Probabilistic impacts of climate change on flood frequency using response surfaces II: Scotland

This paper uses a sensitivity framework approach to look at the probabilistic impacts of climate change on 20-year return period flood peaks, by applying a set of typical response surfaces alongside the probabilistic UK Climate Projections (UKCP09) for 10 river-basin regions over Scotland. The first paper of the pair used the same approach for 10 river-basin regions over England and Wales. This paper develops the methodology for Scotland, by first enabling better estimation of the response type of Scottish catchments. Then, as for England and Wales, the potential range of impacts is shown for different types of catchment in each river-basin region in Scotland, and regional average impact ranges are estimated. Results show clear differences in impacts between catchments of different types and between regions. The Argyll and West Highland regions show the highest impacts, while the North-East Scotland region shows the lowest impacts. The overall ranges are generally smaller for Scotland than England and Wales.     

Modeling Emissions from Elevated Cylindrical Bins

Abstract

This paper demonstrates how wind tunnel modeling data that accurately describe plume characteristics near an unconventional emission source can be used to improve the near-field downwind plume profiles predicted by conventional air pollution dispersion models. The study considers a vertical, cylindrical-shaped, elevated bin similar to large product storage bins that can be found at many industrial plant sites. Two dispersion models are considered: the U.S. Environmental Protection Agency's ISC2(ST) model and the Ontario Ministry of the Environment and Energy's GAS model. The wind tunnel study showed that plume behavior was contrary to what was predicted using conventional dispersion models such as ISC2(ST) and GAS and default values of input parameters. The wind tunnel data were used to develop a protocol for correcting the dispersion models inputs, resulting in a substantial improvement in the accuracy of the dispersion estimates.     

Genetic Variation and the Immune Response in Natural Populations of Pocket Gophers

It is thought that genetic variation can affect the persistence of a population through its influence on disease susceptibility. We assessed genome-wide genetic variation, variation at a locus involved in the immune system, and acceptance or rejection of skin grafts in three natural populations of the pocket gopher ( Thomomys bottae ). Multilocus DNA fingerprints confirmed previous allozyme data, revealing high levels of variation among Hastings Reserve pocket gophers and almost complete within-population identity for individuals from the two Patricks Point populations (Patricks J and Patricks F), although Patricks J animals were dissimilar to animals from Patricks F despite their proximity. Individuals from the high-variation population consistently rejected within-population reciprocal skin grafts, whereas Patricks J and Patricks F individuals accepted within-population grafts. Patricks J and Patricks F individuals were found to be immunocompetent, however, as revealed by the ability of all individuals to reject between-population grafts, including those that previously accepted within-population grafts. A DNA heteroduplex analysis was then used to directly characterize variability at DQα, a locus of the immune system's major histocompatability complex. Both populations low in genetic variation were fixed for unique DQα alleles, whereas observed heterozygosity in the Hastings population was 0.43, ascribable to at least three unique alleles. These data are in accord with previous cheetah skin-graft results and confirm that skin grafts can be used to assess genetic similarity. We suggest that although many animal populations can persist with extremely low levels of genetic variation in the wild, such populations may be at a greater risk of extinction from particular pathogens because of their genetic uniformity.     

Efficacy of extracting indices from large‐scale acoustic recordings to monitor biodiversity

Passive acoustic monitoring could be a powerful way to assess biodiversity across large spatial and temporal scales. However, extracting meaningful information from recordings can be prohibitively time consuming. Acoustic indices (i.e., a mathematical summary of acoustic energy) offer a relatively rapid method for processing acoustic data and are increasingly used to characterize biological communities. We examined the relationship between acoustic indices and the diversity and abundance of biological sounds in recordings. We reviewed the acoustic‐index literature and found that over 60 indices have been applied to a range of objectives with varying success. We used 36 of the most indicative indices to develop a predictive model of the diversity of animal sounds in recordings. Acoustic data were collected at 43 sites in temperate terrestrial and tropical marine habitats across the continental United States. For terrestrial recordings, random‐forest models with a suite of acoustic indices as covariates predicted Shannon diversity, richness, and total number of biological sounds with high accuracy (R² ≥ 0.94, mean squared error [MSE] ≤170.2). Among the indices assessed, roughness, acoustic activity, and acoustic richness contributed most to the predictive ability of models. Performance of index models was negatively affected by insect, weather, and anthropogenic sounds. For marine recordings, random‐forest models poorly predicted Shannon diversity, richness, and total number of biological sounds (R² ≤ 0.40, MSE ≥ 195). Our results suggest that using a combination of relevant acoustic indices in a flexible model can accurately predict the diversity of biological sounds in temperate terrestrial acoustic recordings. Thus, acoustic approaches could be an important contribution to biodiversity monitoring in some habitats.     

Extinction and Colonization of Birds on Habitat Islands

Abstract: We used point-count and transect surveys to estimate the distribution and abundance of eight scrub-breeding bird species in 34 habitat fragments and the urban matrix in southern California. We then calculated local extinction and colonization rates by comparing our data with surveys conducted in 1987. We classified factors that influence extinction and colonization rates into two types: (1) extrinsic factors, which are characteristics of the habitat fragments such as area, age, and isolation and (2) intrinsic factors, which are characteristics of the species that inhabit fragments, such as body size and population density. Over the past decade, at least one species went locally extinct in over 50% of the fragments, and local extinctions were almost twice as common as colonizations. Fragment size and, to a lesser extent, fragment age were the most important extrinsic factors determining extinction and colonization. Density indices of scrub birds were the most important intrinsic factors determining extinction rates, predicting the number of sites occupied, the probability of local extinction, relative area requirements, and time to local extinction.     

Habitat utilization and alteration by the invasive burrowing isopod, Sphaeroma quoyanum, in California salt marshes

In recent years the pace of exotic species introduction and invasion has accelerated, particularly in estuaries and wetlands. Species invasions may affect coastal ecosystems in many ways. Alteration of sedimentary environments, through structure formation and burrowing, has particularly dramatic effects on coastal habitats. This study examines modification of channel bank and marsh edge habitat by the burrowing Australasian isopod Sphaeroma quoyanum Milne Edwards, in created and natural salt marshes of San Diego Bay and San Francisco Bay. Abundance and distribution patterns of this isopod species, its relationships with habitat characteristics, and its effects on sediment properties and bank erosion were examined seasonally, and in several marsh microhabitats. Mean isopod densities were 1541 and 2936 individuals per 0.25 m² in San Francisco Bay, and 361 and 1153 individuals per 0.25 m² in San Diego Bay study sites during December and July 1998, respectively. This isopod forms dense, anastomosing burrow networks. S. quoyanum densities did not differ as a function of location within creeks or location in natural versus created marshes. Burrows, which are on average 6 mm wide and 2 cm long, were associated with firm sediments containing high detrital biomass. Although erosion is a natural process along salt marsh banks, enclosure experiments demonstrated that isopod activities can enhance sediment loss from banks. In areas infested with S. quoyanum, losses may exceed 100 cm of marsh edge per year. The effects of habitat alteration by this invading species are likely to increase in severity in the coastal zone as these ecosystems become degraded. Received: 30 March 2000 / Accepted: 21 September 2000     

Understanding public perceptions of risk regarding outdoor pet cats to inform conservation action

Free‐ranging domestic cats (Felis catus) incur and impose risks on ecosystems and represent a complex issue of critical importance to biodiversity conservation and cat and human health globally. Prior social science research on this topic is limited and has emphasized feral cats even though owned cats often comprise a large proportion of the outdoor cat population, particularly in urban areas. To address this gap, we examined public risk perceptions and attitudes toward outdoor pet cats across varying levels of urbanization, including along the wildland–urban interface, in Colorado (U.S.A.), through a mail survey of 1397 residents. Residents did not view all types of risks uniformly. They viewed risks of cat predation on wildlife and carnivore predation on cats as more likely than disease‐related risks. Additionally, risk perceptions were related to attitudes, prior experiences with cats and cat–wildlife interactions, and cat‐owner behavior. Our findings suggest that changes in risk perceptions may result in behavior change. Therefore, knowledge of cat‐related risk perceptions and attitudes could be used to develop communication programs aimed at promoting risk‐aversive behaviors among cat owners and cat‐management strategies that are acceptable to the public and that directly advance the conservation of native species.     

Adaptation to the Impacts of Sea Level Rise in Egypt

Assessment of the vulnerability and expected socioeconomic losses over the Nile delta coast due to the impact of sea level rise is carried out in details. Impacts of sea level rise over the Governorates of Alexandria and Port Said in particular, are evaluated quantitatively. Analysis of the results at Alexandria Governorate indicate that, if no action is taken, an area of about 30% of the city will be lost due to inundation. Almost 2 million people will have to abandon their homeland; 195,000 jobs will be lost and an economic loss of over $3.5 Billion is expected over the next century. At Port Said Governorate results indicate that beach areas are most severely affected (hence tourism), followed by urban areas. The agriculture sector is the least affected sector. It is estimated that the economic loss is over $ 2.0 Billion for 0.50 m SLR and may exceed $ 4.4 Billion for 1.25 m SLR. Options and costs of adaptation are analyzed and presented. Multi-criteria and decision matrix approaches, based on questionnaire surveys are carried out to identify priorities for the two cases. Analysis of these techniques of two options; the current policy (hard protection measures on some vulnerable areas) and no action (stopping these activities) have the lowest scores. Beach nourishment and integrated coastal zone management (ICZM) have the highest scores, however ICZM has high cost measures. The most cost-effective option is the land-use change, however with relatively very high cost measure. It is recommended that an ICZM approach be adopted since it provides a reasonable trade off between costs and cost effectiveness.     

Modeling and inference of animal movement using artificial neural networks

Movement of animals in relation to objects in their environment is important in many areas of ecology and wildlife conservation. Tools for analysis of movement data, however, still remain rather limited. In previous work, we developed nonlinear regression models for movement in relation to a single landscape feature. Here we greatly expand these previous models by using artificial neural networks. The new models add substantial flexibility and capabilities, including the ability to incorporate multiple factors and covariates. We devise a likelihood-based model fitting procedure that utilizes genetic algorithms and demonstrate the approach with movement data for red diamond rattlesnakes. The proposed methodology can be useful for global positioning system tracking data that are becoming more common in studies of animal movement behavior.