Community-based Adaptation: Lessons from the Development Marketplace 2009 on Adaptation to Climate Change

The Development Marketplace 2009 focused on adaptation to climate change. This paper identifies lessons from the Marketplace and assesses their implications for adaptation support. Our findings are based on: statistical tabulation of all proposals; in-depth qualitative and quantitative analysis of the 346 semi-finalists; and interviews with finalists and assessors. Proposals were fuelled by deep concerns that ongoing climate change and its impacts undermine development and exacerbate poverty, migration and food insecurity. Proposals addressed both local poverty and climate change challenges, and offered a wide range of approaches to render local development more resilient to current climate variability. Therefore, support to community-based adaptation should: exploit its strong local grounding and synergies with development; help connect local initiatives to higher levels; and use complementary approaches to address policy issues.Community-based Adaptation, Development Marketplace, Adaptation, Climate Change

COVID-19 and lessons from multi-hazard early warning systems

Having a common framework for early action to cope with complex disasters can make it easier for authorities and other stakeholders, including populations at risk, to understand the full spectrum of secondary and tertiary effects and thus where to focus preparedness efforts, and how best to provide more targeted warnings and response services. Meteorological and hydrological services world-wide have developed and implemented Multi-Hazard Early Warning Systems (MHEWS) for weather and climate related hazards that are now being expanded and transitioned towards Multi-Hazard Impact-based Early Warning Systems (MHIEWS). While it is still early days it is becoming clear that there are useful lessons from this approach in the COVID-19 global pandemic, and some valuable insight to be gained in risk communication, risk analysis and monitoring methodologies and approaches. The ability to understand and respond effectively to warnings through appropriate behaviours and actions is central to resilient societies and communities. By avoiding physical, societal and economic harm to the greatest extent possible, recovery from a hazard is likely to be faster, less costly and more complete. MHIEWS can be a common approach for all hazards and therefore more likely to become a trusted tool that everyone can understand and use as a basic element of their national disaster risk management system. The interconnectedness of hazards and their impacts is a strong motivator for a common approach. One of the lessons from the COVID-19 pandemic and extreme weather events is the need to understand the vulnerability of individuals, communities and societies so as to provide reliable, targeted guidance and warnings and the willingness and capacity to prepare for a reasonable worst-case scenario based on informed long-term planning. Meteorology and hydrology are making good progress in this direction and the process can be readily applied to health and other sectors

Book Review: Sustainable Development or Malignant Growth? Perspectives of Pacific Island Women

No abstract availabl

Book Review: Pacific Platform for Action - Rethinking Sustainable Development for Pacific Women Towards the Year 2000

No abstract availabl

Community-based Adaptation: Lessons from the Development Marketplace 2009 on Adaptation to Climate Change

The Development Marketplace 2009 focused on adaptation to climate change. This paper identifies lessons from the Marketplace and assesses their implications for adaptation support. Our findings are based on: statistical tabulation of all proposals; in-depth qualitative and quantitative analysis of the 346 semi-finalists; and interviews with finalists and assessors. Proposals were fuelled by deep concerns that ongoing climate change and its impacts undermine development and exacerbate poverty, migration and food insecurity. Proposals addressed both local poverty and climate change challenges, and offered a wide range of approaches to render local development more resilient to current climate variability. Therefore, support to community-based adaptation should: exploit its strong local grounding and synergies with development; help connect local initiatives to higher levels; and use complementary approaches to address policy issues

Deriving functional types for rainforest trees

A common goal in functional type research is to find a useful classification that defines the dynamic behaviour of groups of species in relation to environmental variation. Long-term data sets on the dynamics of forests are difficult to obtain; thus, it would be useful if more readily available data, such as that on morphological and life history characters, could be used to derive groups that reflect the dynamics of the species. We used a 30-yr data set on the dynamics of subtropical rainforests in Australia to derive classification based on the dynamics of the species and compared this classification with groups of species derived by other approaches. Functional types were derived for ca. 80 tree species using subjective, deductive and data-driven approaches. The subjective classification used was a pioneer to late successional grouping. The deductive classification was an extension of the vital attribute approach. Two data sets were used for the data-based classifications, one based on morphological, life history and phenological characters (morphological data) readily available from taxonomic descriptions and another based on long-term observations on the establishment, growth and death of all individuals on permanent plots (dynamic data). SAHN (Sequential, Agglomerative, Hierarchical and Nested) clustering techniques were used for the numerical classifications. There was some similarity between the classification based on dynamic characters and the subjective and deductive classifications. The classification based on the readily available morphological characters showed less similarity with other classifications. However, the morphological data could be used to predict group membership in the dynamic classification using discriminant analysis with 87% accuracy. Thus, it appears that surrogate classifications might be found to describe the dynamics of the subtropical rainforest site. Further exploration and testing at other sites is required, especially to link the functional classification to specific perturbations

The effect of spatial scale on evenness

The effect of spatial scale on species evenness has not previously been investigated. As the area of each sample of vegetation (i.e. the spatial grain) increases, evenness could in theory increase, decrease, or stay the same, though the simplest model predicts an increase. We use biomass data from four dune slack sites and two semi-arid grasslands, sampled to allow calculation of evenness at a range of spatial grains. In all six sites, evenness decreases as grain size increases, almost monotonically. It is hypothesized that such a pattern is a result of a general feature of plant species abundance distributions and of vegetation response to environmental microheterogeneity