Seizure freedom using a regional approach to responsive neurostimulation for multifocal drug-resistant epilepsy: illustrative case.

BACKGROUND: Responsive neurostimulation (RNS) has emerged as an effective neuromodulatory intervention for patients with medically refractory epilepsy who are not candidates for resective or ablative surgery. However, in patients with multifocal seizures arising from a widely distributed network, optimizing lead placement can be challenging. OBSERVATIONS: Here, the authors present the case of a patient with drug-resistant multifocal, nonlateralizing seizures and multiple developmental brain lesions who underwent phase II monitoring with stereoelectroencephalography electrodes targeting the lesion and surrounding cortex as well as the centromedian thalamus. Neurophysiological signals observed during recorded events implicated a seizure network within the left perisylvian polymicrogyria, involving the left parietal operculum, insula, and centromedian thalamic regions rather than a single focus. LESSONS: Using a regional RNS approach to modulate this network, the patient improved from 5 seizures a day to freedom from disabling seizures shortly after lead implantation despite low stimulation parameters. This has implications for understanding the timescale of adaptive mechanisms that occur in response to stimulation and supports the use of RNS as a surgical treatment for drug-resistant epilepsy. https://thejns.org/doi/10.3171/CASE24369.

Water limitation drives species loss in grassland communities after nitrogen addition and warming.

Nutrient addition, particularly nitrogen, often increases plant aboveground biomass but causes species loss. Asymmetric competition for light is frequently assumed to explain the biomass-driven species loss. However, it remains unclear whether other factors such as water can also play a role. Increased aboveground leaf area following nitrogen addition and warming may increase transpiration and cause water limitation, leading to a decline in diversity. To test this, we conducted field measurements in a grassland community exposed to nitrogen and water addition, and warming. We found that warming and/or nitrogen addition significantly increased aboveground biomass but reduced species richness. Water addition prevented species loss in either nitrogen-enriched or warmed treatments, while it partially mitigated species loss in the treatment exposed to increases in both temperature and nitrogen. These findings thus strongly suggest that water limitation can be an important driver of species loss as biomass increases after nitrogen addition and warming when soil moisture is limiting. This result is further supported by a meta-analysis of published studies across grasslands worldwide. Our study indicates that loss of grassland species richness in the future may be greatest under a scenario of increasing temperature and nitrogen deposition, but decreasing precipitation.

Inhibiting methanogenesis by targeting thermodynamics and enzymatic reactions in mixed cultures of rumen microbes in vitro.

Mitigation of enteric methane (CH4) emissions from ruminant livestock represents an opportunity to improve the sustainability, productivity, and profitability of beef and dairy production. Ruminal methanogenesis can be mitigated via two primary strategies: (1) alternative electron acceptors and (2) enzymatic inhibition of methanogenic pathways. The former utilizes the thermodynamic favorability of certain reactions such as nitrate/nitrite reduction to ammonia (NH3) while the latter targets specific enzymes using structural analogs of CH4 and methanogenic cofactors such as bromochloromethane (BCM). In this study, we investigated the effects of four additives and their combinations on CH4 production by rumen microbes in batch culture. Sodium nitrate (NaNO3), sodium sulfate (Na2SO4), and 3-nitro-1-propionate (3NPA) were included as thermodynamic inhibitors, whereas BCM was included as a enzymatic inhibitor. Individual additives were evaluated at three levels of inclusion in experiments 1 and 2. Highest level of each additive was used to determine the combined effect of NaNO3 + Na2SO4 (NS), NS + 3NPA (NSP), and NSP + BCM (NSPB) in experiments 3 and 4. Experimental diets were high, medium, and low forage diets (HF, MF, and LF, respectively) and consisted of alfalfa hay and a concentrate mix formulated to obtain the following forage to concentrate ratios: 70:30, 50:50, and 30:70, respectively. Diets with additives were placed in fermentation culture bottles and incubated in a water bath (39°C) for 6, 12, or 24h. Microbial DNA was extracted for 16S rRNA and ITS gene amplicon sequencing. In experiments 1 and 2, CH4 concentrations in control cultures decreased in the order of LF, MF, and HF diets, whereas in experiments 3 and 4, CH4 was highest in MF diet followed by HF and LF diets. Culture pH and NH3 in the control decreased in the order of HF, MF, to LF as expected. NaNO3 decreased (p < 0.001) CH4 and butyrate and increased acetate and propionate (p < 0.03 and 0.003, respectively). Cultures receiving NaNO3 had an enrichment of microorganisms capable of nitrate and nitrite reduction. 3NPA also decreased CH4 at 6h with no further decrease at 24 h (p < 0.001). BCM significantly inhibited methanogenesis regardless of inclusion levels as well as in the presence of the thermodynamic inhibitors (p < 0.001) while enriching succinate producers and assimilators as well as propionate producers (p adj < 0.05). However, individual inclusion of BCM decreased total short chain fatty acid (SCFA) concentrations (p < 0.002). Inhibition of methanogenesis with BCM individually and in combination with the other additives increased gaseous H2 concentrations (p < 0.001 individually and 0.028 in combination) while decreasing acetate to propionate ratio (p < 0.001). Only the cultures treated with BCM in combination with other additives significantly (padj < 0.05) decreased the abundance of Methanobrevibacter expressed as log fold change. Overall, the combination of thermodynamic and enzymatic inhibitors presented a promising effect on ruminal fermentation in-vitro, inhibiting methanogenesis while optimizing the other fermentation parameters such as pH, NH3, and SCFAs. Here, we provide a proof of concept that the combination of an electron acceptor and a methane analog may be exploited to improve microbial efficiency via methanogenesis inhibition.

The value of long-term ecological research for evolutionary insights.

Scientists must have an integrative understanding of ecology and evolution across spatial and temporal scales to predict how species will respond to global change. Although comprehensively investigating these processes in nature is challenging, the infrastructure and data from long-term ecological research networks can support cross-disciplinary investigations. We propose using these networks to advance our understanding of fundamental evolutionary processes and responses to global change. For ecologists, we outline how long-term ecological experiments can be expanded for evolutionary inquiry, and for evolutionary biologists, we illustrate how observed long-term ecological patterns may motivate new evolutionary questions. We advocate for collaborative, multi-site investigations and discuss barriers to conducting evolutionary work at network sites. Ultimately, these networks offer valuable information and opportunities to improve predictions of species' responses to global change.

Prevailing wind patterns influence the distribution of plastics in small urban lakes.

Cities generate large amounts of plastic waste and thus are often major sources of plastic pollution. Microplastics (particles < 5 mm) are a growing ecological concern as they are readily transported through the environment by wind, flowing water, and other transport processes. Here, we report the findings of an intensive field study that tested associations between prevailing winds and the distribution of plastic pollution around urban lakes (n = 20 lakes) in offshore sediments, shoreline sediments, and surface waters. We tested and found support for the hypothesis that prevailing winds influence the distribution of plastics around lakes. Overall, lakes had greater proportions of macroplastics (i.e., large plastic trash) and microplastics in sediments collected along northern lake shorelines. Notably, we found that macroplastic trash and total microplastics were, respectively, 1.7 and 3 times more abundant in sediments sampled along northern shorelines. Contrary to our expectation, we also found that microplastics in offshore sediments were in greater proportions along western lake shorelines, indicating that wind-driven processes might not explain the distribution of plastics in all lake zones. Furthermore, we observed no discernable patterns within lake surface waters and only captured a handful of suspended microplastic fragments and films from the water column. Overall, our findings revealed that the heterogeneous accumulation of plastic pollution at a lake is influenced, in part, by wind-driven processes. Moreover, these patterns extend across a network of lakes that were distributed across an urbanized landscape.

Heterogeneity promotes resilience in restored prairie: Implications for the environmental heterogeneity hypothesis.

Enhancing resilience in formerly degraded ecosystems is an important goal of restoration ecology. However, evidence for the recovery of resilience and its underlying mechanisms require long-term experiments and comparison with reference ecosystems. We used data from an experimental prairie restoration that featured long-term soil heterogeneity manipulations and data from two long-term experiments located in a comparable remnant (reference) prairie to (1) quantify the recovery of ecosystem functioning (i.e., productivity) relative to remnant prairie, (2) compare the resilience of restored and remnant prairies to a natural drought, and (3) test whether soil heterogeneity enhances resilience of restored prairie. We compared sensitivity and legacy effects between prairie types (remnant and restored) and among four prairie sites that included two remnant prairie sites and prairie restored under homogeneous and heterogeneous soil conditions. We measured sensitivity and resilience as the proportional change in aboveground net primary productivity (ANPP) during and following drought (sensitivity and legacy effects, respectively) relative to average ANPP based on 4 pre-drought years (2014-2017). In nondrought years, total ANPP was similar between remnant and restored prairie, but remnant prairie had higher grass productivity and lower forb productivity compared with restored prairie. These ANPP patterns generally persisted during drought. The sensitivity of total ANPP to drought was similar between restored and remnant prairie, but grasses in the restored prairie were more sensitive to drought. Post-drought legacy effects were more positive in the restored prairie, and we attributed this to the more positive and less variable legacy response of forb ANPP in the restored prairie, especially in the heterogeneous soil treatment. Our results suggest that productivity recovers in restored prairie and exhibits similar sensitivity to drought as in remnant prairie. Furthermore, creating heterogeneity promotes forb productivity and enhances restored prairie resilience to drought.

Multi-modality Regional Alignment Network for Covid X-Ray Survival Prediction and Report Generation.

In response to the worldwide COVID-19 pandemic, advanced automated technologies have emerged as valuable tools to aid healthcare professionals in managing an increased workload by improving radiology report generation and prognostic analysis. This study proposes a Multi-modality Regional Alignment Network (MRANet), an explainable model for radiology report generation and survival prediction that focuses on high-risk regions. By learning spatial correlation in the detector, MRANet visually grounds region-specific descriptions, providing robust anatomical regions with a completion strategy. The visual features of each region are embedded using a novel survival attention mechanism, offering spatially and risk-aware features for sentence encoding while maintaining global coherence across tasks. A cross-domain LLMs-Alignment is employed to enhance the image-to-text transfer process, resulting in sentences rich with clinical detail and improved explainability for radiologists. Multi-center experiments validate the overall performance and each module's composition within the model, encouraging further advancements in radiology report generation research emphasizing clinical interpretation and trustworthiness in AI models applied to medical studies.

Infarcts Due to Large Vessel Occlusions Continue to Grow Despite Near-Complete Reperfusion After Endovascular Treatment.

BACKGROUND AND PURPOSE: Infarcts in acute ischemic stroke (AIS) patients may continue to grow even after reperfusion, due to mechanisms such as microvascular obstruction and reperfusion injury. We investigated whether and how much infarcts grow in AIS patients after near-complete (expanded Thrombolysis in Cerebral Infarction [eTICI] 2c/3) reperfusion following endovascular treatment (EVT), and to assess the association of post-reperfusion infarct growth with clinical outcomes. METHODS: Data are from a single-center retrospective observational cohort study that included AIS patients undergoing EVT with near-complete reperfusion who received diffusion-weighted magnetic resonance imaging (MRI) within 2 hours post-EVT and 24 hours after EVT. Association of infarct growth between 2 and 24 hours post-EVT and 24-hour National Institutes of Health Stroke Scale (NIHSS) as well as 90-day modified Rankin Scale score was assessed using multivariable logistic regression. RESULTS: Ninety-four of 155 (60.6%) patients achieved eTICI 2c/3 and were included in the analysis. Eighty of these 94 (85.1%) patients showed infarct growth between 2 and 24 hours post-reperfusion. Infarct growth ≥5 mL was seen in 39/94 (41.5%) patients, and infarct growth ≥10 mL was seen in 20/94 (21.3%) patients. Median infarct growth between 2 and 24 hours post-reperfusion was 4.5 mL (interquartile range: 0.4-9.2 mL). Post-reperfusion infarct growth was associated with the 24-hour NIHSS in multivariable analysis (odds ratio: 1.16 [95% confidence interval 1.09-1.24], P<0.01). CONCLUSION: Infarcts continue to grow after EVT, even if near-complete reperfusion is achieved. Investigating the underlying mechanisms may inform future therapeutic approaches for mitigating the process and help improve patient outcome.

MRI-Based Prediction of Clinical Improvement after Ventricular Shunt Placement for Normal Pressure Hydrocephalus: Development and Evaluation of an Integrated Multisequence Machine Learning Algorithm.

BACKGROUND AND PURPOSE: Symptoms of normal pressure hydrocephalus (NPH) are sometimes refractory to shunt placement, with limited ability to predict improvement for individual patients. We evaluated an MRI-based artificial intelligence method to predict postshunt NPH symptom improvement. MATERIALS AND METHODS: Patients with NPH who underwent MRI before shunt placement at a single center (2014-2021) were identified. Twelve-month postshunt improvement in mRS, incontinence, gait, and cognition were retrospectively abstracted from clinical documentation. 3D deep residual neural networks were built on skull-stripped T2-weighted and FLAIR images. Predictions based on both sequences were fused by additional network layers. Patients from 2014-2019 were used for parameter optimization, while those from 2020-2021 were used for testing. Models were validated on an external validation data set from a second institution (n = 33). RESULTS: Of 249 patients, n = 201 and n = 185 were included in the T2-based and FLAIR-based models according to imaging availability. The combination of T2-weighted and FLAIR sequences offered the best performance in mRS and gait improvement predictions relative to models trained on imaging acquired by using only 1 sequence, with area under the receiver operating characteristic (AUROC) values of 0.7395 [0.5765-0.9024] for mRS and 0.8816 [0.8030-0.9602] for gait. For urinary incontinence and cognition, combined model performances on predicting outcomes were similar to FLAIR-only performance, with AUROC values of 0.7874 [0.6845-0.8903] and 0.7230 [0.5600-0.8859]. CONCLUSIONS: Application of a combined algorithm by using both T2-weighted and FLAIR sequences offered the best image-based prediction of postshunt symptom improvement, particularly for gait and overall function in terms of mRS.

A global meta-analysis on the effects of organic and inorganic fertilization on grasslands and croplands.

A central role for nature-based solution is to identify optimal management practices to address environmental challenges, including carbon sequestration and biodiversity conservation. Inorganic fertilization increases plant aboveground biomass but often causes a tradeoff with plant diversity loss. It remains unclear, however, whether organic fertilization, as a potential nature-based solution, could alter this tradeoff by increasing aboveground biomass without plant diversity loss. Here we compile data from 537 experiments on organic and inorganic fertilization across grasslands and croplands worldwide to evaluate the responses of aboveground biomass, plant diversity, and soil organic carbon (SOC). Both organic and inorganic fertilization increase aboveground biomass by 56% and 42% relative to ambient, respectively. However, only inorganic fertilization decreases plant diversity, while organic fertilization increases plant diversity in grasslands with greater soil water content. Moreover, organic fertilization increases SOC in grasslands by 19% and 15% relative to ambient and inorganic fertilization, respectively. The positive effect of organic fertilization on SOC increases with increasing mean annual temperature in grasslands, a pattern not observed in croplands. Collectively, our findings highlight organic fertilization as a potential nature-based solution that can increase two ecosystem services of grasslands, forage production, and soil carbon storage, without a tradeoff in plant diversity loss.

De-Biased Disentanglement Learning for Pulmonary Embolism Survival Prediction on Multimodal Data.

Health disparities among marginalized populations with lower socioeconomic status significantly impact the fairness and effectiveness of healthcare delivery. The increasing integration of artificial intelligence (AI) into healthcare presents an opportunity to address these inequalities, provided that AI models are free from bias. This paper aims to address the bias challenges by population disparities within healthcare systems, existing in the presentation of and development of algorithms, leading to inequitable medical implementation for conditions such as pulmonary embolism (PE) prognosis. In this study, we explore the diverse bias in healthcare systems, which highlights the demand for a holistic framework to reducing bias by complementary aggregation. By leveraging de-biasing deep survival prediction models, we propose a framework that disentangles identifiable information from images, text reports, and clinical variables to mitigate potential biases within multimodal datasets. Our study offers several advantages over traditional clinical-based survival prediction methods, including richer survival-related characteristics and bias-complementary predicted results. By improving the robustness of survival analysis through this framework, we aim to benefit patients, clinicians, and researchers by enhancing fairness and accuracy in healthcare AI systems.

Updates on coding in dermatology.

Correct coding is an important component of effective dermatology practice management. Over the past several years there have been updates to many commonly used codes within dermatology. This review highlights many of these updates, such as: the skin biopsy codes have been subdivided to reflect the different biopsy techniques. The definition of complex linear repairs has been updated and clarified. Outpatient and inpatient evaluation and management visits have new coding guidelines to determine level of care. Dermatopathology consultation codes have been updated and category III codes related to digital pathology have been created. Understanding the details and nuances of each of these categories of codes is vital to ensuring appropriate coding is performed.

Sheet Models for Methylaluminoxane (MAO) Activators? A Theoretical Case Study involving rac-Me2Si(η5-C9H6)2Zr (SBIZr) Complexes.

Activation of SBIZrMe2 or SBIZrMeCl and a sheet model for an active component of hydrolytic MAO, (MeAlO)16(Me3Al)6, (16,6) has been studied by DFT. Contact ion-pair formation occurs through the intermediacy of SBIZrMe(Cl) or SBIZrMe2 reacting with sheet 16,6 to furnish SBIZrMe-µ-X(MeAlO)16(Me3Al)6 (2, X=Me, Cl). Contact ion-pairs 2 would be in equilibrium with heterodinuclear catalyst precursors [SBIZrMe2AlMe2][(MeAlO)16(Me3Al)6X] (3 (X=Me, Cl) through reversible binding of Me3Al at higher Al : Zr ratios. Calculations show that formation of ion-pairs 3 from contact ion-pairs 2 is more favourable for the SBIZr compared with the parent Cp2Zr complexes. TD-DFT calculations were conducted on relevant SBIZr complexes to relate the results to earlier spectroscopic studies of catalyst activation using UV-Vis spectroscopy. Finally, propene insertion into ion-pairs 2, SBIZrMe-µ-MeB(C6F5)3 (6) and [SBIZrMe][B(C6F5)4] (7) was studied at M06-2X/TZVP level of theory. These studies suggest that contact ion-pairs 2 are significantly less reactive towards insertion than 6 or 7, in disagreement with experiment.

Expanding the flexibility of base editing for high-throughput genetic screens in bacteria.

Genome-wide screens have become powerful tools for elucidating genotype-to-phenotype relationships in bacteria. Of the varying techniques to achieve knockout and knockdown, CRISPR base editors are emerging as promising options. However, the limited number of available, efficient target sites hampers their use for high-throughput screening. Here, we make multiple advances to enable flexible base editing as part of high-throughput genetic screening in bacteria. We first co-opt the Streptococcus canis Cas9 that exhibits more flexible protospacer-adjacent motif recognition than the traditional Streptococcus pyogenes Cas9. We then expand beyond introducing premature stop codons by mutating start codons. Next, we derive guide design rules by applying machine learning to an essentiality screen conducted in Escherichia coli. Finally, we rescue poorly edited sites by combining base editing with Cas9-induced cleavage of unedited cells, thereby enriching for intended edits. The efficiency of this dual system was validated through a conditional essentiality screen based on growth in minimal media. Overall, expanding the scope of genome-wide knockout screens with base editors could further facilitate the investigation of new gene functions and interactions in bacteria.

Development of a Novel DNA Mono-alkylator Platform for Antibody-Drug Conjugates.

Although microtubule inhibitors (MTI) remain a therapeutically valuable payload option for antibody-drug conjugates (ADC), some cancers do not respond to MTI-based ADCs. Efforts to fill this therapeutic gap have led to a recent expansion of the ADC payload "toolbox" to include payloads with novel mechanisms of action such as topoisomerase inhibition and DNA cross-linking. We present here the development of a novel DNA mono-alkylator ADC platform that exhibits sustained tumor growth suppression at single doses in MTI-resistant tumors and is well tolerated in the rat upon repeat dosing. A phosphoramidate prodrug of the payload enables low ADC aggregation even at drug-to-antibody ratios of 5:1 while still delivering a bystander-capable payload that is effective in multidrug resistant (MDR)-overexpressing cell lines. The platform was comparable in xenograft studies to the clinical benchmark DNA mono-alkylator ADC platform DGN459 but with a significantly better tolerability profile in rats. Thus, the activity and tolerability profile of this new platform make it a viable option for the development of ADCs.

Extreme drought impacts have been underestimated in grasslands and shrublands globally.

Climate change is increasing the frequency and severity of short-term (~1 y) drought events-the most common duration of drought-globally. Yet the impact of this intensification of drought on ecosystem functioning remains poorly resolved. This is due in part to the widely disparate approaches ecologists have employed to study drought, variation in the severity and duration of drought studied, and differences among ecosystems in vegetation, edaphic and climatic attributes that can mediate drought impacts. To overcome these problems and better identify the factors that modulate drought responses, we used a coordinated distributed experiment to quantify the impact of short-term drought on grassland and shrubland ecosystems. With a standardized approach, we imposed ~a single year of drought at 100 sites on six continents. Here we show that loss of a foundational ecosystem function-aboveground net primary production (ANPP)-was 60% greater at sites that experienced statistically extreme drought (1-in-100-y event) vs. those sites where drought was nominal (historically more common) in magnitude (35% vs. 21%, respectively). This reduction in a key carbon cycle process with a single year of extreme drought greatly exceeds previously reported losses for grasslands and shrublands. Our global experiment also revealed high variability in drought response but that relative reductions in ANPP were greater in drier ecosystems and those with fewer plant species. Overall, our results demonstrate with unprecedented rigor that the global impacts of projected increases in drought severity have been significantly underestimated and that drier and less diverse sites are likely to be most vulnerable to extreme drought.

Modeling diffusion-weighted imaging lesion expansion between 2 and 24 h after endovascular thrombectomy in acute ischemic stroke.

PURPOSE: Diffusion-weighted imaging (DWI) lesion expansion after endovascular thrombectomy (EVT) is not well characterized. We used serial diffusion-weighted magnetic resonance imaging (MRI) to measure lesion expansion between 2 and 24 h after EVT. METHODS: In this single-center observational analysis of patients with acute ischemic stroke due to large vessel occlusion, DWI was performed post-EVT (< 2 h after closure) and 24-h later. DWI lesion expansion was evaluated using multivariate generalized linear mixed modeling with various clinical moderators. RESULTS: We included 151 patients, of which 133 (88%) had DWI lesion expansion, defined as a positive change in lesion volume between 2 and 24 h. In an unadjusted analysis, median baseline DWI lesion volume immediately post-EVT was 15.0 mL (IQR: 6.6-36.8) and median DWI lesion volume 24 h post-EVT was 20.8 mL (IQR: 9.4-66.6), representing a median change of 6.1 mL (IQR: 1.5-17.7), or a 39% increase. There were no significant associations among univariable models of lesion expansion. Adjusted models of DWI lesion expansion demonstrated that relative lesion expansion (defined as final/initial DWI lesion volume) was consistent across eTICI scores (0-2a, 0.52%; 2b, 0.49%; 2c-3, 0.42%, p = 0.69). For every 1 mL increase in lesion volume, there was 2% odds of an increase in 90-day mRS (OR: 1.021, 95%CI [1.009, 1.034], p < 0.001). CONCLUSION: We observed substantial lesion expansion post-EVT whereby relative lesion expansion was consistent across eTICI categories, and greater absolute lesion expansion was associated with worse clinical outcome. Our findings suggest that alternate endpoints for cerebroprotectant trials may be feasible.

Interrogating two extensively self-targeting Type I CRISPR-Cas systems in Xanthomonas albilineans reveals distinct anti-CRISPR proteins that block DNA degradation.

CRISPR-Cas systems store fragments of invader DNA as spacers to recognize and clear those same invaders in the future. Spacers can also be acquired from the host's genomic DNA, leading to lethal self-targeting. While self-targeting can be circumvented through different mechanisms, natural examples remain poorly explored. Here, we investigate extensive self-targeting by two CRISPR-Cas systems encoding 24 self-targeting spacers in the plant pathogen Xanthomonas albilineans. We show that the native I-C and I-F1 systems are actively expressed and that CRISPR RNAs are properly processed. When expressed in Escherichia coli, each Cascade complex binds its PAM-flanked DNA target to block transcription, while the addition of Cas3 paired with genome targeting induces cell killing. While exploring how X. albilineans survives self-targeting, we predicted putative anti-CRISPR proteins (Acrs) encoded within the bacterium's genome. Screening of identified candidates with cell-free transcription-translation systems and in E. coli revealed two Acrs, which we named AcrIC11 and AcrIF12Xal, that inhibit the activity of Cas3 but not Cascade of the respective system. While AcrF12Xal is homologous to AcrIF12, AcrIC11 shares sequence and structural homology with the anti-restriction protein KlcA. These findings help explain tolerance of self-targeting through two CRISPR-Cas systems and expand the known suite of DNA degradation-inhibiting Acrs.

Grassland sensitivity to drought is related to functional composition across East Asia and North America.

Plant traits can be helpful for understanding grassland ecosystem responses to climate extremes, such as severe drought. However, intercontinental comparisons of how drought affects plant functional traits and ecosystem functioning are rare. The Extreme Drought in Grasslands experiment (EDGE) was established across the major grassland types in East Asia and North America (six sites on each continent) to measure variability in grassland ecosystem sensitivity to extreme, prolonged drought. At all sites, we quantified community-weighted mean functional composition and functional diversity of two leaf economic traits, specific leaf area and leaf nitrogen content, in response to drought. We found that experimental drought significantly increased community-weighted means of specific leaf area and leaf nitrogen content at all North American sites and at the wetter East Asian sites, but drought decreased community-weighted means of these traits at moderate to dry East Asian sites. Drought significantly decreased functional richness but increased functional evenness and dispersion at most East Asian and North American sites. Ecosystem drought sensitivity (percentage reduction in aboveground net primary productivity) positively correlated with community-weighted means of specific leaf area and leaf nitrogen content and negatively correlated with functional diversity (i.e., richness) on an intercontinental scale, but results differed within regions. These findings highlight both broad generalities but also unique responses to drought of community-weighted trait means as well as their functional diversity across grassland ecosystems.