Cross-country risk quantification of extreme wildfires in Mediterranean Europe

We estimate the country-level risk of extreme wildfires defined by burned area (BA) for Mediterranean Europe and carry out a cross-country comparison. To this end, we avail of the European Forest Fire Information System (EFFIS) geospatial data from 2006 to 2019 to perform an extreme value analysis. More specifically, we apply a point process characterization of wildfire extremes using maximum likelihood estimation. By modeling covariates, we also evaluate potential trends and correlations with commonly known factors that drive or affect wildfire occurrence, such as the Fire Weather Index as a proxy for meteorological conditions, population density, land cover type, and seasonality. We find that the highest risk of extreme wildfires is in Portugal (PT), followed by Greece (GR), Spain (ES), and Italy (IT) with a 10-year BA return level of 50'338 ha, 33'242 ha, 25'165 ha, and 8'966 ha, respectively. Coupling our results with existing estimates of the monetary impact of large wildfires suggests expected losses of 162–439 million € (PT), 81–219 million € (ES), 41–290 million € (GR), and 18–78 million € (IT) for such 10-year return period events.

SUMMARY

We model the risk of extreme wildfires for Italy, Greece, Portugal, and Spain in form of burned area return levels, compare them, and estimate expected losses.     

Tuning and Practicing the Therapeutic Instrument: The Therapist's Life Experience

This article views the therapeutic use of self broadly as if through a wide-angle lens focusing on the therapist within his or her surroundings. These contextual features can be seen as projections of the therapist's self and therefore useable in treatment. Through an interest in alternative brain functions due to her own struggles with a neurological illness, the author arrived at the idea of utilizing her personal interests which naturally come into the milieu as therapeutic vehicles. Personal interests that are compatible with the patient's character offer alternative modes for experiencing, expressing and regulating affect states. These interests in the expressive arts together with the person of the therapist constitute a medium for rotating attention around unfamiliar parts of the mental landscape. Disavowed or dissociated affects can be unearthed, made conscious, put into language, and treated. This idea in practice nests neatly within recent thinking in psychoanalysis, neuroscience, and the philosophy of science. When language alone is not enough to move the therapeutic process forward, other working knowledge in the therapist's life can be brought to bear as a powerful evocative force for therapeutic change.     

Guinea Pigs on the payroll: The ethics of paying research subjects

Regulatory bodies and scholars have traditionally conceptualized biomedical research on healthy subjects in the same way as research on patients. Guidelines and regulations have portrayed payment to a healthy subject as a potential constraint, or “undue influence,”; on the subject's free consent. In this essay we suggest an alternative way of conceptualizing research on healthy subjects, which sees the basic issue not as one of undue influence but as one of justice. Healthy subjects generally enroll in research protocols not for humanitarian reasons but for the money they will receive. Many of these protocols are conducted by profit‐driven corporations. Yet current guidelines and regulations prohibit subjects from negotiating for fair payment for the risks, discomforts and inconveniences they undergo, and IRBs are not staffed adequately to monitor the subject's safety. We propose to remedy the situation by regulating payment to healthy subjects as a labor relation.     

Data-Intensive Science and Research Integrity

In this commentary, we consider questions related to research integrity in data-intensive science and argue that there is no need to create a distinct category of misconduct that applies to deception related to processing, analyzing, or interpreting data. The best way to promote integrity in data-intensive science is to maintain a firm commitment to epistemological and ethical values, such as honesty, openness, transparency, and objectivity, which apply to all types of research, and to promote education, policy development, and scholarly debate concerning appropriate uses of statistics.