Beyond Inventories: Emergence of a New Era in Rangeland Monitoring

In the absence of technology-driven monitoring platforms, US rangeland policies, management practices, and outcome assessments have been primarily informed by the extrapolation of local information from national-scale rangeland inventories. A persistent monitoring gap between plot-level inventories and the scale at which rangeland assessments are conducted has required decision makers to fill data gaps with statistical extrapolations or assumptions of homogeneity and equilibrium. This gap is now being bridged with spatially comprehensive, annual, rangeland monitoring data across all western US rangelands to as- sess vegetation conditions at a resolution appropriate to inform cross-scale assessments and decisions. In this paper, 20-yr trends in plant functional type cover are presented, confirming two widespread national rangeland resource concerns: widespread increases in annual grass cover and tree cover. Rangeland vegetation monitoring is now available to inform national to regional policies and provide essential data at the scales at which decisions are made and implemented

Challenges of Brush Management Treatment Effectiveness in Southern Great Plains, United States

Woodland expansion is a global challenge documented under varying degrees of disturbance, climate, and land ownership patterns. In North American rangelands, mechanical and chemical brush management practices and prescribed fire are frequently promoted by agencies and used by private landowners to reduce woody plant cover. We assess the distribution of agency-supported cost sharing of brush management (2000−2017) in the southern Great Plains, United States, and evaluate the longevity of treatment application. We test the general expectation that the current brush management paradigm in the southern Great Plains reduces woody plants and conserves rangeland resources at broad scales. This study represents the most comprehensive assessment of treatment longevity following brush management in the southern Great Plains by linking confidential private lands management data to a national inventory program (US Department of Agriculture Natural Resources Conservation Service National Resources Inventory). We observed regional differences in the types of brush management techniques used in cost-sharing programs throughout the study area. Mechanical brush management was the most common practice cost shared in Texas, while a mixture of mechanical and chemical application was most common in Oklahoma. Prescribed fire was most common in Kansas with some areas receiving chemical treatment. Our analysis showed brush management, as implemented, did not reduce tree cover long term and minimally reduced shrub cover. Evidence to support the current brush management paradigm only existed at local site-level scales of analysis (40- to 50-acre area), but treatment effectiveness was short-lived. At regional scales, observed changes in woody plant cover showed little to no overall net reduction from 2000 to 2017. These findings bring into question the philosophy of the current brush management paradigm, its implementation as the default rangeland conservation practice, and its prioritization over alternative practices that prevent new woody plant establishment and enhance resilience of rangelands in the southern Great Plains region

Spatial Imaging and Screening for Regime Shifts

Screening is a strategy for detecting undesirable change prior to manifestation of symptoms or adverse effects. Although the well-recognized utility of screening makes it commonplace in medicine, it has yet to be implemented in ecosystem management. Ecosystem management is in an era of diagnosis and treatment of undesirable change, and as a result, remains more reactive than proactive and unable to effectively deal with today’s plethora of non-stationary conditions. In this paper, we introduce spatial imaging-based screening to ecology. We link advancements in spatial resilience theory, data, and technological and computational capabilities and power to detect regime shifts (i.e., vegetation state transitions) that are known to be detrimental to human well-being and ecosystem service delivery. With a state-of-the-art landcover dataset and freely available, cloud-based, geospatial computing platform, we screen for spatial signals of the three most iconic vegetation transitions studied in western USA rangelands: (1) erosion and desertification; (2) woody encroachment; and (3) annual exotic grass invasion. For a series of locations that differ in ecological complexity and geographic extent, we answer the following questions: (1) Which regime shift is expected or of greatest concern? (2) Can we detect a signal associated with the expected regime shift? (3) If detected, is the signal transient or persistent over time? (4) If detected and persistent, is the transition signal stationary or non-stationary over time? (5) What other signals do we detect? Our approach reveals a powerful and flexible methodology, whereby professionals can use spatial imaging to verify the occurrence of alternative vegetation regimes, image the spatial boundaries separating regimes, track the magnitude and direction of regime shift signals, differentiate persistent and stationary transition signals that warrant continued screening from more concerning persistent and non-stationary transition signals, and leverage disciplinary strength and resources for more targeted diagnostic testing (e.g., inventory and monitoring) and treatment (e.g., management) of regime shifts. While the rapid screening approach used here can continue to be implemented and refined for rangelands, it has broader implications and can be adapted to other ecological systems to revolutionize the information space needed to better manage critical transitions in nature

SYNTHESIS AND CYTOTOXICITY OF NOVEL LIGNANS

In this study the syntheses of 11 novel lignans are described. Their cytotoxicities are studied in GLC4, a human small cell lung carcinoma cell line, using the microculture tetrazolium (MTT) assay. Ten of these compounds were substituted with a menthyloxy group on the 5-position of the lactone. These compounds can easily be prepared in (novel) ‘one-pot’, three- or four-step syntheses. In addition, methods for controlling the stereogenic centers are described. Furthermore, five naturally occurring podophyllotoxin-related compounds were tested. The cytotoxicities of all lignan compounds, and of three non-lignan intermediates originating from the syntheses, were compared with the clinically applied anticancer agents etoposide, teniposide, and cisplatin. Most compounds showed moderate to high activities against GLC4, and two of the compounds containing a menthyloxy group showed activities comparable to the reference cytotoxic agents.

Depressive Symptoms and Amygdala Volume in Elderly with Cerebral Small Vessel Disease: The RUN DMC Study

Introduction. Late onset depressive symptoms (LODSs) frequently occur in elderly with cerebral small vessel disease (SVD). SVD cannot fully explain LODS; a contributing factor could be amygdala volume. We investigated the relation between amygdala volume and LODS, independent of SVD in 503 participants with symptomatic cerebral SVD. Methods. Patients underwent FLAIR and T1 scanning. Depressive symptoms were assessed with structured questionnaires; amygdala and WML were manually segmented. The relation between amygdala volume and LODS/EODS was investigated and adjusted for age, sex, intracranial volume, and SVD. Results. Patients with LODS had a significantly lower left amygdala volume than those without (P = 0.02), independent of SVD. Each decrease of total amygdala volume (by mL) was related to an increased risk of LODS (OR = 1.77; 95% CI 1.02–3.08; P = 0.04). Conclusion. Lower left amygdala volume is associated with LODS, independent of SVD. This may suggest differential mechanisms, in which individuals with a small amygdala might be vulnerable to develop LODS

Tracking spatial regimes in animal communities: Implications for resilience-based management

Spatial regimes (the spatial extents of ecological states) exhibit strong spatiotemporal order as they expand or contract in response to retreating or encroaching adjacent spatial regimes (e.g., woody plant invasion of grasslands) and human management (e.g., fire treatments). New methods enable tracking spatial regime boundaries via vegetation landcover data, and this approach is being used for strategic management across biomes. A clear advancement would be incorporating animal community data to track spatial regime boundaries alongside vegetation data. In a 41,170-hectare grassland experiencing woody plant encroachment, we test the utility of using animal community data to track spatial regimes via two hypotheses. (H1) Spatial regime boundaries identified via independent vegetation and animal datasets will exhibit spatial synchrony; specifically, grassland:woodland bird community boundaries will synchronize with grass:woody vegetation boundaries. (H2) Negative feedbacks will stabilize spatial regimes identified via animal data; specifically, frequent fire treatments will stabilize grassland bird community boundaries. We used 26 years of bird community and vegetation data alongside 32 years of fire history data. We identified spatial regime boundaries with bird community data via a wombling approach. We identified spatial regime boundaries with vegetation data by calculating spatial covariance between remotely-sensed grass and woody plant cover per pixel. For fire history data, we calculated the cumulative number of fires per pixel. Setting bird boundary strength (wombling R2 values) as the response variable, we tested our hypotheses with a hierarchical generalized additive model (HGAM). Both hypotheses were supported: animal boundaries synchronized with vegetation boundaries in space and time, and grassland bird communities stabilized as fire frequency increased (HGAM explained 38% of deviance). We can now track spatial regimes via animal community data pixel-by-pixel and year-by-year. Alongside vegetation boundary tracking, tracking animal community boundaries can inform the scale of management necessary to maintain animal communities endemic to desirable ecological states. Our approach will be especially useful for conserving animal communities requiring large-scale, unfragmented landscapes—like grasslands and steppes

Shared Decision Making in Health Care Visits for CKD:Patients’ Decisional Role Preferences and Experiences

Rationale &amp; Objective: Research on shared decision making (SDM) in chronic kidney disease (CKD) has focused almost exclusively on the modality of kidney replacement treatment. We explored what other CKD decisions are recognized by patients, what their preferences and experiences are regarding these decisions, and how decisions are made during their interactions with medical care professionals. Study Design: Cross-sectional study. Setting &amp; Participants: Patients with CKD receiving (outpatient) care in 1 of 2 Dutch hospitals. Exposure: Patients’ preferred decisional roles for treatment decisions were measured using the Control Preferences Scale survey administered after a health care visit with medical professionals. Outcome: Number of decisions for which patients experienced a decisional role that did or did not match their preferred role. Observed levels of SDM and motivational interviewing in audio recordings of health care visits, measured using the 4-step SDM instrument (4SDM) and Motivational Interviewing Treatment Integrity coding tools.Analytical Approach: The results were characterized using descriptive statistics, including differences in scores between the patients’ experienced and preferred decisional roles. Results: According to the survey (n = 122) patients with CKD frequently reported decisions regarding planning (112 of 122), medication changes (82 of 122), or lifestyle changes (59 of 122). Of the 357 reported decisions in total, patients preferred that clinicians mostly (125 of 357) or fully (101 of 357) make the decisions. For 116 decisions, they preferred a shared decisional role. For 151 of 357 decisions, the patients’ preferences did not match their experiences. Decisions were experienced as “less shared/patient-directed” (76 of 357) or “more shared/patient-directed” (75 of 357) than preferred. Observed SDM in 118 coded decisions was low (median 4; range, 0 – 22). Motivational interviewing techniques were rarely used. Limitations: Potential recall and selection bias, and limited generalizability. Conclusions: We identified multiple discrepancies between preferred, experienced, and observed SDM in health care visits for CKD. Although patients varied in their preferred decisional role, a large minority of patients expressed a preference for shared decision making for many decisions. However, SDM behavior during the health care visits was observed infrequently. Plain-Language Summary: Shared decision making (SDM) may be a valuable approach for common chronic kidney disease (CKD) decisions, but our knowledge is limited. We collected patient surveys after health care visits for CKD. Patients most frequently experienced decisions regarding planning, medication, and lifestyle. Three decisional roles were preferred by comparable numbers of patients: let the clinician alone decide, let the clinician decide for the most part, or “equally share” the decision. Patients’ experiences of who made the decision did not always match their preferences. In audio recordings of the health care visits, we observed low levels of SDM behavior. These findings suggest that the preference for “sharing decisions” is often unmet for a large number of patients.</p

Predicting outcomes in chronic kidney disease:needs and preferences of patients and nephrologists

Introduction: Guidelines on chronic kidney disease (CKD) recommend that nephrologists use clinical prediction models (CPMs). However, the actual use of CPMs seems limited in clinical practice. We conducted a national survey study to evaluate: 1) to what extent CPMs are used in Dutch CKD practice, 2) patients’ and nephrologists’ needs and preferences regarding predictions in CKD, and 3) determinants that may affect the adoption of CPMs in clinical practice. Methods: We conducted semi-structured interviews with CKD patients to inform the development of two online surveys; one for CKD patients and one for nephrologists. Survey participants were recruited through the Dutch Kidney Patient Association and the Dutch Federation of Nephrology. Results: A total of 126 patients and 50 nephrologists responded to the surveys. Most patients (89%) reported they had discussed predictions with their nephrologists. They most frequently discussed predictions regarded CKD progression: when they were expected to need kidney replacement therapy (KRT) (n = 81), and how rapidly their kidney function was expected to decline (n = 68). Half of the nephrologists (52%) reported to use CPMs in clinical practice, in particular CPMs predicting the risk of cardiovascular disease. Almost all nephrologists (98%) reported discussing expected CKD trajectories with their patients; even those that did not use CPMs (42%). The majority of patients (61%) and nephrologists (84%) chose a CPM predicting when patients would need KRT in the future as the most important prediction. However, a small portion of patients indicated they did not want to be informed on predictions regarding CKD progression at all (10–15%). Nephrologists not using CPMs (42%) reported they did not know CPMs they could use or felt that they had insufficient knowledge regarding CPMs. According to the nephrologists, the most important determinants for the adoption of CPMs in clinical practice were: 1) understandability for patients, 2) integration as standard of care, 3) the clinical relevance. Conclusion: Even though the majority of patients in Dutch CKD practice reported discussing predictions with their nephrologists, CPMs are infrequently used for this purpose. Both patients and nephrologists considered a CPM predicting CKD progression most important to discuss. Increasing awareness about existing CPMs that predict CKD progression may result in increased adoption in clinical practice. When using CPMs regarding CKD progression, nephrologists should ask whether patients want to hear predictions beforehand, since individual patients’ preferences vary.</p

Tracking spatial regimes in animal communities: Implications for resilience-based management

Spatial regimes (the spatial extents of ecological states) exhibit strong spatiotemporal order as they expand or contract in response to retreating or encroaching adjacent spatial regimes (e.g., woody plant invasion of grasslands) and human management (e.g., fire treatments). New methods enable tracking spatial regime boundaries via vegetation landcover data, and this approach is being used for strategic management across biomes. A clear advancement would be incorporating animal community data to track spatial regime boundaries alongside vegetation data. In a 41,170-hectare grassland experiencing woody plant encroachment, we test the utility of using animal community data to track spatial regimes via two hypotheses. (H1) Spatial regime boundaries identified via independent vegetation and animal datasets will exhibit spatial synchrony; specifically, grassland:woodland bird community boundaries will synchronize with grass:woody vegetation boundaries. (H2) Negative feedbacks will stabilize spatial regimes identified via animal data; specifically, frequent fire treatments will stabilize grassland bird community boundaries. We used 26 years of bird community and vegetation data alongside 32 years of fire history data. We identified spatial regime boundaries with bird community data via a wombling approach. We identified spatial regime boundaries with vegetation data by calculating spatial covariance between remotely-sensed grass and woody plant cover per pixel. For fire history data, we calculated the cumulative number of fires per pixel. Setting bird boundary strength (wombling R2 values) as the response variable, we tested our hypotheses with a hierarchical generalized additive model (HGAM). Both hypotheses were supported: animal boundaries synchronized with vegetation boundaries in space and time, and grassland bird communities stabilized as fire frequency increased (HGAM explained 38% of deviance). We can now track spatial regimes via animal community data pixel-by-pixel and year-by-year. Alongside vegetation boundary tracking, tracking animal community boundaries can inform the scale of management necessary to maintain animal communities endemic to desirable ecological states. Our approach will be especially useful for conserving animal communities requiring large-scale, unfragmented landscapes—like grasslands and steppes

Circulating T cells in sarcoidosis have an aberrantly activated phenotype that correlates with disease outcome

Rationale: Disease course in sarcoidosis is highly variable. Bronchoalveolar lavage fluid and mediastinal lymph nodes show accumulation of activated T cells with a T-helper (Th)17.1 signature, which correlates with non-resolving sarcoidosis. We hypothesize that the peripheral blood (PB) T cell phenotype may correlate with outcome. Objectives: To compare frequencies, phenotypes and function of circulating T cell populations in sarcoidosis patients with healthy controls (HCs) and correlate these parameters with outcome. Methods: We used multi-color flow cytometry to quantify activation marker expression on PB T cell subsets in treatment-naïve patients and HCs. The disease course was determined after 2-year follow-up. Cytokine production was measured after T cell stimulation in vitro. Measurements and main results: We observed significant differences between patients and HCs in several T cell populations, including CD8+ and CD4+ T cells, Th1/Th17 subsets, CD4+ T memory stem cells, regulatory T cells (Tregs) and γδ T cells. Decreased frequencies of CD4+ T cells and increased frequencies of Tregs and CD8+ γδ T cells correlated with worse outcome. Naïve CD4+ T cells displayed an activated phenotype with increased CD25 expression in patients with active chronic disease at 2-year follow-up. A distinctive Treg phenotype with increased expression of CD25, CTLA4, CD69, PD-1 and CD95 correlated with chronic sarcoidosis. Upon stimulation, both naïve and memory T cells displayed a different cytokine profile in sarcoidosis compared to HCs. Conclusions: Circulating T cell subpopulations of sarcoidosis patients display phenotypic abnormalities that correlate with disease outcome, supporting a critical role of aberrant T cell activation in sarcoidosis pathogenesis.</p