Despite the severe threats to plant habitats and high levels of extinction risk for plant species in many parts of the world, plant conservation priorities are often poorly represented in national and global frameworks because of a lack of data in an accessible and consistent format to inform conservation decision making. The Important Plant Areas (IPAs) criteria system offers a pragmatic yet scientifically rigorous means of delivering these datasets, enabling informed national-or regional-scale conservation prioritisation, and contributing significantly towards global prioritisation systems including the International Union for Conservation of Nature Key Biodiversity Areas (KBAs) Standard. In this paper, we review the IPA rationale and progress on IPA identification to date, including the perceived limitations of the process and how these may be overcome. We then present a revised set of criteria for use globally, developed through the combined experiences of IPA -017-1336-6 identification over the past decade and a half and through a recent global consultation process. An overview of how the revised IPA criteria can work alongside the newly published KBA Standard is also provided. IPA criteria are based around a sound, scientific, global framework which acknowledges the practical problems of gathering plant and habitat data in many regions of the world, and recognises the role of peer reviewed expert opinion in the selection process. National and sub-national engagement in IPA identification is essential, providing a primary route towards long term conservation of key sites for plant diversity. The IPA criteria can be applied to the conservation of all organism groups within the plant and fungal kingdoms.
Ecological restoration has a paradigm of re-establishing 'indigenous reference' communities. One resulting concern is that focussing on target communities may not necessarily create systems which function at a high level or are resilient in the face of ongoing global change. Ecological complexity -defined here, based on theory, as the number of components in a system and the number of connections among themprovides a complementary aim, which can be measured directly and has several advantages. Ecological complexity encompasses key ecosystem variables including structural heterogeneity, trophic interactions and functional diversity. Ecological complexity can also be assessed at the landscape scale, with metrics including β diversity, heterogeneity among habitat patches and connectivity. Thus, complexity applies, and can be measured, at multiple scales. Importantly, complexity is linked to system emergent properties, e.g. ecosystem functions and resilience, and there is evidence that both are enhanced by complexity. We suggest that restoration ecology should consider a new paradigm to restore complexity at multiple scales, in particular of individual ecosystems and across landscapes. A complexity approach can make use of certain current restoration methods but also encompass newer concepts such as rewilding. Indeed, a complexity goal might in many cases best be achieved by interventionist restoration methods. Incorporating complexity into restoration policies could be quite straightforward. Related aims such as enhancing ecosystem services and ecological resilience are to the fore in initiatives such as the Sustainable Development Goals and the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services. Implementation in policy and practice will need the development of complexity metrics that can be applied at both local and regional scales. Ultimately, the adoption of an ecological complexity paradigm will be based on an acceptance that the ongoing and unprecedented global environmental change requires new ways of doing restoration that is fit for the future.
This article examines the policy change process that resulted in the current sugar-sweetened beverages taxes in Mexico and Chile, using the Kaleidoscope Model for Policy Change, a framework developed for nutrition and food policy change analysis. We used a qualitative study design, including 24 key informant (KI) interviews (16 researchers, 5 civil society representatives and 3 food/beverage industry representatives), encompassing global and in-country perspectives. The analysis shows concurrence with the Kaleidoscope Model, highlighting commonalities in the policy change process. These included the importance of focusing events and coalitions for agenda-setting. Both top-down executive leadership and bottom-up pressure from civil society coalitions were important for the policy adoption as were flexible framing of the tax, and taking advantage of windows of opportunity. In both countries, the tax resulted from national, revenue-seeking fiscal reforms and in sub-optimal tax rates, as a result of the industry influence. KIs also discussed emerging evaluation results, highlighting differences in interpretation concerning the magnitude of change from the tax, and shared potential modifications to the current policies. This analysis contributes to a greater understanding of the policy change process focused on obesity prevention, using an innovative theoretical framework developed specifically for food and nutrition policy.
Abstract. In this paper we present BurstProbe, a new technique to accurately measure link burstiness in a wireless sensor network employed for time-critical data delivery. Measurement relies on shared probing slots that are embedded in the transmission schedule and used by nodes to assess link burstiness over time. The acquired link burstiness information can be stored in the node's ash memory and relied upon to diagnose transmission problems when missed deadlines occur. Thus, accurate diagnosis is achieved in a distributed manner and without the overhead of transmitting rich measurement data to a central collection point. For the purpose of evaluation we have implemented BurstProbe in the GinMAC WSN protocol and we are able to demonstrate it is an accurate tool to debug time-critical data delivery. In addition, we analyze the cost of implementing BurstProbe and investigate its eectiveness.
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