Long-term trend and interannual variation in evapotranspiration of a young temperate Douglas-fir stand over 2002-2022 reveals the impacts of climate change.

The shortage of decades-long continuous measurements of ecosystem processes limits our understanding of how changing climate impacts forest ecosystems. We used continuous eddy-covariance and hydrometeorological data over 2002-2022 from a young Douglas-fir stand on Vancouver Island, Canada to assess the long-term trend and interannual variability in evapotranspiration (ET) and transpiration (T). Collectively, annual T displayed a decreasing trend over the 21 years with a rate of 1% yr-1, which is attributed to the stomatal downregulation induced by rising atmospheric CO2 concentration. Similarly, annual ET also showed a decreasing trend since evaporation stayed relatively constant. Variability in detrended annual ET was mostly controlled by the average soil water storage during the growing season (May-October). Though the duration and intensity of the drought did not increase, the drought-induced decreases in T and ET showed an increasing trend. This pattern may reflect the changes in forest structure, related to the decline in the deciduous understory cover during the stand development. These results suggest that the water-saving effect of stomatal regulation and water-related factors mostly determined the trend and variability in ET, respectively. This may also imply an increase in the limitation of water availability on ET in young forests, associated with the structural and compositional changes related to forest growth.

Retrospective operationalization of allostatic load in patients with cancer: A systematic review.

Allostatic load (AL) has been shown to impact cancer outcomes. At present, no gold standard exists surrounding AL computation. As such, a systematic review of the literature was performed to identify studies that retrospectively calculated AL in patients with cancer. The following variables were collected for each study: AL calculation method, including the biomarkers used and their cutoff values, number of biosystems represented, definition of high AL, and the use of proxy biomarkers. Thirteen articles were included for full-text review. The number of biomarkers used in the calculation of AL varied considerably, ranging from 6 to 16. Considerable variability was also observed in terms of utilized biomarkers and biosystem representation. This lack of standardization complicates retrospective AL calculation among patients with cancer. Nonetheless, determining AL in patients with cancer presents an important step in the optimization of patient care and outcomes.

Dry-season length affects the annual ecosystem carbon balance of a temperate semi-arid shrubland.

Semi-arid ecosystems have been shown to dominate over tropical forests in determining the trend and interannual variability of land carbon (C) sink. However, the magnitude and variability of ecosystem C balance remain largely uncertain for temperate semi-arid shrublands at the decadal scale. Using eddy-covariance and micro-meteorological measurements, we quantified the interannual variation in net ecosystem production (NEP) and its components, gross primary production (GPP) and ecosystem respiration (Reco, i.e., the sum of autotrophic and heterotrophic respiration), in a semi-arid shrubland of the Mu Us Desert, northern China during 2012-2022. This shrubland was an overall weak C sink over the 11 years (NEP = 12 ± 46 g C m-2 yr-1, mean ± SD). Annual NEP ranged from -66 to 77 g C m-2 yr-1, with the ecosystem frequently switching between being an annual C sink and a C source. GPP was twice as sensitive as Reco to prolonged dry seasons, leading to a close negative relationship between annual NEP and dry-season length (R2 = 0.80, P < 0.01). Annual GPP (R2 = 0.51, P = 0.01) and NEP (R2 = 0.58, P < 0.01) were positively correlated with annual rainfall. Negative annual NEP (the ecosystem being a C source) tended to occur when the dry season exceeded 50 d yr-1 or rainfall dropped below 280 mm yr-1. Increases in dry-season length strengthened the effects of low soil moisture relative to high vapor pressure deficit in constraining NEP. Both GPP and NEP were more closely correlated with C uptake amplitude (annual maximum daily values) than with C uptake period. These findings indicate that dry-season extension under climate change may reduce the long-term C sequestration in semi-arid shrublands. Plant species adapted to prolonged dry seasons should be used in ecosystem restoration in the studied area to enhance ecosystem functions.

Arctic soil methane sink increases with drier conditions and higher ecosystem respiration.

Arctic wetlands are known methane (CH4) emitters but recent studies suggest that the Arctic CH4 sink strength may be underestimated. Here we explore the capacity of well-drained Arctic soils to consume atmospheric CH4 using >40,000 hourly flux observations and spatially distributed flux measurements from 4 sites and 14 surface types. While consumption of atmospheric CH4 occurred at all sites at rates of 0.092 ± 0.011 mgCH4 m-2 h-1 (mean ± s.e.), CH4 uptake displayed distinct diel and seasonal patterns reflecting ecosystem respiration. Combining in situ flux data with laboratory investigations and a machine learning approach, we find biotic drivers to be highly important. Soil moisture outweighed temperature as an abiotic control and higher CH4 uptake was linked to increased availability of labile carbon. Our findings imply that soil drying and enhanced nutrient supply will promote CH4 uptake by Arctic soils, providing a negative feedback to global climate change.

Leaf-level coordination principles propagate to the ecosystem scale.

Fundamental axes of variation in plant traits result from trade-offs between costs and benefits of resource-use strategies at the leaf scale. However, it is unclear whether similar trade-offs propagate to the ecosystem level. Here, we test whether trait correlation patterns predicted by three well-known leaf- and plant-level coordination theories - the leaf economics spectrum, the global spectrum of plant form and function, and the least-cost hypothesis - are also observed between community mean traits and ecosystem processes. We combined ecosystem functional properties from FLUXNET sites, vegetation properties, and community mean plant traits into three corresponding principal component analyses. We find that the leaf economics spectrum (90 sites), the global spectrum of plant form and function (89 sites), and the least-cost hypothesis (82 sites) all propagate at the ecosystem level. However, we also find evidence of additional scale-emergent properties. Evaluating the coordination of ecosystem functional properties may aid the development of more realistic global dynamic vegetation models with critical empirical data, reducing the uncertainty of climate change projections.

Thematic analyses of participant survey responses following dermatology ECHO programs with dermoscopy: Practical tips and lessons learned.

Introduction: Skin cancer is a major public health concern in the United States, reflecting approximately one in every three cancer diagnoses. Despite the high incidence of skin cancer, access to dermatologists is limited, especially in rural areas. Primary care physicians play a pivotal role in the evaluation of skin conditions, but dermatology training gaps exist in primary care training programs. Objectives: This study examines the use of the Project ECHO (Extension for Community Healthcare Outcomes) knowledge-sharing framework to provide dermoscopy and skin cancer detection training to primary care providers (PCPs). Methods: Responses to surveys administered to participants in two separate dermoscopy-focused Project ECHO courses were analyzed. Survey responses were collected over a 4-year period for the two courses, which were delivered in Maine and Texas. Thematic analysis of the qualitative data was performed, revealing codes and subcodes that indicated several overall trends. Results: Overall, most respondents indicated the ECHO sessions to be helpful, reporting an increase in confidence and knowledge in dermoscopy. Other codes reflected a positive reception of the learning materials and teaching styles. Furthermore, participant survey analyses highlighted areas of improvement for future ECHO course sessions. Conclusions: This thematic analysis of Project ECHO courses in dermatology with dermoscopy demonstrates the feasibility of using virtual educational platforms to effectively teach PCPs about dermoscopy and skin cancer, with high levels of participant satisfaction. The need to keeping the educational sessions brief, avoid scheduling sessions on high-volume patient care days, and provide a means for participants to obtain hands-on training in the operation of a dermatoscope were among the top lessons learned.

The Challenges of Characterizing the Zooplankton Community Response Following Simulated Spills of Diluted Bitumen into Boreal Lake Limnocorrals.

We attempted to characterize zooplankton community response following spills of the unconventional crude oil, diluted bitumen (dilbit), into 10-m diameter, ~ 100 m3, ~ 1.5-m deep boreal lake limnocorrals, including two controls and seven dilbit treatments ranging from 1.5 to 180 L (1:100,000 to 1:1,000 v/v, dilbit:water). Community composition and abundances were monitored weekly to bi-weekly over three months. Total zooplankton biomass and abundance seemingly collapsed in all limnocorrals, regardless of treatment, though some rotifer species persisted. As a result, it was not possible to determine the impacts of dilbit. We theorize several potential non-oil-related reasons for the sudden community collapse - including elevated zinc levels, fish grazing pressures, and sampling biases - and provide guidance for future work using in-lake enclosures.

Re-assessment of the climatic controls on the carbon and water fluxes of a boreal aspen forest over 1996-2016: Changing sensitivity to long-term climatic conditions.

Recent evidence suggests that the relationships between climate and boreal tree growth are generally non-stationary; however, it remains uncertain whether the relationships between climate and carbon (C) fluxes of boreal forests are stationary or have changed over recent decades. In this study, we used continuous eddy-covariance and microclimate data over 21 years (1996-2016) from a 100-year-old trembling aspen stand in central Saskatchewan, Canada to assess the relationships between climate and ecosystem C and water fluxes. Over the study period, the most striking climatic event was a severe, 3-year drought (2001-2003). Gross ecosystem production (GEP) showed larger interannual variability than ecosystem respiration (Re ) over 1996-2016, but Re was the dominant component contributing to the interannual variation in net ecosystem production (NEP) during post-drought years. The interannual variations in evapotranspiration (ET) and C fluxes were primarily driven by temperature and secondarily by water availability. Two-factor linear models combining precipitation and temperature performed well in explaining the interannual variation in C and water fluxes (R2 > .5). The temperature sensitivities of all three C fluxes (NEP, GEP and Re ) declined over the study period (p < .05), and, as a result, the phenological controls on annual NEP weakened. The decreasing temperature sensitivity of the C fluxes may reflect changes in forest structure, related to the over-maturity of the aspen stand at 100 years of age, and exacerbated by high tree mortality following the severe 2001-2003 drought. These results may provide an early warning signal of driver shift or even an abrupt status shift of aspen forest dynamics. They may also imply a universal weakening in the relationship between temperature and GEP as forests become over-mature, associated with the structural and compositional changes that accompany forest ageing.

Honey bee (Apis mellifera ligustica) acetylcholinesterase enzyme activity and aversive conditioning following aluminum trichloride exposure.

BACKGROUND: Aluminum is the third most prevalent element in the earth's crust. In most conditions, it is tightly bound to form inaccessible compounds, however in low soil pH, the ionized form of aluminum can be taken up by plant roots and distributed throughout the plant tissue. Following this uptake, nectar and pollen concentrations in low soil pH regions can reach nearly 300 mg/kg. Inhibition of acetylcholinesterase (AChE) has been demonstrated following aluminum exposure in mammal and aquatic invertebrate species. In honey bees, behaviors consistent with AChE inhibition have been previously recorded; however, the physiological mechanism has not been tested, nor has aversive conditioning. RESULTS: This article presents results of ingested aqueous aluminum chloride exposure on AChE as well as acute exposure effects on aversive conditioning in an Apis mellifera ligustica hive. Contrary to previous findings, AChE activity significantly increased as compared to controls following exposure to 300 mg/L Al3+. In aversive conditioning studies, using an automated shuttlebox, there were time and dose-dependent effects on learning and reduced movement following 75 and 300 mg/L exposures. CONCLUSIONS: These findings, in comparison to previous studies, suggest that aluminum toxicity in honey bees may depend on exposure period, subspecies, and study metrics. Further studies are encouraged at the moderate-high exposure concentrations as there may be multiple variables that affect toxicity which should be teased apart further.

The three major axes of terrestrial ecosystem function.

The leaf economics spectrum1,2 and the global spectrum of plant forms and functions3 revealed fundamental axes of variation in plant traits, which represent different ecological strategies that are shaped by the evolutionary development of plant species2. Ecosystem functions depend on environmental conditions and the traits of species that comprise the ecological communities4. However, the axes of variation of ecosystem functions are largely unknown, which limits our understanding of how ecosystems respond as a whole to anthropogenic drivers, climate and environmental variability4,5. Here we derive a set of ecosystem functions6 from a dataset of surface gas exchange measurements across major terrestrial biomes. We find that most of the variability within ecosystem functions (71.8%) is captured by three key axes. The first axis reflects maximum ecosystem productivity and is mostly explained by vegetation structure. The second axis reflects ecosystem water-use strategies and is jointly explained by variation in vegetation height and climate. The third axis, which represents ecosystem carbon-use efficiency, features a gradient related to aridity, and is explained primarily by variation in vegetation structure. We show that two state-of-the-art land surface models reproduce the first and most important axis of ecosystem functions. However, the models tend to simulate more strongly correlated functions than those observed, which limits their ability to accurately predict the full range of responses to environmental changes in carbon, water and energy cycling in terrestrial ecosystems7,8.

Surface oil is the primary driver of macroinvertebrate impacts following spills of diluted bitumen in freshwater.

The response of freshwater invertebrates following accidental releases of oil is not well understood. This knowledge gap is more substantial for unconventional oils such as diluted bitumen (dilbit). We evaluated the effects of dilbit on insect emergence and benthic invertebrates by conducting experimental spills in limnocorrals (10-m diameter; ~100-m3) deployed in a boreal lake at the IISD-Experimental Lakes Area, Canada. The study included seven dilbit treatments (spill volumes ranged from 1.5 L [1:66,000, oil:water, v/v] to 180 L [1:590, oil:water, v/v]), two controls, and additional lake reference sites, monitored for 11 weeks. Invertebrate emergence declined at the community level following oil addition in a significantly volume-dependent manner, and by 93-100 % over the 11 weeks following the spill in the highest treatment. Dilbit altered community structure of benthic invertebrates, but not abundance. One-year post-spill and following oil removal using traditional skimming and absorption techniques, benthic richness and abundance were greater among all treatments than the previous year. These results indicate that recovery in community composition is possible following oil removal from a lake ecosystem. Research is needed concerning the mechanisms by which surface oil directly affect adult invertebrates, whether through limiting oviposition, limiting emergence, or both. The response of benthic communities to sediment tar mats is also warranted.

Seasonal variation in the canopy color of temperate evergreen conifer forests.

Evergreen conifer forests are the most prevalent land cover type in North America. Seasonal changes in the color of evergreen forest canopies have been documented with near-surface remote sensing, but the physiological mechanisms underlying these changes, and the implications for photosynthetic uptake, have not been fully elucidated. Here, we integrate on-the-ground phenological observations, leaf-level physiological measurements, near surface hyperspectral remote sensing and digital camera imagery, tower-based CO2 flux measurements, and a predictive model to simulate seasonal canopy color dynamics. We show that seasonal changes in canopy color occur independently of new leaf production, but track changes in chlorophyll fluorescence, the photochemical reflectance index, and leaf pigmentation. We demonstrate that at winter-dormant sites, seasonal changes in canopy color can be used to predict the onset of canopy-level photosynthesis in spring, and its cessation in autumn. Finally, we parameterize a simple temperature-based model to predict the seasonal cycle of canopy greenness, and we show that the model successfully simulates interannual variation in the timing of changes in canopy color. These results provide mechanistic insight into the factors driving seasonal changes in evergreen canopy color and provide opportunities to monitor and model seasonal variation in photosynthetic activity using color-based vegetation indices.

Spatial and temporal variations in global soil respiration and their relationships with climate and land cover.

Soil respiration (R s) represents the largest flux of CO2 from terrestrial ecosystems to the atmosphere, but its spatial and temporal changes as well as the driving forces are not well understood. We derived a product of annual global R s from 2000 to 2014 at 1 km by 1 km spatial resolution using remote sensing data and biome-specific statistical models. Different from the existing view that climate change dominated changes in R s, we showed that land-cover change played a more important role in regulating R s changes in temperate and boreal regions during 2000-2014. Significant changes in R s occurred more frequently in areas with significant changes in short vegetation cover (i.e., all vegetation shorter than 5 m in height) than in areas with significant climate change. These results contribute to our understanding of global R s patterns and highlight the importance of land-cover change in driving global and regional R s changes.

Ecosystem transpiration and evaporation: Insights from three water flux partitioning methods across FLUXNET sites.

We apply and compare three widely applicable methods for estimating ecosystem transpiration (T) from eddy covariance (EC) data across 251 FLUXNET sites globally. All three methods are based on the coupled water and carbon relationship, but they differ in assumptions and parameterizations. Intercomparison of the three daily T estimates shows high correlation among methods (R between .89 and .94), but a spread in magnitudes of T/ET (evapotranspiration) from 45% to 77%. When compared at six sites with concurrent EC and sap flow measurements, all three EC-based T estimates show higher correlation to sap flow-based T than EC-based ET. The partitioning methods show expected tendencies of T/ET increasing with dryness (vapor pressure deficit and days since rain) and with leaf area index (LAI). Analysis of 140 sites with high-quality estimates for at least two continuous years shows that T/ET variability was 1.6 times higher across sites than across years. Spatial variability of T/ET was primarily driven by vegetation and soil characteristics (e.g., crop or grass designation, minimum annual LAI, soil coarse fragment volume) rather than climatic variables such as mean/standard deviation of temperature or precipitation. Overall, T and T/ET patterns are plausible and qualitatively consistent among the different water flux partitioning methods implying a significant advance made for estimating and understanding T globally, while the magnitudes remain uncertain. Our results represent the first extensive EC data-based estimates of ecosystem T permitting a data-driven perspective on the role of plants' water use for global water and carbon cycling in a changing climate.

Precision Measurement of the Neutron Scattering Length of

We report a 0.08% measurement of the bound neutron scattering length of ^{4}He using neutron interferometry. The result is b=(3.0982±0.0021[stat]±0.0014[syst]) fm. The corresponding free atomic scattering length is a=(2.4746±0.0017[stat]±0.0011[syst]) fm. With this result the world average becomes b=(3.0993±0.0025) fm, a 2% downward shift and a reduction in uncertainty by more than a factor of six. Our result is in disagreement with a previous neutron interferometric measurement but is in good agreement with earlier measurements using neutron transmission.

Gap-filling approaches for eddy covariance methane fluxes: A comparison of three machine learning algorithms and a traditional method with principal component analysis.

Methane flux (FCH4 ) measurements using the eddy covariance technique have increased over the past decade. FCH4 measurements commonly include data gaps, as is the case with CO2 and energy fluxes. However, gap-filling FCH4 data are more challenging than other fluxes due to its unique characteristics including multidriver dependency, variabilities across multiple timescales, nonstationarity, spatial heterogeneity of flux footprints, and lagged influence of biophysical drivers. Some researchers have applied a marginal distribution sampling (MDS) algorithm, a standard gap-filling method for other fluxes, to FCH4 datasets, and others have applied artificial neural networks (ANN) to resolve the challenging characteristics of FCH4 . However, there is still no consensus regarding FCH4 gap-filling methods due to limited comparative research. We are not aware of the applications of machine learning (ML) algorithms beyond ANN to FCH4 datasets. Here, we compare the performance of MDS and three ML algorithms (ANN, random forest [RF], and support vector machine [SVM]) using multiple combinations of ancillary variables. In addition, we applied principal component analysis (PCA) as an input to the algorithms to address multidriver dependency of FCH4 and reduce the internal complexity of the algorithmic structures. We applied this approach to five benchmark FCH4 datasets from both natural and managed systems located in temperate and tropical wetlands and rice paddies. Results indicate that PCA improved the performance of MDS compared to traditional inputs. ML algorithms performed better when using all available biophysical variables compared to using PCA-derived inputs. Overall, RF was found to outperform other techniques for all sites. We found gap-filling uncertainty is much larger than measurement uncertainty in accumulated CH4 budget. Therefore, the approach used for FCH4 gap filling can have important implications for characterizing annual ecosystem-scale methane budgets, the accuracy of which is important for evaluating natural and managed systems and their interactions with global change processes.