankee Fork Salmon River (YFSR), Idaho (USA); a site where past restoration has occurred and where more has been proposed to help recover anadromous salmonids. Utilizing an ecosystem approach, we found that the dredged segment had comparable terrestrial leaf and invertebrate inputs, aquatic primary producer biomass, and production of aquatic invertebrates relative to five reference floodplains. Thus, the food-base in the dredged segment did not necessarily appear impaired. On the other hand, we observed that off-channel aquatic habitats were frequently important to productivity in reference floodplains, and the connection of these habitats in the dredged segment via previous restoration increased invertebrate productivity by 58%. However, using a simple bioenergetic model, we estimated that the invertebrate food-base was at least 4× larger than present demand for food by fish in dredged and reference segments. In the context of salmon recovery efforts, this observation questions whether additional food-base productivity provided by further habitat restoration would be warranted in the YFSR. Together, our findings highlight the importance of studies that assess the aquatic food-base, and emphasize the need for more robust ecosystem models that evaluate factors potentially limiting fish populations that are the target of restoration.     

Is adaptive management helping to solve fisheries problems?

Adaptive management has been widely recommended as a way to deal with extreme uncertainty in natural resource and environmental decision making. The core concept in adaptive management is that policy choices should be treated as deliberate, large-scale experiments; hence, policy choice should be treated at least partly as a problem of scientific experimental design. There have now been upwards of 100 case studies where attempts were made to apply adaptive management to issues ranging from restoration of endangered desert fish species to protection of the Great Barrier Reef. Most of these cases have been failures in the sense that no experimental management program was ever implemented, and there have been serious problems with monitoring programs in the handful of cases where an experimental plan was implemented. Most of the failures can be traced to three main institutional problems: i) lack of management resources for the expanded monitoring needed to carry out large-scale experiments; ii) unwillingness by decision makers to admit and embrace uncertainty in making policy choices; and iii) lack of leadership in the form of individuals willing to do all the hard work needed to plan and implement new and complex management programs.     

Bacterial community structure in soils contaminated by polycyclic aromatic hydrocarbons

Bacterial community structure was examined in polycyclic aromatic hydrocarbon (PAH) contaminated soil taken from a timber treatment facility in southern Ireland. Profiles of soil bacterial communities were generated using a molecular fingerprinting technique, terminal restriction fragment length polymorphism (TRFLP), and results were interpreted using sophisticated multivariate statistical analysis. Findings suggested that there was a correlation between PAH structure and bacterial community composition. Initial characterisation of soil from the timber treatment facility indicated that PAH contamination was unevenly distributed across the site. Bacterial community composition was correlated with the type of PAH present, with microbial community structure associated with soil contaminated with two-ringed PAHs only being distinctly different to communities in soils contaminated with multi-component PAH mixtures. Typically the number of bacterial ribotypes detected in samples did not appear to be adversely affected by the level of contamination.     

Customers as contributors and reliable evaluators of creativity in the service industry

Using hair stylists, we examined the nature of creativity in a service setting and the impact of customers as part of the social context for employee creativity. We also assessed whether customers could serve as reliable evaluators of creativity. To do so, we collected data from multiple sources: service providers, supervisors, and customers. Results demonstrated that customer input and customer affective‐based trust made significant, positive, and independent contributions to service‐related creativity. Moreover, customers in the service industry proved to be reliable raters of employee creativity, compatible with supervisors. Finally, input and trust were associated differently with service‐related and organization‐related creativity. Copyright © 2008 John Wiley & Sons, Ltd.