Managing uncertainty in decision-making for conservation science.

Science-based decision-making is the ideal. However, scientific knowledge is incomplete, and sometimes wrong. Responsible science-based policy, planning, and action must exploit knowledge while managing uncertainty. I considered the info-gap method to manage deep uncertainty surrounding knowledge that is used for decision-making in conservation. A central concept is satisficing, which means satisfying a critical requirement. Alternative decisions are prioritized based on their robustness to uncertainty, and critical outcome requirements are satisficed. Robustness is optimized; outcome is satisficed. This is called robust satisficing. A decision with a suboptimal outcome may be preferred over a decision with a putatively optimal outcome if the former can more robustly achieve an acceptable outcome. Many biodiversity conservation applications employ info-gap theory, under which parameter uncertainty but not uncertainty in functional relations is considered. I considered info-gap models of functional uncertainty, widely used outside of conservation science, as applied to conservation of a generic endangered species by translocation to a new region. I focused on 2 uncertainties: the future temperature is uncertain due to climate change, and the shape of the reproductive output function is uncertain due to translocation to an unfamiliar region. The value of new information is demonstrated based on the robustness function, and the info-gap opportuneness function demonstrates the potential for better-than-anticipated outcomes.

Gestión de la incertidumbre en las decisiones para las ciencias de la conservación Resumen Lo ideal es tomar decisiones con base en la ciencia. Sin embargo, el conocimiento científico está incompleto y a veces es incorrecto. Las políticas, planeaciones y acciones responsables basadas en la ciencia deben explotar el conocimiento mientras que gestionan la incertidumbre. Consideré el método de vacío de información para gestionar la incertidumbre profunda en torno al conocimiento usado para las decisiones de conservación. Un concepto central es satisfacción que significa cumplir con un requerimiento crítico. Las decisiones alternativas se priorizan con base en su solidez respecto a la incertidumbre y se cumplen los requerimientos críticos de los resultados. La solidez mejora, el resultado se cumple. A esto se le llama satisfacción sólida. Puede que se prefiera una decisión con un resultado subóptimo por encima de una decisión con un resultado óptimo posible si la primera puede lograr con mayor solidez un resultado aceptable. Muchas aplicaciones de conservación de la biodiversidad usan la teoría del vacío de información, la cual considera la incertidumbre del parámetro, pero no la incertidumbre en las relaciones funcionales. Consideré los modelos de vacío de información en la incertidumbre funcional, usados de forma extensa fuera de las ciencias de la conservación, aplicados a la conservación de una especie genérica amenazada mediante la reubicación a una nueva región. Me enfoqué en dos incertidumbres: la temperatura en el futuro es incierta debido al cambio climático y la forma de la función del rendimiento reproductivo es incierta debido a la reubicación a una región desconocida. El valor de la nueva información queda demostrado con base en la función de la solidez y la función de la conveniencia demuestra el potencial para resultados mejores a lo esperado.

Refugee visa insecurity disrupts the brain's default mode network.

BACKGROUND: Research has largely focused on the psychological consequences of refugee trauma exposure, but refugees living with visa insecurity face an uncertain future that also adversely affects psychological functioning and self-determination. OBJECTIVE: This study aimed to examine how refugee visa insecurity affects the functional brain. METHOD: We measured resting state brain activity via fMRI in 47 refugees with insecure visas (i.e. temporary visa status) and 52 refugees with secure visas (i.e. permanent visa status) residing in Australia, matched on key demographic, trauma exposure and psychopathology. Data analysis comprised independent components analysis to identify active networks and dynamic functional causal modelling tested visa security group differences in network connectivity. RESULTS: We found that visa insecurity specifically affected sub-systems within the default mode network (DMN) - an intrinsic network subserving self-referential processes and mental simulations about the future. The insecure visa group showed less spectral power in the low frequency band in the anterior ventromedial DMN, and reduced activity in the posterior frontal DMN, compared to the secure visa group. Using functional dynamic causal modelling, we observed positive coupling between the anterior and posterior midline DMN hubs in the secure visa group, while the insecure visa group displayed negative coupling that correlated with self-reported fear of future deportation. CONCLUSIONS: Living with visa-related uncertainty appears to undermine synchrony between anterior-posterior midline components of the DMN responsible for governing the construction of the self and making mental representations of the future. This could represent a neural signature of refugee visa insecurity, which is marked by a perception of living in limbo and a truncated sense of the future.

Refugee visa insecurity disrupts default mode network (DMN) connectivity ­ a core network that supports the internal construction of the self.Refugees living with insecure visa status showed decreased connectivity in the DMN and more negative coupling between midline anterior­posterior hubs of the DMN, compared to refugees living with secure visas.Diminished DMN connectivity may represent a neural basis for the psychological effects of refugee visa insecurity, which is associated with prolonged uncertainty regarding the future self and increased risk for psychological distress.

Estimating changes and trends in ecosystem extent with dense time-series satellite remote sensing.

Quantifying trends in ecosystem extent is essential to understanding the status of ecosystems. Estimates of ecosystem loss are widely used to track progress toward conservation targets, monitor deforestation, and identify ecosystems undergoing rapid change. Satellite remote sensing has become an important source of information for estimating these variables. Despite regular acquisition of satellite data, many studies of change in ecosystem extent use only static snapshots, which ignores considerable amounts of data. This approach limits the ability to explicitly estimate trend uncertainty and significance. Assessing the accuracy of multiple snapshots also requires time-series reference data which is often very costly and sometimes impossible to obtain. We devised a method of estimating trends in ecosystem extent that uses all available Landsat satellite imagery. We used a dense time series of classified maps that explicitly accounted for covariates that affect extent estimates (e.g., time, cloud cover, and seasonality). We applied this approach to the Hukaung Valley Wildlife Sanctuary, Myanmar, where rapid deforestation is greatly affecting the lowland rainforest. We applied a generalized additive mixed model to estimate forest extent from more than 650 Landsat image classifications (1999-2018). Forest extent declined significantly at a rate of 0.274%/year (SE = 0.078). Forest extent declined from 91.70% (SE = 0.02) of the study area in 1999 to 86.52% (SE = 0.02) in 2018. Compared with the snapshot method, our approach improved estimated trends of ecosystem loss by allowing significance testing with confidence intervals and incorporation of nonlinear relationships. Our method can be used to identify significant trends over time, reduces the need for extensive reference data through time, and provides quantitative estimates of uncertainty.

Estimación de los Cambios y Tendencias en la Extensión de los Ecosistemas Mediante Teledetección Satelital de Series Temporales Densas Resumen Las tendencias de cuantificación de la extensión de los ecosistemas es esencial para el entendimiento de su estado. Las estimaciones de pérdidas de los ecosistemas se usan con amplitud para rastrear el progreso hacia los objetivos de conservación, monitorear la deforestación e identificar a los ecosistemas que están experimentando un cambio rápido. La teledetección satelital se ha transformado en una fuente importante de información para la estimación de estas variables. A pesar de la obtención de datos satelitales, muchos estudios sobre el cambio en la extensión de los ecosistemas usan solamente capturas estáticas, lo cual ignora cantidades considerables de datos. Esta estrategia limita la habilidad que se tiene para estimar explícitamente la incertidumbre e importancia de la tendencia. La valoración de la precisión de múltiples capturas también requiere datos de referencia de series temporales, lo cual es muy costoso e imposible de conseguir en algunos casos. Diseñamos un método para estimar las tendencias en la extensión de los ecosistemas que usa todas las imágenes satelitales disponibles en Landsat. Usamos una serie temporal densa de los mapas clasificados que considera explícitamente a las covarianzas que afectan a las estimaciones de la extensión (p.ej.: tiempo, cobertura de nubes y estacionalidad). Aplicamos esta estrategia en el Santuario de Vida Silvestre del Valle de Huakaung en Myanmar, en donde la deforestación acelerada está afectando enormemente a la selva de tierras bajas. Aplicamos también un modelo mixto, aditivo y generalizado para estimar la extensión del bosque a partir de más de 650 clasificaciones de imágenes en Landsat (1999 - 2018). La extensión del bosque declinó significativamente a una tasa de 0.274%/año (SE 0.078). La extensión del bosque declinó del 91.70% (SE 0.02) del área de estudio en 1999 a 86.52% (SE 0.02) en 2018. Si la comparamos con la estrategia de las capturas, nuestra estrategia mejoró las tendencias estimadas de la pérdida del ecosistema al permitir la evaluación de significancia con intervalos de confianza y la incorporación de relaciones no lineales. Nuestro método puede usarse para identificar las tendencias significativas a lo largo del tiempo; también reduce la necesidad de tener datos de referencia extensos a lo largo del tiempo y proporciona estimaciones cuantitativas de la incertidumbre.

Uncertainty analysis and robust areas of high and low modeled human impact on the global oceans.

Increasing anthropogenic pressure on marine ecosystems from fishing, pollution, climate change, and other sources is a big concern in marine conservation. Scientists have thus developed spatial models to map cumulative human impacts on marine ecosystems. However, these models are based on many assumptions and incorporate data that suffer from substantial incompleteness and inaccuracies. Rather than using a single model, we used Monte Carlo simulations to identify which parts of the oceans are subject to the most and least impact from anthropogenic stressors under 7 simulated sources of uncertainty (factors: e.g., missing stressor data and assuming linear ecosystem responses to stress). Most maps agreed that high-impact areas were located in the Northeast Atlantic, the eastern Mediterranean, the Caribbean, the continental shelf off northern West Africa, offshore parts of the tropical Atlantic, the Indian Ocean east of Madagascar, parts of East and Southeast Asia, parts of the northwestern Pacific, and many coastal waters. Large low-impact areas were located off Antarctica, in the central Pacific, and in the southern Atlantic. Uncertainty in the broad-scale spatial distribution of modeled human impact was caused by the aggregate effects of several factors, rather than being attributable to a single dominant source. In spite of the identified uncertainty in human-impact maps, they can-at broad spatial scales and in combination with other environmental and socioeconomic information-point to priority areas for research and management.

'Thank God I'm not a Jungian'.

This article focuses less on the content of Jung's ideas than on ways in which they act as both invitation and challenge to engage with psyche. It explores the mythic framework of Jung's approach and how this can enable individuals to live in psychological and mundane worlds in which there can be no final certainties. It elaborates three particular aspects of Jung's thinking that I have found personally valuable: his generosity of vision, his insistence that individuals engage for and with themselves rather than relying on someone else's ideas, and his ponderings on the relationship between the individual and the collective. All three aspects seem to be important elements of the work of individuation.