How do practitioners characterize land tenure security?

Improving land tenure security (LTS) is a significant challenge for sustainable development. The Sustainable Development Goals and other recent global initiatives have renewed and increased the need to improve LTS to address climate change, biodiversity loss, food security, poverty reduction, and other challenges. At the same time, policymakers are increasingly interested in evidence- based policies and decisions, creating urgency for practitioners and researchers to work together. Yet, incongruent characterizations of LTS (identifying the key components of LTS) by practitioners and researchers can limit collaboration and information flows necessary for research and effective policymaking. While there are systematic reviews of how LTS is characterized in the academic literature, no prior study has assessed how practitioners characterize LTS. We address this gap using data from 54 interviews of land tenure practitioners working in 10 countries of global importance for biodiversity and climate change mitigation. Practitioners characterize LTS as complex and multifaceted, and a majority of practitioners refer to de jure terms (e.g., titling) when characterizing it. Notably, in our data just one practitioner characterized LTS in terms of perceptions of the landholder, contrasting the recent emphasis in the academic literature on landholder perceptions in LTS characterizations. Researchers should be aware of incongruence in how LTS is characterized in the academic literature when engaging practitioners.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/155485/1/csp2186.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/155485/2/csp2186_am.pd

Learning Agile Soccer Skills for a Bipedal Robot with Deep Reinforcement Learning

We investigate whether Deep Reinforcement Learning (Deep RL) is able to synthesize sophisticated and safe movement skills for a low-cost, miniature humanoid robot that can be composed into complex behavioral strategies in dynamic environments. We used Deep RL to train a humanoid robot with 20 actuated joints to play a simplified one-versus-one (1v1) soccer game. We first trained individual skills in isolation and then composed those skills end-to-end in a self-play setting. The resulting policy exhibits robust and dynamic movement skills such as rapid fall recovery, walking, turning, kicking and more; and transitions between them in a smooth, stable, and efficient manner - well beyond what is intuitively expected from the robot. The agents also developed a basic strategic understanding of the game, and learned, for instance, to anticipate ball movements and to block opponent shots. The full range of behaviors emerged from a small set of simple rewards. Our agents were trained in simulation and transferred to real robots zero-shot. We found that a combination of sufficiently high-frequency control, targeted dynamics randomization, and perturbations during training in simulation enabled good-quality transfer, despite significant unmodeled effects and variations across robot instances. Although the robots are inherently fragile, minor hardware modifications together with basic regularization of the behavior during training led the robots to learn safe and effective movements while still performing in a dynamic and agile way. Indeed, even though the agents were optimized for scoring, in experiments they walked 156% faster, took 63% less time to get up, and kicked 24% faster than a scripted baseline, while efficiently combining the skills to achieve the longer term objectives. Examples of the emergent behaviors and full 1v1 matches are available on the supplementary website.Comment: Project website: https://sites.google.com/view/op3-socce

Progress report of the Fort Peck Reservoir fishery survey.

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Snowmobiles and off road vehicles in Montana : a review of literature /

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Draft environmental statement : addendum number one to project no. FG-22, annual statewide harvest of big game animals /

ADDEN

Idaho Habitat Evaluation for Off-Site Mitigation Record : Annual Report 1987.

The Idaho Department of Fish and Game has been monitoring and evaluating existing and proposed habitat improvement projects for steelhead (Salmo gairdneri) and chinook salmon (Oncorhynchus tshawytscha) in the Clearwater and Salmon River drainages over the last four years. Projects included in the evaluation are funded by, or proposed for funding by, the Bonneville Power Administration (BPA) under the Northwest Power Planning Act as off-site mitigation for downstream hydropower development on the Snake and Columbia rivers. A mitigation record is being developed to use increased smolt production at full seeding as the best measure of benefit from a habitat enhancement project. Determination of full benefit from a project depends on presence of adequate numbers of fish to document actual increases in fish production. The depressed nature of upriver anadromous stocks have precluded attainment of full benefit of any habitat project in Idaho. Partial benefit will be credited to the mitigation record in the interim period of run restoration. According to the BPA Work Plan, project implementors have the primary responsibility for measuring physical habitat and estimating habitat change. To date, Idaho habitat projects have been implemented primarily by the US Forest Service (USFS). The Shoshone-Bannock Tribes (SBT) have sponsored three projects (Bear Valley Mine, Yankee Fork, and the proposed East Fork Salmon River projects). IDFG implemented two barrier-removal projects (Johnson Creek and Boulder Creek) that the USFS was unable to sponsor at that time. The role of IDFG in physical habitat monitoring is primarily to link habitat quality and habitat change to changes in actual, or potential, fish production. Individual papers were processed separately for the data base

Transnational organized crime

Marine biodiversity and fisheries operate in 3D dynamic space while UNCLOS jurisdictions are mainly based on 2D boundaries, challenging space-based governance. Spatial dimensions of fisheries governance become explicit in space–time operational restrictions in a system aiming at conserving fishery resources by maintaining stocks maximum sustainable yield level. Environmental governance uses Marine Protected Areas as a main measure for conserving biological diversity and aims at covering 10% of the world oceans by 2020. This target and the issue of no-take MPAs have been a source of tension between the two streams of governance. The chapter considers spatial governance in fisheries and biodiversity conservation, the impacts of the terrestrial heritage of conservation, the spatio-temporal issues in both governance fields and the potential offered by spatially structured multiuse integrated management frameworks. It concludes that the spatial dimensions of both governance streams and the similarity of issues arising from an increasing range of human uses and impacts would require an effective integrated approach to spatial and temporal management