Microtargeting for conservation

Widespread human action and behavior change is needed to achieve many conservation goals. Doing so at the requisite scale and pace will require the efficient delivery of outreach campaigns. Conservation gains will be greatest when efforts are directed toward places of high conservation value (or need) and tailored to critical actors. Recent strategic conservation planning has relied primarily on spatial assessments of biophysical attributes, largely ignoring the human dimensions. Elsewhere, marketers, political campaigns, and others use microtargeting—predictive analytics of big data—to identify people most likely to respond positively to particular messages or interventions. Conservationists have not yet widely capitalized on these techniques. To investigate the effectiveness of microtargeting to improve conservation, we developed a propensity model to predict restoration behavior among 203,645 private landowners in a 5,200,000 ha study area in the Chesapeake Bay Watershed (U.S.A.). To isolate the additional value microtargeting may offer beyond geospatial prioritization, we analyzed a new high-resolution land-cover data set and cadastral data to identify private owners of riparian areas needing restoration. Subsequently, we developed and evaluated a restoration propensity model based on a database of landowners who had conducted restoration in the past and those who had not (n = 4978). Model validation in a parallel database (n = 4989) showed owners with the highest scorers for propensity to conduct restoration (i.e., top decile) were over twice as likely as average landowners to have conducted restoration (135%). These results demonstrate that microtargeting techniques can dramatically increase the efficiency and efficacy of conservation programs, above and beyond the advances offered by biophysical prioritizations alone, as well as facilitate more robust research of many social–ecological systems.     

Probabilistic Flood Inundation Forecasting Using Rating Curve Libraries

One approach for performing uncertainty assessment in flood inundation modeling is to use an ensemble of models with different conceptualizations, parameters, and initial and boundary conditions that capture the factors contributing to uncertainty. However, the high computational expense of many hydraulic models renders their use impractical for ensemble forecasting. To address this challenge, we developed a rating curve library method for flood inundation forecasting. This method involves pre‐running a hydraulic model using multiple inflows and extracting rating curves, which prescribe a relation between streamflow and stage at various cross sections along a river reach. For a given streamflow, flood stage at each cross section is interpolated from the pre‐computed rating curve library to delineate flood inundation depths and extents at a lower computational cost. In this article, we describe the workflow for our rating curve library method and the Rating Curve based Automatic Flood Forecasting (RCAFF) software that automates this workflow. We also investigate the feasibility of using this method to transform ensemble streamflow forecasts into local, probabilistic flood inundation delineations for the Onion and Shoal Creeks in Austin, Texas. While our results show water surface elevations from RCAFF are comparable to those from the hydraulic models, the ensemble streamflow forecasts used as inputs to RCAFF are the largest source of uncertainty in predicting observed floods.     

Locating Spatial Variation in the Association Between Wildland Fire Risk and Social Vulnerability Across Six Southern States

Wildland fire in the South commands considerable attention, given the expanding wildland urban interface (WUI) across the region. Much of this growth is propelled by higher income retirees and others desiring natural amenity residential settings. However, population growth in the WUI increases the likelihood of wildfire fire ignition caused by people, as humans account for 93% of all wildfires fires in the South. Coexisting with newly arrived, affluent WUI populations are working class, poor or otherwise socially vulnerable populations. The latter groups typically experience greater losses from environmental disasters such as wildfire because lower income residents are less likely to have established mitigation programs in place to help absorb loss. We use geographically weighted regression to examine spatial variation in the association between social vulnerability (SOVUL) and wildfire risk. In doing so, we identify “hot spots” or geographical clusters where SOVUL varies positively with wildfire risk across six Southern states—Alabama, Arkansas, Florida, Georgia, Mississippi, and South Carolina. These clusters may or may not be located in the WUI. These hot spots are most prevalent in South Carolina and Florida. Identification of these population clusters can aid wildfire managers in deciding which communities to prioritize for mitigation programming.     

Facilitating climate‐change‐induced range shifts across continental land‐use barriers

Climate changes impose requirements for many species to shift their ranges to remain within environmentally tolerable areas, but near‐continuous regions of intense human land use stretching across continental extents diminish dispersal prospects for many species. We reviewed the impact of habitat loss and fragmentation on species’ abilities to track changing climates and existing plans to facilitate species dispersal in response to climate change through regions of intensive land uses, drawing on examples from North America and elsewhere. We identified an emerging analytical framework that accounts for variation in species' dispersal capacities relative to both the pace of climate change and habitat availability. Habitat loss and fragmentation hinder climate change tracking, particularly for specialists, by impeding both propagule dispersal and population growth. This framework can be used to identify prospective modern‐era climatic refugia, where the pace of climate change has been slower than surrounding areas, that are defined relative to individual species' needs. The framework also underscores the importance of identifying and managing dispersal pathways or corridors through semi‐continental land use barriers that can benefit many species simultaneously. These emerging strategies to facilitate range shifts must account for uncertainties around population adaptation to local environmental conditions. Accounting for uncertainties in climate change and dispersal capabilities among species and expanding biological monitoring programs within an adaptive management paradigm are vital strategies that will improve species' capacities to track rapidly shifting climatic conditions across landscapes dominated by intensive human land use.     

Spatial and temporal drivers of zoonotic pathogen contamination of an agricultural watershed

In regions where animal agriculture is prominent, such as southern Alberta, higher rates of gastrointestinal illness have been reported when compared with nonagricultural regions. This difference in the rate of illness is thought to be a result of increased zoonotic pathogen exposure through environmental sources such as water. In this study, temporal and spatial factors associated with bacterial pathogen contamination of the Oldman River, which transverses this region, were analyzed using classification and regression tree analysis. Significantly higher levels of fecal indicators; more frequent isolations of Campylobacter spp., Escherichia coli O157:H7, and Salmonella enterica spp.; and higher rates of detection of pig-specific Bacteroides markers occurred at downstream sites than at upstream sites, suggesting additive stream inputs. Fecal indicator densities were also significantly higher when any one of these three bacterial pathogens was present and where there were higher total animal manure units; however, occasionally pathogens were present when fecal indicator levels were low or undetectable. Overall, Salmonella spp., Campylobacter spp., and E. coli O157:H7 presence was associated with season, animal manure units, and total rainfall on the day of sampling and 3 d in advance of sampling. Several of the environmental variables analyzed in this study appear to influence pathogen prevalence and therefore may be useful in predicting water quality and safety and in the improvement of watershed management practices in this and other agricultural regions.     

Evaluation of a Statewide Matching Grant Program for the Collection of Household Hazardous Waste

Between Fall 1985 and Spring 1987, the Massachusetts Departments of Environmental Management and Environmental Quality Engineering awarded communities $490,000 in matching state grants for the collection of household hazardous waste. Funded collections resulted in the disposal of approximately 291 tons of waste at an average cost of $9 per gallon. Household participation rates ranged from 0.2 percent to 5.8 percent. An average of 10 gallons of household hazardous waste was disposed of per participating household. Total collection costs including local and state shares exceeded $900,000. Differences in participation, wastes collected and collection costs among communities were due to variations in outreach and education efforts, experience, bid specifications, wastes collected, setup costs, and collection techniques. The relative high cost per participating household and low participation rate suggest the need for alternative approaches to the management of household hazardous waste which will be explored in future grant cycles.     

Effectiveness of the Local Adaptation Plan of Action to support climate change adaptation in Nepal

A key challenge in climate change adaptation in developing countries as a whole, and to handling global change in particular, is to link local adaptation needs on the one hand, with national adaptation initiatives on the other, so that vulnerable households and communities can directly benefit. This study assesses the impact of the Nepal government’s efforts to promote its Local Adaptation Plan of Action (LAPA) and its applicability to other least developed countries (LDCs). Based on data gathered from two field studies in Nepal, the research shows that the Nepal’s LAPA has succeeded in mobilizing local institutions and community groups in adaptation planning and recognizing their role in adaptation. However, the LAPA approach and implementation have been constrained by sociostructural and governance barriers that have failed to successfully integrate local adaptation needs in local planning and increase the adaptive capacity of vulnerable households. This paper describes the mechanisms of suitable governance strategies for climate change adaptation specific to Nepal and other LDCs. It also argues the need to adopt an adaptive comanagement approach, where the government and all stakeholders identify common local- and national-level mainstreaming strategy for knowledge management, resource mobilization, and institutional development, ultimately using adaptation as a tool to handle global change.     

Assessing the shelf life of cost‐efficient conservation plans for species at risk across gradients of agricultural land use

High costs of land in agricultural regions warrant spatial prioritization approaches to conservation that explicitly consider land prices to produce protected‐area networks that accomplish targets efficiently. However, land‐use changes in such regions and delays between plan design and implementation may render optimized plans obsolete before implementation occurs. To measure the shelf life of cost‐efficient conservation plans, we simulated a land‐acquisition and restoration initiative aimed at conserving species at risk in Canada's farmlands. We accounted for observed changes in land‐acquisition costs and in agricultural intensity based on censuses of agriculture taken from 1986 to 2011. For each year of data, we mapped costs and areas of conservation priority designated using Marxan. We compared plans to test for changes through time in the arrangement of high‐priority sites and in the total cost of each plan. For acquisition costs, we measured the savings from accounting for prices during site selection. Land‐acquisition costs and land‐use intensity generally rose over time independent of inflation (24–78%), although rates of change were heterogeneous through space and decreased in some areas. Accounting for spatial variation in land price lowered the cost of conservation plans by 1.73–13.9%, decreased the range of costs by 19–82%, and created unique solutions from which to choose. Despite the rise in plan costs over time, the high conservation priority of particular areas remained consistent. Delaying conservation in these critical areas may compromise what optimized conservation plans can achieve. In the case of Canadian farmland, rapid conservation action is cost‐effective, even with moderate levels of uncertainty in how to implement restoration goals.     

Adapting to climate change through local municipal planning: barriers and challenges

Municipal planning represents a key avenue for local adaptation, but is subject to recognised constraints. To date, these constraints have focused on simplistic factors such as limited resources and lack of information. In this paper we argue that this focus has obscured a wider set of constraints which need to be acknowledged and addressed if adaptation is likely to advance through municipal planning. Although these recognised constraints are relevant, we argue that what underpins these issues are more fundamental challenges affecting local, placed-based planning by drawing on the related field of community-based environmental planning (CBEP). In considering a wider set of constraints to practical attempts towards adaptation, the paper considers planning based on a case study of three municipalities in Sydney, Australia in 2008. The results demonstrate that climate adaptation was widely accepted as an important issue for planning conducted by local governments. However, it was yet to be embedded in planning practice which retained a strong mitigation bias in relation to climate change. In considering the case study, we draw attention to factors thus far under-acknowledged in the climate adaptation literature. These include leadership, institutional context and competing planning agendas. These factors can serve as constraints or enabling mechanisms for achieving climate adaptation depending upon how they are exploited in any given situation. The paper concludes that, through addressing these issues, local, place-based planning can play a greater role in achieving climate adaptation.