Creating spatially-explicit lawn maps without classifying remotely-sensed imagery: The case of suburban Boston, Massachusetts, USA

Residential lawns are a dominant and growing feature of US residential landscapes, and the resource-intensive management of this landscape feature presents major potential risks to both humans and the environment. In recent years, scientists and policymakers have been increasingly calling for large-extent measures of lawns and other similar landscape features. Unfortunately, the production of such datasets using traditional, remotely sensed measurement approaches can be prohibitively expensive and time consuming. This study uses two statistical prediction methods to extrapolate the quantity and spatial distribution of residential lawns from a sample of mapped lawns in a large study area in suburban Boston, Massachusetts. The goal is to find an inexpensive, broad-coverage dataset that will provide useable estimates of landscape features in places where we do not have direct measurements of those landscape features. The first estimation method uses OLS regression in conjunction with the sample of mapped lawns and freely available US Census data representing theoretically informed social driver variables. The second, simpler, and less computationally intensive estimation method allocates the mean of the sample of mapped lawns uniformly across the study area. Both estimation methods are performed 1000 times in a Monte Carlo framework where the sample is drawn randomly each realization, to assess the sensitivity of the prediction results to the selection of CBGs in each simple random sample. The outputs of each estimation method are then compared to a reference map where the quantity and spatial allocation of lawns is known for each spatial unit of analysis. Results indicate that the OLS prediction method specified with the independent social driver variables performs better than a uniform prediction method when both are compared to the full-study area reference map

The James Webb Space Telescope Mission

Twenty-six years ago a small committee report, building on earlier studies, expounded a compelling and poetic vision for the future of astronomy, calling for an infrared-optimized space telescope with an aperture of at least $4m$. With the support of their governments in the US, Europe, and Canada, 20,000 people realized that vision as the $6.5m$ James Webb Space Telescope. A generation of astronomers will celebrate their accomplishments for the life of the mission, potentially as long as 20 years, and beyond. This report and the scientific discoveries that follow are extended thank-you notes to the 20,000 team members. The telescope is working perfectly, with much better image quality than expected. In this and accompanying papers, we give a brief history, describe the observatory, outline its objectives and current observing program, and discuss the inventions and people who made it possible. We cite detailed reports on the design and the measured performance on orbit.Comment: Accepted by PASP for the special issue on The James Webb Space Telescope Overview, 29 pages, 4 figure

Fundamentals for Using Geographic Information Science to Measure the Effectiveness of Land Conservation Projects

Some humans spend a tremendous amount of effort to change landscapes from a “natural” state to a “developed” state for a variety of desirable economic uses, such as urban, agriculture, transportation, and mining. Others spend a tremendous amount of effort to prevent such development in order to conserve the landscapes for a variety of important environmental uses, such as biodiversity maintenance, carbon storage, water filtration, and landslide prevention. It would be efficient in theory if a society were to focus its development efforts at locations that give the largest economic utility per area developed, and to focus its conservation efforts at locations that give the largest environmental utility per area conserved. However this is not necessarily the strategy of some important conservation policies. Some policy approaches, such as those proposed by the Clean Development Mechanism of the Kyoto Protocol on climate change and the subsequent Bali Roadmap, call for conservation on land that is under imminent threat of new development, not necessarily on land that gives the largest environmental utility (Sedjo et al. 1998, Clémençon 2008). The apparent motivation to focus policy strategies on land under immediate threat is to prevent development before it exerts its environmental impact. This strategy is nearly a perfect equation for escalation of conflict, because it motivates conservationists to prevent the actions that are highest priority for developers. If conservation is effective in preventing development, then conservationists win and developers lose. If conservation is not effective in preventing development, then developers win and conservationists lose. A third plausible outcome of this policy strategy is that a conservation project might inspire developers to shift their future development from their first priority locations to their second priority locations. The process whereby conservation at one location causes development to shift from that location to another location is known as leakage Leakage can undermine the overall effectiveness of a conservation project in terms of total environmental utility (Schwarze et al. 2002). This chapter presents a general conceptual framework to assess the effectiveness of land conservation projects by using Geographic Information Science (GIS) and land change modeling to analyze development and conservation in the presence of leakage. Reprinted from: Geoinformatics for Natural Resource Management, 2009, edited by P.K. Joshi et al. with permission from Nova Science Publishers, Inc

Comparing the input, output, and validation maps for several models of land change

C52, C53, Q15, Q24, R14, R52,

Research on Coupled Human and Natural Systems (CHANS): Approach, Challenges, and Strategies

Understanding the complexity of human–nature interactions is central to the quest for both human well-being and global sustainability. To build an understanding of these interactions, scientists, planners, resource managers, policy makers, and communities increasingly are collaborating across wide-ranging disciplines and knowledge domains. Scientists and others are generating new integrated knowledge on top of their requisite specialized knowledge to understand complex systems in order to solve pressing environmental and social problems (e.g., Carpenter et al. 2009). One approach to this sort of integration, bringing together detailed knowledge of various disciplines (e.g., social, economic, biological, and geophysical), has become known as the study of Coupled Human and Natural Systems, or CHANS (Liu et al. 2007a, b). In 2007 a formal standing program in Dynamics of Coupled Natural and Human Systems was created by the U.S. National Science Foundation. Recently, the program supported the launch of an International Network of Research on Coupled Human and Natural Systems (CHANS-Net.org). A major kick-off event of the network was a symposium on Complexity in Human–Nature Interactions across Landscapes, which brought together leading CHANS scientists at the 2009 meeting of the U.S. Regional Association of the International Association for Landscape Ecology in Snowbird, Utah. The symposium highlighted original and innovative research emphasizing reciprocal interactions between human and natural systems at multiple spatial, temporal, and organizational scales. The presentations can be found at: http://chansnet. org/Symposium_2009.aspx. The symposium was accompanied by a workshop on Challenges and Opportunities in CHANS Research. This article provides an overview of the CHANS approach, outlines the primary challenges facing the CHANS research community, and discusses potential strategies to meet these challenges, based upon the presentations and discussions among participants at the Snowbird meeting

Feline Congenital Erythropoietic Porphyria: Two Homozygous UROS Missense Mutations Cause the Enzyme Deficiency and Porphyrin Accumulation

The first feline model of human congenital erythropoietic porphyria (CEP) due to deficient uroporphyrinogen III synthase (URO-synthase) activity was identified by its characteristic clinical phenotype, and confirmed by biochemical and molecular genetic studies. The proband, an adult domestic shorthair cat, had dark-red urine and brownish discolored teeth with red fluorescence under ultraviolet light. Biochemical studies demonstrated markedly increased uroporphyrinogen I in urine and plasma (2,650- and 10,700-fold greater than wild type, respectively), whereas urinary 5-aminolevulinic acid and porphobilinogen were lower than normal. Erythrocytic URO-synthase activity was <1% of mean wild-type activity, confirming the diagnosis and distinguishing it from feline phenocopies having acute intermittent porphyria. Sequencing of the affected cat’s UROS gene revealed two missense mutations, c.140C>T (p.S47F) in exon 3 and c.331G>A (p.G111S) in exon 6, both of which were homozygous, presumably owing to parental consanguinity. Neither was present in 100 normal cat alleles. Prokaryotic expression and thermostability studies of the purified monomeric wild-type, p.S47F, p.G111S, and p.S47F/G111S enzymes showed that the p.S47F enzyme had 100% of wild-type specific activity but ~50% decreased thermostability, whereas the p.G111S and p.S47F/G111S enzymes had about 60% and 20% of wild-type specific activity, respectively, and both were markedly thermolabile. Molecular modeling results indicated that the less active/less stable p.G111S enzyme was further functionally impaired by a structural interaction induced by the presence of the S47F substitution. Thus, the synergistic interaction of two rare amino acid substitutions in the URO-synthase polypeptide caused the feline model of human CEP