Suchergebnisse

As the global environmental crisis grows in scale and complexity, conservation professionals and policymakers are increasingly called upon to make decisions despite high levels of uncertainty, limited resources, and insufficient data. Global efforts to protect biodiversity in areas beyond national jurisdiction require substantial international cooperation and negotiation, both of which are characterized by unpredictability and high levels of uncertainty. Here we build on recent studies to adapt forecasting techniques from the fields of hazard prediction, risk assessment, and intelligence analysis to forecast the likelihood of marine protected area (MPA) designation in the Southern Ocean. We used two questionnaires, feedback, and a discussion round in a Delphi-style format expert elicitation to obtain forecasts, and collected data on specific biophysical, socioeconomic, geopolitical, and scientific factors to assess how they shape and influence these forecasts. We found that areas further north along the Western Antarctic Peninsula were considered to be less likely to be designated than areas further south, and that geopolitical factors, such as global politics or events, and socioeconomic factors, such as the presence of fisheries, were the key determinants of whether an area was predicted to be more or less likely to be designated as an MPA. Forecasting techniques can be used to inform protected area design, negotiation, and implementation in highly politicized situations where data is lacking by aiding with spatial prioritization, targeting scarce resources, and predicting the success of various spatial arrangements, interventions, or courses of action.

As the global environmental crisis grows in scale and complexity, conservation professionals and policymakers are increasingly called upon to make decisions despite high levels of uncertainty, limited resources, and insufficient data. Global efforts to protect biodiversity in areas beyond national jurisdiction require substantial international cooperation and negotiation, both of which are characterized by unpredictability and high levels of uncertainty. Here we build on recent studies to adapt forecasting techniques from the fields of hazard prediction, risk assessment, and intelligence analysis to forecast the likelihood of marine protected area (MPA) designation in the Southern Ocean. We used two questionnaires, feedback, and a discussion round in a Delphi format expert elicitation to obtain forecasts, and collected data on specific biophysical, socioeconomic, geopolitical, and scientific factors to assess how they shape and influence these forecasts. We found that areas further north along the Western Antarctic Peninsula were considered to be less likely to be designated than areas further south, and that geopolitical factors, such as global politics or events, and socioeconomic factors, such as the presence of fisheries, were the key determinants of whether an area was predicted to be more or less likely to be designated as an MPA. Forecasting techniques can be used to inform protected area design, negotiation, and implementation in highly politicized situations where data is lacking by aiding with spatial prioritization, targeting scarce resources, and predicting the success of various spatial arrangements, interventions, or courses of action.

More than two decades of deconstruction, renovation, and reconstruction have left the urban environments in the former German Democratic Republic completely transformed. This volume considers the changing urban landscapes in the former East — and how the filling of previous absences and the absence of previous presence — creates the cultural landscape of modern unified Germany. This broadens our understanding of this transformation by examining often-neglected cities, spaces, or structures, and historical narration and preservation.

Adverse posttraumatic neuropsychiatric sequelae (APNS) are common among civilian trauma survivors and military veterans. These APNS, as traditionally classified, include posttraumatic stress, post-concussion syndrome, depression, and regional or widespread pain. Traditional classifications have come to hamper scientific progress because they artificially fragment APNS into siloed, syndromic diagnoses unmoored to discrete components of brain functioning and studied in isolation. These limitations in classification and ontology slow the discovery of pathophysiologic mechanisms, biobehavioral markers, risk prediction tools, and preventive/treatment interventions. Progress in overcoming these limitations has been challenging, because such progress would require studies that both evaluate a broad spectrum of posttraumatic sequelae (to overcome fragmentation) and also perform in-depth biobehavioral evaluation (to index sequelae to domains of brain function). This article summarizes the methods of the Advancing Understanding of RecOvery afteR traumA (AURORA) Study. AURORA conducts a large scale (n = 5,000 target sample) in-depth assessment of APNS development using a state-of-the-art battery of self-report, neurocognitive, physiologic, digital phenotyping, psychophysical, neuroimaging, and genomic assessments, beginning in the early aftermath of trauma and continuing for one year. The goals of AURORA are to achieve improved phenotypes, prediction tools, and understanding of molecular mechanisms to inform the future development and testing of preventive and treatment interventions.

Adverse posttraumatic neuropsychiatric sequelae (APNS) are common among civilian trauma survivors and military veterans. These APNS, as traditionally classified, include posttraumatic stress, postconcussion syndrome, depression, and regional or widespread pain. Traditional classifications have come to hamper scientific progress because they artificially fragment APNS into siloed, syndromic diagnoses unmoored to discrete components of brain functioning and studied in isolation. These limitations in classification and ontology slow the discovery of pathophysiologic mechanisms, biobehavioral markers, risk prediction tools, and preventive/treatment interventions. Progress in overcoming these limitations has been challenging because such progress would require studies that both evaluate a broad spectrum of posttraumatic sequelae (to overcome fragmentation) and also perform in-depth biobehavioral evaluation (to index sequelae to domains of brain function). This article summarizes the methods of the Advancing Understanding of RecOvery afteR traumA (AURORA) Study. AURORA conducts a large-scale (n = 5000 target sample) in-depth assessment of APNS development using a state-of-the-art battery of self-report, neurocognitive, physiologic, digital phenotyping, psychophysical, neuroimaging, and genomic assessments, beginning in the early aftermath of trauma and continuing for 1 year. The goals of AURORA are to achieve improved phenotypes, prediction tools, and understanding of molecular mechanisms to inform the future development and testing of preventive and treatment interventions.