The impact of insect herbivory on biogeochemical cycling in broadleaved forests varies with temperature.

Herbivorous insects alter biogeochemical cycling within forests, but the magnitude of these impacts, their global variation, and drivers of this variation remain poorly understood. To address this knowledge gap and help improve biogeochemical models, we established a global network of 74 plots within 40 mature, undisturbed broadleaved forests. We analyzed freshly senesced and green leaves for carbon, nitrogen, phosphorus and silica concentrations, foliar production and herbivory, and stand-level nutrient fluxes. We show more nutrient release by insect herbivores at non-outbreak levels in tropical forests than temperate and boreal forests, that these fluxes increase strongly with mean annual temperature, and that they exceed atmospheric deposition inputs in some localities. Thus, background levels of insect herbivory are sufficiently large to both alter ecosystem element cycling and influence terrestrial carbon cycling. Further, climate can affect interactions between natural populations of plants and herbivores with important consequences for global biogeochemical cycles across broadleaved forests.

Specific Associations Between Type of Childhood Abuse and Elevated C-Reactive Protein in Young Adult Psychiatric Rehabilitation Participants.

BACKGROUND: Early-life adversity such as childhood emotional, physical, and sexual trauma is associated with later-life psychiatric and chronic medical conditions, including elevated inflammatory markers. Although previous research suggests a role for chronic inflammatory dysfunctions in several disease etiologies, specific associations between childhood trauma types and later-life inflammation and health status are poorly understood. METHODS: We studied patients (n = 280) admitted to a psychiatric rehabilitation center. Self-reported histories of childhood emotional, physical, and sexual trauma were collected with a standard instrument. At the time of admission, we also assessed individuals' body mass index and collected blood samples used to examine inflammatory marker C-reactive protein (CRP) levels. RESULTS: The prevalence of all 3 types of abuse was relatively high at 21% or more. Fifty percent of the sample had elevations in CRP, with clinically significant elevations in 26%. We found that compared with a history of emotional or physical abuse, a history of childhood sexual trauma was more specifically associated with elevated CRP. This result held up when using linear regressions to examine the contribution of body mass index. LIMITATION: Our sample was relatively young, with an average age of 27.2 years and minimal representation of ethnic and racial minority participants. CONCLUSION: Relative to childhood emotional and physical trauma, childhood sexual trauma may lead to elevated inflammatory responses, as confirmed in our finding of an association between CRP and sexual abuse. Future studies need to assess the causal link between childhood sexual trauma and poorer health outcomes later in life.

Integrating biobehavioral information to predict mood disorder suicide risk.

The will to live and the ability to maintain one's well-being are crucial for survival. Yet, almost a million people die by suicide globally each year (Aleman and Denys, 2014), making premature deaths due to suicide a significant public health problem (Saxena et al., 2013). The expression of suicidal behaviors is a complex phenotype with documented biological, psychological, clinical, and sociocultural risk factors (Turecki et al., 2019). From a brain disease perspective, suicide is associated with neuroanatomical, neurophysiological, and neurochemical dysregulations of brain networks involved in integrating and contextualizing cognitive and emotional regulatory behaviors. From a symptom perspective, diagnostic measures of dysregulated mood states like major depressive symptoms are associated with over sixty percent of suicide deaths worldwide (Saxena et al., 2013). This paper reviews the neurobiological and clinical phenotypic correlates for mood dysregulations and suicidal phenotypes. We further propose machine learning approaches to integrate neurobiological measures with dysregulated mood symptoms to elucidate the role of inflammatory processes as neurobiological risk factors for suicide.