Experts working on behalf of international development organisations need better tools to assist land managers in developing countries maintain their livelihoods, as climate change puts pressure on the ecosystem services that they depend upon. However, current understanding of livelihood vulnerability to climate change is based on a fractured and disparate set of theories and methods. This review therefore combines theoretical insights from sustainable livelihoods analysis with other analytical frameworks (including the ecosystem services framework, diffusion theory, social learning, adaptive management and transitions management) to assess the vulnerability of rural livelihoods to climate change. This integrated analytical framework helps diagnose vulnerability to climate change, whilst identifying and comparing adaptation options that could reduce vulnerability, following four broad steps: i) determine likely level of exposure to climate change, and how climate change might interact with existing stresses and other future drivers of change; ii) determine the sensitivity of stocks of capital assets and flows of ecosystem services to climate change; iii) identify factors influencing decisions to develop and/or adopt different adaptation strategies, based on innovation or the use/substitution of existing assets; and iv) identify and evaluate potential trade-offs between adaptation options. The paper concludes by identifying interdisciplinary research needs for assessing the vulnerability of livelihoods to climate change.

In programs for trading pollution abatement between point and nonpoint sources, the trading ratio specifies the rate at which nonpoint source abatement can be substituted for point source abatement. The appropriate value of this ratio is unclear because of qualitative differences between the two classes of sources. To identify the optimal trading ratio, we develop and analyze a model of point/nonpoint trading. We find the optimal trading ratio depends on the relative costs of enforcing point versus nonpoint reductions and on the uncertainty associated with nonpoint loadings. The uncertainty does not imply a lower bound for the optimal trading ratio.

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A necessary initial step in assessing the value of climate information for regional agriculture is to gauge user perceptions concerning the use of that information. We attempt to do so for cereal and oilseed production in Pergamino, Argentina, located in the Pampas, one of the world's major agricultural regions. A survey of 200 farmers identified climate forecast scale and the reliability of the source of forecast as critical obstacles to adoption. Users' incomplete knowledge of how El Niño-Southern Oscillation affects their region may also pose an obstacle to greater use of climate information. A related problem is that users sometimes confuse the different time scales of weather and climate forecasting. Research and outreach to downscaling forecasts temporally and spatially toward user communities would help close the gap of expectations between forecast user and provider, and would facilitate the trust building process between the two that must precede adoption. KEY WORDS: Climate information · Attitudes · ENSO · AgricultureResale or republication not permitted without written consent of the publisher Clim Res 19: 57-67, 2001 priorities and may undermine our ability to provide useful information. Scientists need to know how the public is likely to respond to ENSO-based climate forecasts because those responses alter the economic influence of climatic impacts (Burns 1999). Policy makers should understand user needs, to realize the potential economic value from the emerging technology of ENSO-based climate forecasting (Changnon 1996).To assess perceptions of ENSO-based climatic forecasting, we used focus groups and a user survey to approach cereal and oilseed producers in Pergamino, Argentina, located in the climatically favorable eastern portion of the Pampas, one of the world's major agricultural regions (Fig. 1). We focus on Argentina for several reasons. Argentina is a major agricultural producer. The value of its agricultural exports was 50 to 60% that of its overall exports and 5.5 to 9.6% of its GDP (gross domestic product) over 1989 (InterAmerican Development Bank 1999. In Argentina, interannual climatic variability causes high variability in crop yields and returns (Parellada et al. 1998, Messina et al. 1999, Podestá et al. 1999a, Ferreyra et al. 2001.1 Since the economic reforms of 1991, rising grain prices, relative to those for beef, have induced an expansion of cultivated areas that amplifies the effects of anomalous climate (Basualdo 1995). 2 The predominant soil in Pergamino is a typical Argiudoll (Paruelo & Sala 1993). Characteristic crop rotations include maize, soybean, and a wheat-soybean relay. Median annual precipitation is 937 mm. Hall et al. (1992) give a description of the climate, soils, and crop production systems in the Pampas. We take an empirical case study approach so that we can identify a specific context for climate information in agricultural decision making. However, the similarity in production scale, crops grown and technology in the Pampas to those in other ma...

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Climate and crop yield variability associated with El Niño -Southern Oscillation (ENSO) are now predictable within limits. This predictability suggests a potential to tailor agricultural management to mitigate impacts of adverse conditions and to take advantage of favorable conditions. However, improved climate predictions may benefit society only with parallel advances in our ability to use this knowledge. We show that the value that will accrue to any given actor from an ENSO phase forecast should be viewed not as a known number but instead as a random draw from a distribution, even when the forecast is always correct. Forecast value depends on the highly variable contexts in which forecasts are used. Randomness in forecast value has significant implications for choices made by forecasters, forecast users and policy makers. To show randomness, we estimate potential economic values of ENSO forecasts for agricultural producers based on two realistic assumptions: the crop prices farmers receive are uncertain; and within an ENSO phase, the actual climate is variable in ways that affect profits. The use of synthetic weather and crop price series, with crop simulation models, helps show the range and likelihood of climate forecast value.

Note: We thank Kevin Simmons, Kerry Smith, and John Whitehead for comments on an earlier draft (subject to the usual caveat that any remaining errors are the responsibility of the authors alone). This paper is a work in progress. We gladly accept any input or thoughts on the content of this discussion. We also appreciate any additional relevant references or studies that we have not covered here. 1 In a memo titled "The Forecast & Warning Process," dated November 19, 2004, H.E. Willoughby (IHRC/FIU) writes: "A narrow definition of hurricane forecast and warning process might be: 'The writing and dissemination of advisory products by the NWS and interpretation and responses by users, from the time the forecast track first threatens U.S. mainland or territories through (XX hours after?) landfall.' This definition is, in fact, too restrictive. Factors such as operational planning prior to each season, demographics, evacuation clearance times, damage to economic assets, lost business opportunities, and expected performances of structures or infrastructure necessarily shape the advisories as much as the meteorology. Pre-storm and preseason education and outreach are essential to the process because they shape the response. What is not part of the process are largely passive measures that might limit damage (including loss of life?) or shape the recovery independently of the content of NWS products or user's response to them. Examples might include aspects of CoE [Corps of Engineers] waterworks, building codes, post-storm recovery, and windstorm or flood insurance. The key distinction here is whether or not a particular aspect influences what happens during the first-threat-to-landfall interval." Most hurricane forecast information predicts events over several days (e.g., 3or 5-day forecasts), but some do predict on seasonal (Gray, Klotzbach, and Thorson 2004) or even decadal time scales (Pielke and Landsea 1998). In general, we focus on shorter-term (e.g., less than 2-week) hurricane forecasts.

Coastal erosion threatens many sandy beaches and the ecological, economic, social and cultural amenities they provide. The problem is especially chronic in South Florida. A frequent solution for beach restoration involves sand replacement, or nourishment, but is temporary, expensive, and has usually been funded by governmental sources. However, as such agencies reduce their share and require more local funding, beach nourishment must rely on other funding sources, including beach recreationists. Our study characterized three South Florida beaches and probed visitor willingness-to-pay for beach nourishment. We found that even beaches within close proximity attract different user types. Users are amenable to higher fees if they lead to greater resource protection.