FOREWORD: The Economics of Land Use Change: Advancing the Frontiers

Agricultural and Food Policy, Community/Rural/Urban Development, Environmental Economics and Policy, Land Economics/Use, Research Methods/ Statistical Methods, Resource /Energy Economics and Policy,

MODELING TROPICAL DEFORESTATION: A SURVIVAL ANALYSIS LINKING SATELLITE AND HOUSEHOLD SURVEY DATA

This research estimates a hazard model of forest conversion in southern Mexico using geographical information systems, household survey data, and satellite imagery. A utility-maximizing model consistent with agricultural frontier conditions is developed. The econometric methodology incorporates temporal dynamics into the otherwise static range of analyses possible using categorical satellite data.Resource /Energy Economics and Policy,

Capitalization of Open Spaces into Housing Values and the Residential Property Tax Revenue Impacts of Agricultural Easement Programs

Using a unique spatial database, a hedonic model is developed to estimate the value to nearby residents of open space purchased through agricultural preservation programs in three Maryland counties. After correcting for endogeneity and spatial autocorrelation, the estimated coefficients are used to calculate the potential changes in housing values for a given change in neighborhood open space following an agricultural easement purchase. Then, using the current residential property tax for each parcel, the expected increase in county tax revenue is computed and this revenue is compared to the cost of preserving the lands.Land Economics/Use,

An Evaluation of Working Land and Open Space Preservation Programs in Maryland: Are They Paying Too Much?

Farmland preservation programs compensate landowners who enroll for the value lost due to the the restrictions on development applied to their land. These restrictions in principle decrease the value of the land. Yet few studies have found strong statistical evidence that preserved parcels sell for lower prices than unpreserved parcels. We use both a hedonic and a propensity score method to find that preserved parcels sell for 11.4 to 19.8% less than identical unpreserved parcels in Maryland. While significant, a decrease of less than 20% in land value is surprisingly small. If impacts to land value are small, could programs pay landowners less to enroll and thus enroll more land?Land Economics/Use,

TIME SERIES ANALYSIS OF SATELLITE DATA: DEFORESTATION IN SOUTHERN MEXICO

Tropical deforestation is significant to a range of themes that have relevance for the study of environmental change and economic development, including global warming, land degradation, species extinction, and sustainability issues. Recognition that both the location and pattern of forest clearance are often as important as its magnitude has motivated an increasing number of econometric studies that link satellite data and government census data with the aim of modeling the spatial dimensions of deforestation processes. Initial research focused on time series analysis, while recent work has started developing models that make use of time series data on land use. In this paper, we use satellite data from three dates over an approximate 15-year period to estimate the probability of a satellite pixel being in a forested or human-disturbed state. Our study focuses on land-use change in an agricultural frontier spanning the southern Mexican states of Campeche and Quintana Roo. This region contains one of the largest and oldest expanses of tropical forests in the Americas outside of Amazonia and has been identified as a "hot spot" of forest and biotic diversity loss. Over the past 30 years, these forests have been under sustained pressure following the construction of a highway in 1972 that opened the frontier to settlement. The road was part of a larger development effort to promote agricultural colonization and has contributed to a prolonged period of land transformation that has been captured by Thematic Mapper (TM) satellite imagery. We capture these landscape dynamics by assembling a spatial database that links the pixels from three TM images spanning the years 1986-1997 and other spatial environmental and GIS-location derived data with government census socio-economic data of data. We develop a simple utility-maximizing model of the forest clearance decision. Based on previous research, the theoretical model suggests many possible determinants of forest clearance in an economic environment characterized by missing or thin markets, as typifies frontier regions in the nascent stages of economic development. We subsequently test the significance of these determinants using discrete choice analysis These modeling questions have particular relevance for informing carbon sequestration and global warming policy initiatives. Other on-going research conducted by the ecologists associated with the project focus on the species composition, abundance, structure, and re-growth of the different forests types in the region. In addition, litter and biomass studies have been completed which included carbon estimates for the different forest types, including forest re-growth on agricultural land, as function of fallow cycle dynamics. Fallow cycle dynamics are extremely important as the region is dominated by semi-subsistence agriculture with very little chemical inputs, so farmers depend on the fallow cycle to restore soil productivity. It will be these detailed data that will be used to calculate baseline carbon sequestration amounts.Resource /Energy Economics and Policy,

Modeling and Managing Urban Growth at the Rural-Urban Fringe: A Parcel-Level Model of Residential Land Use Change

As many local and state governments in the United States grapple with increasing growth pressures, the need to understand the economic and institutional factors underlying these pressures has taken on added urgency. From an economic perspective, individual land use decisions play a central role in the manifestation of growth pressures, as changes in land use pattern are the cumulative result of numerous individual decisions regarding the use of lands. In this study, the issue of growth management is addressed by developing a spatially disaggregated, microeconomic model of land conversion decisions suitable for describing residential land use change at the rural-urban fringe. The model employs parcel-level data on land use in Calvert County, Maryland, a rapidly growing rural-urban fringe county. A probabilistic model of residential land use change is estimated using a duration model, and the parameter estimates are employed to simulate possible future growth scenarios under alternative growth management scenarios. Results suggest that "smart growth" objectives are best met when policies aimed at concentrating growth in target areas are implemented in tandem with policies designed to preserve rural or open space lands.Land Economics/Use,

Antibacterial Characterization of Novel Synthetic Thiazole Compounds against Methicillin-Resistant Staphylococcus pseudintermedius

Staphylococcus pseudintermedius is a commensal organism of companion animals that is a significant source of opportunistic infections in dogs. With the emergence of clinical isolates of S. pseudintermedius (chiefly methicillin-resistant S. pseudintermedius (MRSP)) exhibiting increased resistance to nearly all antibiotic classes, new antimicrobials and therapeutic strategies are urgently needed. Thiazole compounds have been previously shown to possess potent antibacterial activity against multidrug-resistant strains of Staphylococcus aureus of human and animal concern. Given the genetic similarity between S. aureus and S. pseudintermedius, this study explores the potential use of thiazole compounds as novel antibacterial agents against methicillin-sensitive S. pseudintermedius (MSSP) and MRSP. A broth microdilution assay confirmed these compounds exhibit potent bactericidal activity (at sub-microgram/mL concentrations) against both MSSA and MRSP clinical isolates while the MTS assay confirmed three compounds (at 10 μg/mL) were not toxic to mammalian cells. A time-kill assay revealed two derivatives rapidly kill MRSP within two hours. However, this rapid bactericidal activity was not due to disruption of the bacterial cell membrane indicating an alternative mechanism of action for these compounds against MRSP. A multistep resistance selection analysis revealed compounds 4 and 5 exhibited a modest (twofold) shift in activity over ten passages. Furthermore, all six compounds (at a subinihibitory concentration) demonstrated the ability to re-sensitize MRSP to oxacillin, indicating these compounds have potential use for extending the therapeutic utility of β-lactam antibiotics against MRSP. Metabolic stability analysis with dog liver microsomes revealed compound 3 exhibited an improved physicochemical profile compared to the lead compound. In addition to this, all six thiazole compounds possessed a long post-antibiotic effect (at least 8 hours) against MRSP. Collectively the present study demonstrates these synthetic thiazole compounds possess potent antibacterial activity against both MSSP and MRSP and warrant further investigation into their use as novel antimicrobial agents

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

Temporal and spatial modelling of tropical deforestation: a survival analysis linking satellite and household survey data

We estimate a spatially explicit model of the forest clearance process among smallholder farmers in an agricultural frontier of southern Mexico. Our analysis takes as its point of departure a simple utility-maximising model that suggests many possible determinants of deforestation in an economic environment characterised by missing or thin markets. Hypotheses from the model are tested on a data set that combines a time series of satellite imagery with data collected from a survey of farm households whose agricultural plots were geo-referenced using a global positioning system (GPS). We implement a survival analysis to identify the effect of household level explanatory variables on the probability of deforestation. This approach allows us to introduce a measure of the time until clearance as a covariate, thereby affording a control for the effect of potentially important explanatory variables that vary through time but are not directly observable. In addition to identifying several variables relevant for policy analysis, including household demographics, proximity to roads, and government provision of agricultural support, model results suggest that the deforestation process is characterised by non-linear duration dependence, with the probability of forest clearance first decreasing and then increasing with the passage of time. Published by Elsevier Science B.V