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We study whether the corporate tax system provides incentives for risky firm investment. We analytically and empirically show two main findings: first, risk-taking is positively related to the length of tax loss periods because the loss rules shift some risk to the government; and second, the tax rate has a positive effect on risk-taking for firms that expect to use losses, and a weak negative effect for those that cannot. Thus, the sign of the tax effect on risky investment hinges on firm-specific expectations of future loss recovery.

\"The self\" has seen a surprising resurgence in recent anthropological theorizing, revitalizing interest in whether and how it can be studied ethnographically. These issues are brought to the fore by a newly popular psychotherapy technique, Internal Family Systems therapy (IFS), as practiced in a US eating-disorders clinic. There, clinicians and clients negotiate tensions between this model's understanding of a multiple, refracted self and managed-care companies' insistence on personal responsibility. In considering the moral and pragmatic work of IFS in the clinic, a new critical anthropology of selfhood illuminates the vectors through which economic and political commitments become imbricated in the self. They do so in ways that resist both psychologism and subjectivism while holding them in productive—albeit sometimes troubling—tension.

The International Union for Conservation of Nature (IUCN) Red List of Ecosystems is a powerful tool for classifying threatened ecosystems, informing ecosystem management, and assessing the risk of ecosystem collapse (that is, the endpoint of ecosystem degradation). These risk assessments require explicit definitions of ecosystem collapse, which are currently challenging to implement. To bridge the gap between theory and practice, we systematically review evidence for ecosystem collapses reported in two contrasting biomes – marine pelagic ecosystems and terrestrial forests. Most studies define states of ecosystem collapse quantitatively, but few studies adequately describe initial ecosystem states or ecological transitions leading to collapse. On the basis of our review, we offer four recommendations for defining ecosystem collapse in risk assessments: (1) qualitatively defining initial and collapsed states, (2) describing collapse and recovery transitions, (3) identifying and selecting indicators of collapse, and (4) setting quantitative collapse thresholds.

This paper examines the moral work of a controversial psychiatric diagnosis—Borderline Personality Disorder—in an American eating disorder treatment center in the era of managed mental health care. Based on fieldwork at this clinic spanning more than 6 years, I consider how clinicians invoke aspects of Borderline Personality Disorder in everyday conversation, in a practice I call “borderline talk.” I argue that borderline talk emerges in response to being caught between contradictory models of the subject entailed in managed care and psychodynamic discourses. Specifically, borderline talk enables clinicians to endorse a formulation of the subject that, although considered pathological, provides them with a clear path of ethical action in otherwise ethically ambiguous situations. These kinds of everyday ethical negotiations percolate throughout the American health care system and are key mechanisms through which notions of economic expediency become entangled with concepts of the healthy subject. As clinicians struggle out a course of action between competing ethical imperatives, they also struggle out the workability—and failures—of various articulations of the subject within contemporary American cultural ideologies of health and pathology.

Landscape classification and hydrological regionalisation studies are being increasingly used in ecohydrology to aid in the management and research of aquatic resources. We present a methodology for classifying hydrologic landscapes based on spatial environmental variables by employing non-parametric statistics and hybrid image classification. Our approach differed from previous classifications which have required the use of an a priori spatial unit (e.g. a catchment) which necessarily results in the loss of variability that is known to exist within those units. The use of a simple statistical approach to identify an appropriate number of classes eliminated the need for large amounts of post-hoc testing with different number of groups, or the selection and justification of an arbitrary number. Using statistical clustering, we identified 23 distinct groups within our training dataset. The use of a hybrid classification employing random forests extended this statistical clustering to an area of approximately 228,000 km2 of south-eastern Australia without the need to rely on catchments, landscape units or stream sections. This extension resulted in a highly accurate regionalisation at both 30-m and 2.5-km resolution, and a less-accurate 10-km classification that would be more appropriate for use at a continental scale. A smaller case study, of an area covering 27,000 km2, demonstrated that the method preserved the intra- and inter-catchment variability that is known to exist in local hydrology, based on previous research. Preliminary analysis linking the regionalisation to streamflow indices is promising suggesting that the method could be used to predict streamflow behaviour in ungauged catchments. Our work therefore simplifies current classification frameworks that are becoming more popular in ecohydrology, while better retaining small-scale variability in hydrology, thus enabling future attempts to explain and visualise broad-scale hydrologic trends at the scale of catchments and continents.

Amongst oviparous animals, the spatial distribution of individuals is often set initially by where females lay eggs, with potential implications for populations and species coexistence. Do the spatial arrangements of oviposition sites or female behaviours determine spatial patterns of eggs? The consequences of spatial patterns may be context independent if strong behaviours drive patterns; context dependent if the local environment dominates. We tested these ideas using a guild of stream-dwelling caddisflies that oviposit on emergent rocks, focussing on genera with contrasting behaviours. In naturally occurring oviposition landscapes (riffles with emergent rocks), we surveyed the spatial arrangement and environmental characteristics of all emergent rocks, identified and enumerated egg masses on each. Multiple riffles were surveyed to test for spatially invariant patterns and behaviours. In landscapes, we tested for spatial clumping of oviposition sites exploited by each species and for segregation of congeneric species. At oviposition sites, we characterised the frequency distributions of egg masses and tested for species associations. Genus-specific behaviours produced different spatial patterns of egg masses in the same landscapes. Congregative behaviour of Ulmerochorema spp. at landscape scales and an aggregative response at preferred oviposition sites led to clumped patterns, local aggregation and species overlap. In contrast, avoidance behaviours by congeners of Apsilochorema resulted in no or weak clumping, and species segregation in some landscapes. Spatial patterns were consistent across riffles that varied in area and oviposition site density. These results suggest that quite different oviposition behaviours may be context independent, and the consequences of spatial patterns may be spatially invariant also.

Extreme climatic events are linked to an increase in emergent diseases. Such increases depend on the relationships between environmental conditions and host–parasite dynamics. Caddisflies host the oomycete Saprolegnia, which has increased in prevalence in freshwater systems and causes mortality in caddisflies, most prominently Ulmerochorema rubiconum. We tested how short (12 h) or longer (21 days) heatwaves (22.5°C water temperature) alter U. rubiconum hatching and Saprolegnia infection in eggs compared to no heatwave (i.e., ongoing low temperatures at 12.5°C). Short and longer heatwaves yielded similarly elevated infection probability compared to no heatwaves. A longer heatwave shortened the egg period significantly compared to a short heatwave or no heatwaves. As short heatwaves increased infection probability and resulted in longer egg durations than longer heatwaves, they could pose a greater risk to caddisfly populations than the longer heatwaves. Population modeling demonstrates how this hatching‐infection trade‐off determines the effect of heatwaves on population growth rates. Predicted increases in heatwave frequency and magnitude increased the likelihood that eggs would experience conditions favorable for infection, potentially disrupting caddisfly populations and ecosystem functioning. Similar asymmetric impacts of climate on ecological relationships are likely common and may yield important population outcomes. The responses of hosts and pathogens to change must be studied in unison, rather than individual components in isolation.

Ongoing ecosystem degradation and transformation are major threats to biodiversity. Measuring ecosystem change toward collapse relies on monitoring indicators that quantify key ecological processes. Yet little guidance is available on selection and use of indicators for ecosystem risk assessment We reviewed indicator use in ecological studies of ecosystem collapse in marine pelagic and temperate forest ecosystems. We examined indicator-selection methods, indicator types (geographic distribution, abiotic, biotic), methods of assessing multiple indicators, and temporal quality of time series. We compared how these factors were applied in the ecological studies with how they were applied in risk assessments by using the International Union for Conservation of Nature's Red List of Ecosystems (RLE), for which indicators are used to estimate risk of ecosystem collapse. Ecological studies and RLE assessments rarely reported how indicators were selected, particularly in terrestrial ecosystems. Few ecological studies and RLE assessments quantified ecosystem change based on all 3 indicator types, and indicators types used differed between marine and terrestrial ecosystems. Several studies used indices or multivariate analyses to assess multiple indicators simultaneously, but RLE assessments did not because as RLE guidelines advise against them. Most studies and RLE assessments used time-series data that spanned at least 30 years, which increases the probability of reliably detecting change. Limited use of indicator-selection protocols and infrequent use of all 3 indicator types may hamper accurate detection of change. To improve the value of risk assessments for informing policy and management, we recommend using explicit protocols, including conceptual models, to identify and select indicators; a range of indicators spanning distributional, abiotic, and biotic features; indices and multivariate analyses with extreme care until guidelines are developed; time series with sufficient data to increase ability to accurately diagnose directional change; data from multiple sources to support assessments; and explicitly reporting steps in the assessment process. La continua degradación y transformación de los ecosistemas son amenazas importantes para la biodiversidad. La medición del cambio de los ecosistemas hacia el colapso depende del monitoreo de los indicadores que cuantifican los procesos ecológicos clave. A pesar de esto, existe poca orientación disponible para la selección y el uso de los indicadores de riesgo en un ecosistema. Revisamos el uso de indicadores en estudios ecológicos del colapso ecosistémico en ecosistemas marinos pelágicos y de bosques templados. Examinamos los métodos de selección de indicadores, los tipos de indicadores (distribución geográfica, abiótico, biótico), los métodos de evaluación de indicadores múltiples, y la calidad temporal de las series de tiempo. Comparamos cómo estos factores fueron aplicados en los estudios ecológicos con la forma en que fueron aplicados en las evaluaciones de riesgo al usar la Lista Roja de Ecosistemas de la Unión Internaciona para la Conservación de la Naturaleza (RLE, en inglés), para la cual se usan los indicadores para estimar e riesgo de colapso de un ecosistema. Los estudios ecológicos y las evaluaciones de la RLE rara vez reportaron cómo se seleccionaron los indicadores, particularmente en ecosistemas terrestres. Pocos estudios ecológicos y evaluaciones de la RLE cuantificaron el cambio del ecosistema con base en los tres tipos de indicadores, y los tipos de indicadores usados difirieron entre los ecosistemas marinos y los terrestres. Varios estudios usaron índices o análisis multivariados para evaluar indicadores múltiples simultáneamente, pero las evaluaciones de la RLE no lo hicieron porque las pautas de la RLE sugieren que no se usen. La mayoría de los estudios y de las evaluaciones de la RLE usaron datos de series de tiempo que abarcaban por lo menos 30 años, lo que incrementa la probabilidad de la confiabilidad para detector el cambio. Para aumentar el valor de la evaluación de riesgos para informar a la política y al manejo recomendamos utilizar protocolos explícitos, incluyendo los modelos conceptuales, para identificar y seleccionar los indicadores; una gama de indicadores que abarquen las características de distribución, abióticas y bióticas; índices y análisis multivariados con extremo cuidado hasta que se desarrollen pautas adecuadas; series de tiempo con suficientes datos para incrementar la habilidad de diagnosticar correctamente el cambio direccional; datos de fuentes múltiples para respaldar las evaluaciones; y reportar explícitamente los pasos en el proceso de evaluación. 持续的生态系统退化和转化对生物多祥性构成了主要威胁。測量生态系统走向崩溃的变化依赖于对可以 定量关键生态过程指标的监測。然而: 目前还缺乏対生态系统风险评估指标选择和应用的指导意见。本文综述 了生态学研究中海洋浮游生态系统和温带森林生态系统的生态系统崩溃所采用的指标。我们分析了指标选择方 法、指标类型（地理分布、非生物和生物指标) 、评估多个指标的方法，以及时间序列的时间质量。为比较这些 因素在生态学研究和风险评估中的应用，我们利用了世界自然保护联盟的《生态系统红色名录’ RLE) ,其指标 用于评估生态系统崩溃的风险。生态学研究和RLE评估很少报道指标的选择方法，特别是对于陆 生态系统。 也很少有生态学研究和RLE评估根据所有的三类指标来定量生态系统改变，且海洋和陆地生态系统所用指标类 型也不同。有的研究用ー些指数或是多因素分析来同时评估多个指标，但RLE评估没有这样做, 因为RLE指导 方针中建议不要用这样的方法。大多研究和RLE评估用了超过3 0 年的时间序列数据,这样更有可能可靠地监 测到变化。而指标选择方法的使用较为有限，同时使用所有的三类指标也较为少见，这可能会妨碍准确监测到变 化。为了提髙风险评估为政策和管理提供信息的价值, 我们建议：用明确的方法(包括概念模型)来确定和选择 指标;使用包括地理分布、非生物和生物特征的一系列指标;在有指导方针前，应谨慎使用指数和多因素分析;用 有充足数据的时间序列来提高对方向性变化的准确检测，•用多个来源的数据来支持评估;明确地报告评估过程的 步骤.

How do U.S. companies respond to incentives intended to encourage domestic manufacturing? I study the Domestic Production Activities Deduction (DPAD), which was enacted in the American Jobs Creation Act (AJCA) of 2004 and was the third largest U.S. corporate tax expenditure as of 2017. Using confidential data from the U.S. Bureau of Economic Analysis, I find greater average domestic investment spending of $95.5-$143.6 million, but only within the sample of domestic-only firms and not until 2010, when the greatest statutory DPAD benefits were available. Additional evidence suggests that U.S. multinational claimants invest abroad rather than in the United States and that the increased investment by DPAD firms is accompanied by a reduction in the domestic workforce, consistent with a substitution of capital for labor. I also show that the delayed investment response is due to firms engaging in other responses first, such as changing corporate reporting to shift income across time and borders. Quantifying the extent of these effects contributes to the literature that studies this tax deduction and informs policy makers as to the effectiveness of both manufacturing incentives and U.S. corporate income tax rate reductions in stimulating real domestic activity.