Riparian rehabilitation planning in an urban–rural gradient: Integrating social needs and ecological conditions

In the present context of global change and search for sustainability, we detected a gap between restoration and society: local communities are usually only considered as threats or disturbances when planning for restoration. To bridge this gap, we propose a landscape design framework for planning riparian rehabilitation in an urban–rural gradient. A spatial multi-criteria analysis was used to assess the priority of riversides by considering two rehabilitation objectives simultaneously—socio-environmental and ecological—and two sets of criteria were designed according to these objectives. The assessment made it possible to identify 17 priority sites for riparian rehabilitation that were associated with different conditions along the gradient. The double goal setting enabled a dual consideration of citizens, both as beneficiaries and potential impacts to rehabilitation, and the criteria selected incorporated the multi-dimensional nature of the environment. This approach can potentially be adapted and implemented in any other anthropic–natural interface throughout the world.     

The distribution and extent of heavy metal accumulation in song sparrows along Arizona’s upper Santa Cruz River

Heavy metals are persistent environmental contaminants, and transport of metals into the environment poses a threat to ecosystems, as plants and wildlife are susceptible to long-term exposure, bioaccumulation, and potential toxicity. We investigated the distribution and cascading extent of heavy metal accumulation in southwestern song sparrows (Melospiza melodia fallax), a resident riparian bird species that occurs along the US/Mexico border in Arizona’s upper Santa Cruz River watershed. This study had three goals: (1) quantify the degree of heavy metal accumulation in sparrows and determine the distributional patterns among study sites, (2) compare concentrations of metals found in this study to those found in studies performed prior to a 2009 international wastewater facility upgrade, and (3) assess the condition of song sparrows among sites with differing potential levels of exposure. We examined five study sites along with a reference site that reflect different potential sources of contamination. Body mass residuals and leukocyte counts were used to assess sparrow condition. Birds at our study sites typically had higher metal concentrations than birds at the reference site. Copper, mercury, nickel, and selenium in song sparrows did exceed background levels, although most metals were below background concentrations determined from previous studies. Song sparrows generally showed lower heavy metal concentrations compared to studies conducted prior to the 2009 wastewater facility upgrade. We found no cascading effects as a result of metal exposure.     

Archaeological Evidence of Validity of Fish Populations on Unexploited Reefs as Proxy Targets for Modern Populations

Reef‐fish management and conservation is hindered by a lack of information on fish populations prior to large‐scale contemporary human impacts. As a result, relatively pristine sites are often used as conservation baselines for populations near sites affected by humans. This space‐for‐time approach can only be validated by sampling assemblages through time. We used archaeological remains to evaluate whether the remote, uninhabited Northwestern Hawaiian Islands (NWHI) might provide a reasonable proxy for a lightly exploited baseline in the Main Hawaiian Islands (MHI). We used molecular and morphological techniques to describe the taxonomic and size composition of the scarine parrotfish catches present in 2 archaeological assemblages from the MHI, compared metrics of these catches with modern estimates of reproductive parameters to evaluate whether catches represented by the archaeological material were consistent with sustainable fishing, and evaluated overlap between size structures represented by the archaeological material and modern survey data from the MHI and the NWHI to assess whether a space‐for‐time substitution is reasonable. The parrotfish catches represented by archaeological remains were consistent with sustainable fishing because they were dominated by large, mature individuals whose average size remained stable from prehistoric (AD approximately 1400–1700) through historic (AD 1700–1960) periods. The ancient catches were unlike populations in the MHI today. Overlap between the size structure of ancient MHI catches and modern survey data from the NWHI or the MHI was an order of magnitude greater for the NWHI comparison, a result that supports the validity of using the NWHI parrotfish data as a proxy for the MHI before accelerated, heavy human impacts in modern times. Evidencia Arqueológica de la Validez de Poblaciones de Peces en Arrecifes Sin Explotar como Objetivos de Apoderamiento para Poblaciones Actuales     

Scaring as a tool to alleviate crop damage by geese: Revealing differences between farmers’ perceptions and the scale of the problem

Expanding populations of farmland foraging geese are causing escalating conflict with agriculture. We used questionnaires to investigate farmers´ perceptions in mid-Norway of spring staging geese and the extent to which they attempt to reduce pasture damage by goose scaring. We predicted farmers’ scaring effort (a measure of dissatisfaction) to increase on fields closer to goose roosting sites where goose grazing intensity was highest (measured by dropping counts). Results showed no such relationship, suggesting that farmers’ perception of goose use was not linked to actual goose use, but influenced by sociological factors and individual opinion. These results confirm the need to distribute subsidies/compensation to affected farmers based upon quantifiable measures of goose use rather than complaint levels. To avoid further conflict escalation, it is equally important that managers are aware of farmers´ perceptions and their causes, to effectively target communication about policies and measures to mitigate goose–agriculture problems.     

Elite cues,media coverage,and public concern: an integrated path analysis of public opinion on climate change, 2001–2013

To analyze the factors affecting US public concern about the threat of climate change between January 2002 and December 2013, data from 74 separate surveys are used to construct quarterly measures of public concern over global climate change. Five factors should account for changes in levels of concern: extreme weather events, public access to accurate scientific information, media coverage, elite cues, and movement/countermovement advocacy. Structural equation modeling indicates that elite cues, movement advocacy efforts, weather, and structural economic factors influence the level of public concern about climate change. While media coverage exerts an important influence, it is itself largely a function of elite cues and economic factors. Promulgation to the public of scientific information on climate change has no effect. Information-based science advocacy has had only a minor effect on public concern, while political mobilization by elites and advocacy groups is critical in influencing climate change concern.     

A new sampler for stratified lagoon chemical and microbiological assessments

A sampler was needed for a spatial and temporal study of microbial and chemical stratification in a large swine manure lagoon that was known to contain zoonotic bacteria. Conventional samplers were limited to collections of surface water samples near the bank or required a manned boat. A new sampler was developed to allow simultaneous collection of multiple samples at different depths, up to 2.3 m, without a manned boat. The sampler was tethered for stability, used remote control (RC) for sample collection, and accommodated rapid replacement of sterile tubing modules and sample containers. The sampler comprised a PVC pontoon with acrylic deck and watertight enclosures, for a 12 VDC gearmotor, to operate the collection module, and vacuum system, to draw samples into reusable autoclavable tubing and 250-mL bottles. Although designed primarily for water samples, the sampler was easily modified to collect sludge. The sampler held a stable position during deployment, created minimal disturbance in the water column, and was readily cleaned and sanitized for transport. The sampler was field tested initially in a shallow fresh water lake and subsequently in a swine manure treatment lagoon. Analyses of water samples from the lagoon tests showed that chemical and bacterial levels, pH, and EC did not differ between 0.04, 0.47, and 1.0 m depths, but some chemical and bacterial levels differed between winter and spring collections. These results demonstrated the utility of the sampler and suggested that future manure lagoon studies employ fewer or different depths and more sampling dates.     

A graphical assessment and spatial clustering of the Deepwater Horizon oil spill impact on Laughing Gulls

The Deepwater Horizon oil spill occurred in the Gulf of Mexico on April 20, 2010. Considered the largest accidental marine oil spill in history, oil flowed for three months and approximately five million barrels of oil spilled through by mid-July 2010. In this article, we analyze bird data to assess the impact of the oil spill on the Gulf wildlife. Particularly, we want to determine in which regions Laughing Gulls were mostly affected by the oil spill, and whether those regions spatially shifted throughout the year 2010. Though our data sets have some limitations to apply statistical analysis methods, we obtained very interesting results. Our analyses showed the general consistency of the results based on two population data sets (from the 2011 Data Expo and from the eBird community) and justified the use of both publicly available data sets. We showed that the closer the surface oil spill area approached to the Laughing Gulls habitats, the more significant clusters of bird cases were observed.     

Goose management schemes to resolve conflicts with agriculture: Theory,practice and effects

In 2012, the four countries hosting the Svalbard population of pink-footed goose Anser brachyrhynchus along its flyway launched an International Species Management Plan for the population. One of the aims was to reduce conflicts between geese and agriculture to an acceptable level. Since 2006, Norway has offered subsidies to farmers that provide refuge areas for geese on their land. We evaluate the mid-Norwegian goose management subsidy scheme, with a view to its adjustment to prevailing ecological and socio-economic parameters. The analysis indicates that the legitimacy of the scheme is highly dependent on transparency of knowledge management and accountability of management scheme to the farming community. Among farmers, as well as front-line officials, outcomes of prioritisation processes within the scheme are judged unfair when there is an evident mismatch between payments and genuine damage. We suggest how the scheme can be made more fair and responsive to ecological changes, within a framework of adaptive management.     

A Tool for Classification and Regression Using Random Forest Methodology: Applications to Landslide Susceptibility Mapping and Soil Thickness Modeling

Classification and regression problems are a central issue in geosciences. In this paper, we present Classification and Regression Treebagger (ClaReT), a tool for classification and regression based on the random forest (RF) technique. ClaReT is developed in Matlab and has a simple graphic user interface (GUI) that simplifies the model implementation process, allows the standardization of the method, and makes the classification and regression process reproducible. This tool performs automatically the feature selection based on a quantitative criterion and allows testing a large number of explanatory variables. First, it ranks and displays the parameter importance; then, it selects the optimal configuration of explanatory variables; finally, it performs the classification or regression for an entire dataset. It can also provide an evaluation of the results in terms of misclassification error or root mean squared error. We tested the applicability of ClaReT in two case studies. In the first one, we used ClaReT in classification mode to identify the better subset of landslide conditioning variables (LCVs) and to obtain a landslide susceptibility map (LSM) of the Arno river basin (Italy). In the second case study, we used ClaReT in regression mode to produce a soil thickness map of the Terzona catchment, a small sub-basin of the Arno river basin. In both cases, we performed a validation of the results and a comparison with other state-of-the-art techniques. We found that ClaReT produced better results, with a more straightforward and easy application and could be used as a valuable tool to assess the importance of the variables involved in the modeling.