The reality of having to live with some degree of anthropogenic global warming provides a strong impetus for the development and implementation of climate change adaptation strategies. Humans are credited with the ability to foresee and thus to selectively introduce adaptation strategies in anticipation of and response to the challenges of global warming (Gallopín in Glob Environ Change 16 (3): [293][294][295][296][297][298][299][300][301][302][303] 2006; Gunderson in Ecol Soc 15(2):1-11, 2010). However, these strategies of deliberate change have to be considered in the context of closely coupled social-ecological systems (SES). Adaptations introduced must therefore be compatible with the social-ecological system in its entirety (Berkes et al. in Navigating social-ecological systems. Building resilience for complexity and change. Cambridge University Press, Cambridge, 2003) and that requires a holistic, systems approach. Using two case studies from West Africa, this chapter presents examples of prominent adaptation strategies that have been introduced in an attempt to adjust to the already evolving climatic conditions. However, through these examples, this chapter demonstrates that a lack of whole systems thinking is at the heart of the limited sustainability of promising strategies. The chapter will examine where the obstacles to sustained implementation arise, concluding with recommendations to address the limitations.To examine limitations to adaptation in the case study communities, this chapter will aim to answer the following three key questions:1. What are the impacts of climatic variability, changing rainfall patterns and natural hazards such as floods, dry spells and droughts on rural livelihoods?

In this paper, we develop a reduced form model for factors influencing the conservation of forest resources. We then estimate it using a bivariate negative binomial regression model with cases of illegal farming and illegal cattle grazing in the W Reserve in West Africa. Our results show that population size and farm area in the periphery of the W Reserve are associated with an increase of 2.4% and 7.1% of these illegal activities, respectively. On the other hand, income level, the existence of a checkpoint, and the distance between the villages and the reserve decrease these illegal activities by 7.3%, 63.2%, and 2.3%, respectively.

Lumber is one of the most essential forest products in the United States. During the first year of the COVID-19 pandemic, lumber prices almost quadrupled, and fluctuations reached record levels. Although market experts have pointed to various drivers of such high price volatility, no firm conclusions have been drawn yet. Using the generalized autoregressive conditional heteroskedasticity-mixed data sampling (GARCH-MIDAS) framework, this study assesses the potential drivers of lumber price volatility, with predictors including the Google Trends Web Search Index, housing starts, US lumber production quantity, and VIX index, representing public attention, housing demand, lumber supply, and macroeconomic concerns, respectively. We have found that housing demand is the key driver of lumber price volatility, followed by public attention. It is worth noting that US lumber supply and macroeconomic concerns have played a modest role in explaining lumber price volatility. Also, forecasting lumber price by using the housing demand variable substantially outperforms others. Market participants, including lumber mills, wholesalers, and home builders can get valuable information from the housing market to manage lumber price risk. Study Implications: The findings of this study can be used to improve hedging strategies, design option pricing formulas, and setting margin requirements. Critical information for price risk management on the lumber market can be gained by lumber market participants from the housing market. For forest management decisions by landowners, giving close attention to housing market would provide valuable information on the appropriate time for timber harvesting, because changes in the housing market affect lumber price that will indirectly affect the demand for timber, which is the most important factor of production for lumber mills.

In this article, we present a model and estimates of US import demand for softwood plywood from Brazil, Canada, Chile, and China using a cointegration framework. We find evidence of long-run cointegration for time series variables in US import demand functions from Brazil, Canada, and China but not from Chile. The short-run own price elasticity estimates of US import demand from Brazil, Canada, Chile, and China are at –0.53, –0.80, –0.82, and –0.91, respectively. The estimates of long-run price elasticity suggest that US import demand for softwood plywood from the three countries is more sensitive to softwood plywood price change.

No abstract