Modification of forests by people means only 40% of remaining forests have high ecosystem integrity

Many global environmental agendas, including halting biodiversity loss, reversing land degradation, and limiting climate change, depend upon retaining forests with high ecological integrity, yet the scale and degree of forest modification remain poorly quantified and mapped. By integrating data on observed and inferred human pressures and an index of lost connectivity, we generate a globally consistent, continuous index of forest condition as determined by the degree of anthropogenic modification. Globally, only 17.4 million km2 of forest (40.5%) has high landscape-level integrity (mostly found in Canada, Russia, the Amazon, Central Africa, and New Guinea) and only 27% of this area is found in nationally designated protected areas. Of the forest inside protected areas, only 56% has high landscape-level integrity. Ambitious policies that prioritize the retention of forest integrity, especially in the most intact areas, are now urgently needed alongside current efforts aimed at halting deforestation and restoring the integrity of forests globally

Anthropogenic modification of forests means only 40% of remaining forests have high ecosystem integrity

Many global environmental agendas, including halting biodiversity loss, reversing land degradation, and limiting climate change, depend upon retaining forests with high ecological integrity, yet the scale and degree of forest modification remain poorly quantified and mapped. By integrating data on observed and inferred human pressures and an index of lost connectivity, we generate a globally consistent, continuous index of forest condition as determined by the degree of anthropogenic modification. Globally, only 17.4 million km2 of forest (40.5%) has high landscape-level integrity (mostly found in Canada, Russia, the Amazon, Central Africa, and New Guinea) and only 27% of this area is found in nationally designated protected areas. Of the forest inside protected areas, only 56% has high landscape-level integrity. Ambitious policies that prioritize the retention of forest integrity, especially in the most intact areas, are now urgently needed alongside current efforts aimed at halting deforestation and restoring the integrity of forests globally

Equitable and effective area‐based conservation: towards the conserved areas paradigm

In 2018, the Parties to the Convention on Biological Diversity (CBD) adopted a decision on protected areas and other effective area-based conservation measures (OECMs). It contains the definition of an OECM and related scientific and technical advice that has broadened the scope of governance authorities and areas that can be engaged and recognised in global conservation efforts. The voluntary guidance on OECMs and protected areas, also included in the decision, promotes the use of diverse, effective and equitable governance models, the integration of protected areas and OECMs into wider landscapes and seascapes, and mainstreaming of biodiversity conservation across sectors. Taken as a whole, the advice and voluntary guidance provides further clarity about the CBD Parties’ understanding of what constitutes equitable and effective area-based conservation measures within and beyond protected areas and provides standardised criteria with which to measure and report areas’ attributes and performance. This policy perspective suggests that this CBD decision represents further evidence of the evolution from the ‘new paradigm for protected areas’ to a broader ‘conserved areas paradigm’ that embodies good governance, equity and effective conservation outcomes and is inclusive of a diversity of contributions to conservation within and beyond protected areas

An Electronic Performance Support System Based on a Hybrid Content-Collaborative Recommender System

An Electronic Performance Support System (EPSS) introduces challenges on contextualized and personalized information delivery. Recommender systems aim at delivering and suggesting relevant information according to users preferences, thus EPSSs could take advantage of the recommendation algorithms that have the effect of guiding users in a large space of possible options. The JUMP project(1) aims at integrating an EPSS with a hybrid recommender system. Collaborative and content-based filtering are the recommendation techniques most widely adopted to date. The main contribution of this paper is a content-collaborative hybrid recommender which computes similarities between users relying on their content-based profiles in which user preferences are stored, instead of comparing their rating styles. A distinctive feature of our system is that a statistical model of the user interests is obtained by machine learning techniques integrated with linguistic knowledge contained in WordNet. This model, named "semantic user profile", is exploited by the hybrid recommender in the neighborhood formation process

Proceedings of the ACM Recommender Systems 2012 Workshop on Human Decision Making in Recommender Systems (Decisions@RecSys 2012)

Interacting with a recommender system means to take different decisions such as selecting a song/movie from a recommendation list, selecting specific feature values (e.g., camera’s size, zoom) as criteria, selecting feedback features to be critiqued in a critiquing based recommendation session, or selecting a repair proposal for inconsistent user preferences when interacting with a knowledge-based recommender. In all these scenarios, users have to solve a decision task. The complexity of decision tasks, limited cognitive resources of users, and the tendency to keep the overall decision effort as low as possible lead to the phenomenon of bounded rationality, i.e., users exploit decision heuristics rather than trying to take an optimal decision. Furthermore, preferences of users will likely change throughout a recommendation session, i.e., preferences are constructed in a specific decision environment and users do not know their preferences beforehand. Decision making under bounded rationality is a door opener for different types of non-conscious influences on the decision behavior of a user. Theories from decision psychology and cognitive psychology are trying to explain these influences, for example, decoy effects and defaults can trigger significant shifts in item selection probabilities; in group decision scenarios, the visibility of the preferences of other group members can have a significant impact on the final group decision. The major goal of this workshop was to establish a platform for industry and academia to present and discuss new ideas and research results that are related to the topic of human decision making in recommender systems. The workshop consisted of technical sessions in which results of ongoing research as reported in these proceedings were presented, a keynote talk given by Joseph A. Konstan on “Decision-Making and Recommender Systems: Failures, Successes, and Research Directions” and a wrap up session chaired by Alexander Felfernig