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AbstractAlthough canopy height has long been a focus of interest in ecology, it has remained difficult to study at large spatial scales. Recently, satellite‐borne LiDAR equipment produced the first systematic high resolution maps of vegetation height worldwide. Here we show that this new resource reveals three marked modes in tropical canopy height ~40, ~12, and ~2 m corresponding to forest, savanna, and treeless landscapes. The distribution of these modes is consistent with the often hypothesized forest‐savanna bistability and suggests that both states can be stable in areas with a mean annual precipitation between ~1,500 and ~2,000 mm. Although the canopy height states correspond largely to the much discussed tree cover states, there are differences, too. For instance, there are places with savanna‐like sparse tree cover that have a forest‐like high canopy, suggesting that rather than true savanna, those are thinned relicts of forest. This illustrates how complementary sets of remotely sensed indicators may provide increasingly sophisticated ways to study ecological phenomena at a global scale.

Changes in weather patterns pose a threat to the serviceability and long-term performance of roads, and porous asphalt (PA) roads are particularly sensitive to the freezing-thawing (FT) phenomenon. The main objective of this research is to assess the impact of climate change, particularly freezing and thawing cycles, on PA. Climate models predict changes in air temperature, not pavement temperature. To predict the climate change impact on pavements performance, this requires first establishing a relationship between air and road temperature and a correlation between pavement performance and FT cycles. This project focuses on the Netherlands, where PA pavement use has become mandatory, and recent severe winters have increased the discussion about the cold weather performance of porous asphalt and the potential challenges of changing winter weather patterns. When considering long-term changes in climate, the cost impacts of freeze-thaw on PA pavement are predicted to vary regionally and in most areas reach a point in the middle of the century when a reactive wait-and-see approach is more advantageous than proactive adaptation. Further research is suggested to refine the relationship between observed damage and freeze-thaw impacts on PA pavement.

In cold regions, the occurrence of frozen ground has a fundamental control over the character of the water cycle. To investigate the impact of changing ground temperature conditions on hydrological processes in the context of climate change, a distributed hydrological model with an explicit frozen ground module was applied to an alpine watershed in the upstream area of the Hei'he River in the Qilian Mountains, northwest China. After evaluating the base model, we considered scenarios of frost-free ground and climate change. Results showed that the base model with a frozen ground module successfully captured the water balance and thermal regimes in the basin. When the frozen ground module was turned off, the simulated groundwater recharge and base flow increased by a factor of two to three because surface runoff caused by exceeding infiltration capacities at high elevations, which occurred in the base model, was eliminated. Consequently, the river hydrograph became smoother and flatter, with summer flood peaks delayed and reduced in volume. The annual mean depth where subsurface runoff was generated, was about 2.4m compared to 1.1m in the base model. For a warming climate, a combination of increasing evapotranspiration and reducing permafrost area results in smoother and flatter hydrographs, and a reduction in total river discharge. Although our analysis using numerical models has its limitations, it still provides new quantitative understanding of the influences of frozen ground and climate change on hydrological processes in an alpine watershed.

The literature on real options shows that irreversibilities, uncertainties about future benefits and costs, and the flexibility in decision making generate benefits and costs of delaying immediate action. When applied to government policy making, real option models can lead to efficient policies that take full account of these trade-offs, but they can also cause strategic behavior that tries to delay policies through influencing important elements such as downside risks. This contribution reviews the latest developments in real option–based policy research by looking at what we know about the benefits from waiting (the good), the costs from waiting (the bad), and how strategic behavior can influence policies (the ugly). Much has been said in the literature about the good and the bad, but more work is needed to study the ugly aspects of real option–driven policies.

Water quality agencies and scientists are increasingly adopting standardized sampling methodologies because of the challenges associated with interpreting data derived from dissimilar protocols. Here, we compare 13 protocols for monitoring streams from different regions and countries around the globe. Despite the spatially diverse range of countries assessed, many aspects of bioassessment structure and protocols were similar, thereby providing evidence of key characteristics that might be incorporated in a global sampling methodology. Similarities were found regarding sampler type, mesh size, sampling period, subsampling methods, and taxonomic resolution. Consistent field and laboratory methods are essential for merging data sets collected by multiple institutions to enable large-scale comparisons. We discuss the similarities and differences among protocols and present current trends and future recommendations for monitoring programs, especially for regions where large-scale protocols do not yet exist. We summarize the current state in one of these regions, Latin America, and comment on the possible development path for these techniques in this region. We conclude that several aspects of stream biomonitoring need additional performance evaluation (accuracy, precision, discriminatory power, relative costs), particularly when comparing targeted habitat (only the commonest habitat type) versus site-wide sampling (multiple habitat types), appropriate levels of sampling and processing effort, and standardized indicators to resolve dissimilarities among biomonitoring methods. Global issues such as climate change are creating an environment where there is an increasing need to have universally consistent data collection, processing and storage to enable large-scale trend analysis. Biomonitoring programs following standardized methods could aid international data sharing and interpretation.

Despite suffering significantly from the adverse impacts of climate change and human-induced hazards, many people at risk deliberately choose not to migrate from hazard-prone areas in coastal Bangladesh. As many of them encounter significant challenges in maintaining their livelihoods, ascertaining how and under what circumstances voluntary non-migration decisions occur is crucial. Only a handful of studies have investigated whether individuals and groups who decide to stay put in the face of climatic hazards consider their decision to be an adaptive action. In this regard, this study contributes to the existing literature by empirically investigating the voluntary non-migration decision as an adaptation strategy through an exploration of the factors affecting this decision. We employed a systematic random sampling technique and selected 627 respondents from two climatic hazard-prone coastal districts: Khulna and Satkhira. Using the Generalized Structural Equation Model (GSEM), we found that voluntary non-migrants (84% of total respondents) appeared to enjoy the significant advantage of access to their communities' basic need provision and social support. Furthermore, the social, psychological, and economic opportunities found at their existing location (e.g., better income prospects, affordable living costs, receipt of financial help during post-disaster periods, and skills allowing them to stay in that location), as well as their access to local natural resources, strengthened their social capital and thus influenced their desire to stay. Together, these factors enhanced people's adaptability to climatic shocks and motivated them to choose voluntary non-migration as an adaptation option.

Droughts have increased in frequency, duration, and severity across most of the tropics but their effect on forest communities remain not fully understood. Here we assessed the effects of a severe El Niño-induced drought event on dominant and low abundance understory plant species and the consequent impacts on ecosystem functions in the South American Atlantic Forest. We established 20 permanent plots with contrasting vegetation structure and topography. In each plot, we measured the stem diameter at breast height (DBH) of every understory woody plant (i.e. 1 to 10 cm stem diameter) before and after a severe 4-year drought event to calculate relative growth and mortality rates after drought. Litter biomass, litter nutrient content and soil nutrients, as well as tree canopy cover, were also quantified. High stem density reduced survival to drought for both dominant and low abundance understory woody species. The growth rate of dominant and low abundance species was lower on steeper slopes during the drought. Dominant species were the main contributor of litter biomass production whereas low abundance species were important drivers of litter quality. Overall, our findings suggest that habitats with low tree density and larger trees on flat areas, such as in valleys, can act as refuges for understory plant species during drought periods. These habitats are resource-rich, providing nutrients and water during unfavorable drought periods and might improve forest resilience to climate change in the long term.