Eight Perspectives on Yvon Neptune v. Haiti

Yvon Neptune v. Haiti is a noteworthy decision of the Inter- American Court of Human Rights, with potentially wide-ranging impacts. The Court ordered a wholesale change in the Haitian prison system in order to prevent Haiti from violating former Haitian Prime Minister Yvon Neptune\u27s rights again. Haiti violated Articles 1 (obligation to respect rights), 5 (humane treatment), 7 (personal liberty), 8 (fair trial) and 25 (the right to judicial protection) of the American Convention on Human Rights. Haitian and U.S. human rights groups worked together with a virtual human rights clinic to trigger the decision by filing a petition with the Inter-American Commission of Human Rights. The decision has significance for Yvon Neptune, other Haitian detainees, Haitian activists and attorneys, Haitian government officials, U.S. law students, human rights organizations, foreign governments and international agencies, and the Inter-American Human Rights System generally. While Yvon Neptune is no longer a political prisoner, the decision is only a partial victory because Haiti currently refuses to implement the decision. Yvon Neptune v. Haiti, as a partial victory in the effort to bring rule of law in a transitional justice context, parallels the unfinished state of Haiti\u27s transition to democracy. Further efforts to protect the human rights of Haitian detainees will require the support of many groups, working together, to succeed

War Aims Matter: Keeping Jus Contra Bellum Restrictive While Requiring the Articulation of the Goals of the Use of Force

Exploring the Frontiers of International La

String-localized quantum fields from Wigner representations

In contrast to the usual representations of of the Poincar\'e group of finite spin or helicity the Wigner representations of mass zero and infinite spin are known to be incompatible with pointlike localized quantum fields. We present here a construction of quantum fields associated with these representations that are localized in semi-infinite, space-like strings. The construction is based on concepts outside the realm of Lagrangian quantization with the potential for further applications.Comment: References, some text and an appendix adde

String-localized Quantum Fields and Modular Localization

We study free, covariant, quantum (Bose) fields that are associated with irreducible representations of the Poincar\'e group and localized in semi-infinite strings extending to spacelike infinity. Among these are fields that generate the irreducible representations of mass zero and infinite spin that are known to be incompatible with point-like localized fields. For the massive representation and the massless representations of finite helicity, all string-localized free fields can be written as an integral, along the string, of point-localized tensor or spinor fields. As a special case we discuss the string-localized vector fields associated with the point-like electromagnetic field and their relation to the axial gauge condition in the usual setting.Comment: minor correction

At War’s end: time to turn to Jus Post Bellum’

To be complete

Will Biotic Interactions Ever be Predictable: Insights from Combining Correlational and Process-Based Tree Species Distribution Models

: Predicting how climate change and changes to disturbance regimes will influence forest systems requires understanding abiotic constraints to species fitness as well as biotic interactions such as competition and disease. So far, predictions have been largely based on abiotic conditions because biotic interactions are notoriously difficult to describe and predict. We combine four different distribution modeling approaches on a spectrum from correlational to process-based models to elucidate general patterns of biotic interaction strength that may lay the basis for including biotic interactions in predictive models based on future conditions. We use the phenology-based model Phenofit to derive climatic suitability predictions that are closely related to the fundamental niche of 13 eastern US tree species. Differences between Phenofit models, actual tree distributions from the Forest Inventory and Analysis (FIA) data, and predictions from correlation-based species 10 distribution models using soil, landscape, and climate data (DISTRIB) indicate areas of biotic constraints. Further support for the identification of relative biotic interaction strength comes from the Leaf Area Index of the MAPSS model and from constraints-based distribution models. Finally, we relate the identified distribution and characteristics of putative biotic interactions back to climate so that they become predictable under future conditions

Will Biotic Interactions Ever be Predictable: Insights from Combining Correlational and Process-Based Tree Species Distribution Models

: Predicting how climate change and changes to disturbance regimes will influence forest systems requires understanding abiotic constraints to species fitness as well as biotic interactions such as competition and disease. So far, predictions have been largely based on abiotic conditions because biotic interactions are notoriously difficult to describe and predict. We combine four different distribution modeling approaches on a spectrum from correlational to process-based models to elucidate general patterns of biotic interaction strength that may lay the basis for including biotic interactions in predictive models based on future conditions. We use the phenology-based model Phenofit to derive climatic suitability predictions that are closely related to the fundamental niche of 13 eastern US tree species. Differences between Phenofit models, actual tree distributions from the Forest Inventory and Analysis (FIA) data, and predictions from correlation-based species 10 distribution models using soil, landscape, and climate data (DISTRIB) indicate areas of biotic constraints. Further support for the identification of relative biotic interaction strength comes from the Leaf Area Index of the MAPSS model and from constraints-based distribution models. Finally, we relate the identified distribution and characteristics of putative biotic interactions back to climate so that they become predictable under future conditions