Systematic Temporal Patterns in the Relationship Between Housing Development and Forest Bird Biodiversity

As people encroach increasingly on natural areas, one question is how this affects avian biodiversity. The answer to this is partly scale‐dependent. At broad scales, human populations and biodiversity concentrate in the same areas and are positively associated, but at local scales people and biodiversity are negatively associated with biodiversity. We investigated whether there is also a systematic temporal trend in the relationship between bird biodiversity and housing development. We used linear regression to examine associations between forest bird species richness and housing growth in the conterminous United States over 30 years. Our data sources were the North American Breeding Bird Survey and the 2000 decennial U.S. Census. In the 9 largest forested ecoregions, housing density increased continually over time. Across the conterminous United States, the association between bird species richness and housing density was positive for virtually all guilds except ground nesting birds. We found a systematic trajectory of declining bird species richness as housing increased through time. In more recently developed ecoregions, where housing density was still low, the association with bird species richness was neutral or positive. In ecoregions that were developed earlier and where housing density was highest, the association of housing density with bird species richness for most guilds was negative and grew stronger with advancing decades. We propose that in general the relationship between human settlement and biodiversity over time unfolds as a 2‐phase process. The first phase is apparently innocuous; associations are positive due to coincidence of low‐density housing with high biodiversity. The second phase is highly detrimental to biodiversity, and increases in housing density are associated with biodiversity losses. The long‐term effect on biodiversity depends on the final housing density. This general pattern can help unify our understanding of the relationship of human encroachment and biodiversity response. Patrones Sistemáticos Temporales en la Relación entre Desarrollos Urbanos y la Biodiversidad de Aves de Bosque     

Exploring the risks and benefits of flexibility in biodiversity offset location in a case study of migratory shorebirds

Biodiversity offsets aim to counterbalance the residual impacts of development on species and ecosystems. Guidance documents explicitly recommend that biodiversity offset actions be located close to the location of impact because of higher potential for similar ecological conditions, but allowing greater spatial flexibility has been proposed. We examined the circumstances under which offsets distant from the impact location could be more likely to achieve no net loss or provide better ecological outcomes than offsets close to the impact area. We applied a graphical model for migratory shorebirds in the East Asian–Australasian Flyway as a case study to explore the problems that arise when incorporating spatial flexibility into offset planning. Spatially flexible offsets may alleviate impacts more effectively than local offsets; however, the risks involved can be substantial. For our case study, there were inadequate data to make robust conclusions about the effectiveness and equivalence of distant habitat-based offsets for migratory shorebirds. Decisions around offset placement should be driven by the potential to achieve equivalent ecological outcomes; however, when considering more distant offsets, there is a need to evaluate the likely increased risks alongside the potential benefits. Although spatially flexible offsets have the potential to provide more cost-effective biodiversity outcomes and more cobenefits, our case study showed the difficulty of demonstrating these benefits in practice and the potential risks that need to be considered to ensure effective offset placement.     

Characterization of particulate matter concentrations during controlled indoor activities

Indoor sources have been identified as a major contributor to the increase of particle concentration in indoor environments. The work presented here is a study of the characteristics of particulate matter number size distribution and mass concentration under controlled indoor activities in a laboratory room. The objective is to characterize particulate matter concentrations indoors resulted under the influence of specific sources. Measurements were performed in an empty laboratory (period September–October 2006) using a GRIMM SMPS+C system (particle size range between 11.1 and 1083.3 nm), a DustTrak Aerosol Monitor (TSI) and a P-Trak Ultrafine Particle Counter (TSI). The studied indoor activities included candle burning, hot plate heating, water boiling, onion frying, vacuuming, hair drying, hair spraying, smoking and burning of incense stick. The AMANpsd computer algorithm was used to evaluate the modal structure of measured particle number size distribution data. Furthermore, the change of the particle number size distribution shape under the influence of different emission sources was studied versus time. Finally the particle emission rates were computed. High particle number concentrations were observed during smoking, onion frying, candle burning and incense stick burning. The highest particle mass concentrations were measured during smoking and hair spraying. The shift of the particle size distribution to larger diameters suggests the presence of strong coagulation effect during candle burning, incense stick burning, smoking and onion frying. The size distribution was mainly bimodal during onion frying and candle burning, whereas the size distribution remained unimodal during incense stick burning and smoking experiments.     

The Value of Using Feasibility Models in Systematic Conservation Planning to Predict Landholder Management Uptake

Understanding the social dimensions of conservation opportunity is crucial for conservation planning in multiple‐use landscapes. However, factors that influence the feasibility of implementing conservation actions, such as the history of landscape management, and landholders’ willingness to engage are often difficult or time consuming to quantify and rarely incorporated into planning. We examined how conservation agencies could reduce costs of acquiring such data by developing predictive models of management feasibility parameterized with social and biophysical factors likely to influence landholders’ decisions to engage in management. To test the utility of our best‐supported model, we developed 4 alternative investment scenarios based on different input data for conservation planning: social data only; biological data only; potential conservation opportunity derived from modeled feasibility that incurs no social data collection costs; and existing conservation opportunity derived from feasibility data that incurred collection costs. Using spatially explicit information on biodiversity values, feasibility, and management costs, we prioritized locations in southwest Australia to control an invasive predator that is detrimental to both agriculture and natural ecosystems: the red fox (Vulpes vulpes). When social data collection costs were moderate to high, the most cost‐effective investment scenario resulted from a predictive model of feasibility. Combining empirical feasibility data with biological data was more cost‐effective for prioritizing management when social data collection costs were low (<4% of the total budget). Calls for more data to inform conservation planning should take into account the costs and benefits of collecting and using social data to ensure that limited funding for conservation is spent in the most cost‐efficient and effective manner.     

Quantifying population declines based on presence‐only records for red‐list assessments

Accurate trend estimates are necessary for understanding which species are declining and which are most in need of conservation action. Imperfect species detection may result in unreliable trend estimates because this may lead to the overestimation of declines. Because many management decisions are based on population trend estimates, such biases could have severe consequences for conservation policy. We used an occupancy‐modeling framework to estimate detectability and calculate nationwide population trends for 14 Swiss amphibian species both accounting for and ignoring imperfect detection. Through the application of International Union for Conservation of Nature Red List criteria to the different trend estimates, we assessed whether ignoring imperfect detection could affect conservation policy. Imperfect detection occurred for all species and detection varied substantially among species, which led to the overestimation of population declines when detectability was ignored. Consequently, accounting for imperfect detection lowered the red‐list risk category for 5 of the 14 species assessed. We demonstrate that failing to consider species detectability can have serious consequences for species management and that occupancy modeling provides a flexible framework to account for observation bias and improve assessments of conservation status. A problem inherent to most historical records is that they contain presence‐only data from which only relative declines can be estimated. A move toward the routine recording of nonobservation and absence data is essential if conservation practitioners are to move beyond this toward accurate population trend estimation.     

Evaluating the Quality of Citizen‐Scientist Data on Pollinator Communities

Abstract: Concerns about pollinator declines have grown in recent years, yet the ability to detect changes in abundance, taxonomic richness, and composition of pollinator communities is hampered severely by the lack of data over space and time. Citizen scientists may be able to extend the spatial and temporal extent of pollinator monitoring programs. We developed a citizen‐science monitoring protocol in which we trained 13 citizen scientists to observe and classify floral visitors at the resolution of orders or super families (e.g., bee, wasp, fly) and at finer resolution within bees (superfamily Apoidea) only. We evaluated the protocol by comparing data collected simultaneously at 17 sites by citizen scientists (observational data set) and by professionals (specimen‐based data set). The sites differed with respect to the presence and age of hedgerows planted to improve habitat quality for pollinators. We found significant, positive correlations among the two data sets for higher level taxonomic composition, honey bee (Apis mellifera) abundance, non‐Apis bee abundance, bee richness, and bee community similarity. Results for both data sets also showed similar trends (or lack thereof) in these metrics among sites differing in the presence and age of hedgerows. Nevertheless, citizen scientists did not observe approximately half of the bee groups collected by professional scientists at the same sites. Thus, the utility of citizen‐science observational data may be restricted to detection of community‐level changes in abundance, richness, or similarity over space and time, and citizen‐science observations may not reliably reflect the abundance or frequency of occurrence of specific pollinator species or groups.     

Uncertainty characterization for emergy values

While statistical estimation of uncertainty has not typically accompanied published emergy values, as with any other quantitative model, uncertainty is embedded in these values, and lack of uncertainty characterization makes their accuracy not only opaque, it also prevents the use of emergy values in statistical tests of hypotheses. This paper first attempts to describe sources of uncertainty in unit emergy values (UEVs) and presents a framework for estimating this uncertainty with analytical and stochastic models, with model choices dependent upon on how the UEV is calculated and what kind of uncertainties are quantified. The analytical model can incorporate a broader spectrum of uncertainty types than the stochastic model, including model and scenario uncertainty, which may be significant in emergy models, but is only appropriate for the most basic of emergy calculations. Although less comprehensive in its incorporation of uncertainty, the proposed stochastic method is suitable for all types of UEVs. The distributions of unit emergy values approximate the lognormal distribution with variations depending on the types of uncertainty quantified as well as the way the UEVs are calculated. While both methods of estimating uncertainty in UEVs have their limitations in their presented stage of development, this paper provides methods for incorporating uncertainty into emergy, and demonstrates how this can be depicted and propagated so that it can be used in future emergy analyses and permit emergy to be more readily incorporated into other methods of environmental assessment, such as LCA.     

Brain myelination in rats treated with ionizing radiation in utero

Abstract

Effects of ionizing radiation on brain myelination and some physical development parameters were studied in laboratory rats (Fisher F‐344 inbred strain). Rats were treated with three different doses of radiation (150 rad, 15 rad, and 6.8 rad) delivered on the 20th day of prenatal life. Exposure to 150 rad reduced body, brain, ovary, kidney, heart and spleen weights. Prenatal exposure to 150 rad of radiation reduced the cerebral cortex weight by 22 percent at 30 days of age, and 20 percent at 52 days of age which caused a reduction in cerebral cortex myelin content by 20 and 23 percent at the ages of 30 and 52 days respectively. This dose did not affect the myelin content of the cerebellum or the brain stem, or the myelin concentration (mg myelin/g brain tissue) of the cerebral cortex, cerebellum, and the brain stem. The cerebral cortex weight of the 15 rad treated rats was reduced at the age of 30 days. Exposure to 15 rad, and 6.8 rad did not affect either the myelin content or the myelin concentration of these brain areas.