Fire-prone invasive grasses create novel ecosystem threats by increasing fine-fuel loads and continuity, which can alter fire regimes. While the existence of an invasive grass-fire cycle is well ...known, evidence of altered fire regimes is typically based on local-scale studies or expert knowledge. Here, we quantify the effects of 12 nonnative, invasive grasses on fire occurrence, size, and frequency across 29 US ecoregions encompassing more than one third of the conterminous United States. These 12 grass species promote fire locally and have extensive spatial records of abundant infestations. We combined agency and satellite fire data with records of abundant grass invasion to test for differences in fire regimes between invaded and nearby “uninvaded” habitat. Additionally, we assessed whether invasive grass presence is a significant predictor of altered fire by modeling fire occurrence, size, and frequency as a function of grass invasion, in addition to anthropogenic and ecological covariates relevant to fire. Eight species showed significantly higher fire-occurrence rates, which more than tripled for Schismus barbatus and Pennisetum ciliare. Six species demonstrated significantly higher mean fire frequency, which more than doubled for Neyraudia reynaudiana and Pennisetum ciliare. Grass invasion was significant in fire occurrence and frequency models, but not in fire-size models. The significant differences in fire regimes, coupled with the importance of grass invasion in modeling these differences, suggest that invasive grasses alter US fire regimes at regional scales. As concern about US wildfires grows, accounting for fire-promoting invasive grasses will be imperative for effectively managing ecosystems.
The biotic resistance hypothesis predicts that diverse native communities are more resistant to invasion. However, past studies vary in their support for this hypothesis due to an apparent ...contradiction between experimental studies, which support biotic resistance, and observational studies, which find that native and non‐native species richness are positively related at broad scales (small‐scale studies are more variable). Here, we present a novel analysis of the biotic resistance hypothesis using 24 456 observations of plant richness spanning four community types and seven ecoregions of the United States. Non‐native plant occurrence was negatively related to native plant richness across all community types and ecoregions, although the strength of biotic resistance varied across different ecological, anthropogenic and climatic contexts. Our results strongly support the biotic resistance hypothesis, thus reconciling differences between experimental and observational studies and providing evidence for the shared benefits between invasive species management and native biodiversity conservation.
The biotic resistance hypothesis predicts that diverse native communities are more resistant to invasion, but evidence for this hypothesis varies among past studies. Using a new statistical approach with 24 456 plant surveys across the United States, we found universal support for the biotic resistance hypothesis.
With growing concern about the impacts of fires on ecosystems and economies, satellite products are increasingly being used to understand fire regimes. Concurrently, where available, agency records ...of fires have also been used to assess fire regimes. Yet, it remains unclear if these independent datasets measure the same fires, which raises concerns about the interpretation and benchmarking of models derived from these products. Here, we present a novel product intercomparison of the MODIS burned area and active fire products across the conterminous United States using nearly 250,000 agency reported wildfires as reference data to model consistencies and inconsistencies between all three datasets. We compared agency reported wildfires from the Fire Program Analysis fire occurrence database to the MODIS products to identify which fires were detected vs. omitted by MODIS products relative to agency fire records, and by agency fire records relative to MODIS. We created generalized linear models as a function of fire attributes (e.g. size) and environmental variables (e.g. cloud cover) to predict MODIS detection of agency wildfires, and anthropogenic variables (e.g. agriculture) to predict agency detection of MODIS fires. We modeled fire detection probability separately for MODIS burned area and active fire products, and for the eastern and western U.S. Overall, we found that MODIS product detection rates ranged from 3.5% to 23.4% of all documented agency wildfires >1 ha, and that likelihood of detection increased with fire size. Agency detection rates ranged from 23.5% to 48% of MODIS burned area and active fires. Under ideal conditions, the MODIS active fire product had a 50% probability of detecting a wildfire that grew to at least 10 ha (eastern U.S.) – 78 ha (western U.S.), while the burned area product had a 50% probability of detecting a wildfire that grew to at least 169 ha (eastern U.S.) – 234 ha (western U.S.). Cloud cover and leaf area index were significant predictors of MODIS fire detection, while state boundaries were significant predictors of agency fire detection. This analysis presents an important assessment of the fire attributes and ground conditions that influence MODIS fire detection relative to extensive and increasingly used ground-based wildfire records. The large discrepancy in records of fire occurrence between MODIS and agency fire datasets highlights the need for this type of analysis into the types of fires likely to be included in each database.
•MODIS detected fewer than a quarter of all fire occurrences recorded by agencies.•Agencies recorded fewer than half of all fire occurrences recorded by MODIS.•New estimates for final wildfire size required for MODIS detection.•Fire size and environmental factors are most important in MODIS fire detection.•Land use and political boundaries are most important in agency fire detection.
Humans have a profound effect on fire regimes by increasing the frequency of ignitions. Although ignition is an integral component of understanding and predicting fire, to date fire models have not ...been able to isolate the ignition location, leading to inconsistent use of anthropogenic ignition proxies. Here, we identified fire ignitions from the Moderate Resolution Imaging Spectrometer (MODIS) Burned Area Product (2000-2012) to create the first remotely sensed, consistently derived, and regionally comprehensive fire ignition data set for the western United States. We quantified the spatial relationships between several anthropogenic land-use/disturbance features and ignition for ecoregions within the study area and used hierarchical partitioning to test how the anthropogenic predictors of fire ignition vary among ecoregions. The degree to which anthropogenic features predicted ignition varied considerably by ecoregion, with the strongest relationships found in the Marine West Coast Forest and North American Desert ecoregions. Similarly, the contribution of individual anthropogenic predictors varied greatly among ecoregions. Railroad corridors and agricultural presence tended to be the most important predictors of anthropogenic ignition, while population density and roads were generally poor predictors. Although human population has often been used as a proxy for ignitions at global scales, it is less important at regional scales when more specific land uses (e.g., agriculture) can be identified. The variability of ignition predictors among ecoregions suggests that human activities have heterogeneous impacts in altering fire regimes within different vegetation types and geographies.
Since the 1970s, the magnitude of turtle cold-stun strandings have increased dramatically within the northwestern Atlantic. Here, we examine oceanic, atmospheric, and biological factors that may ...affect the increasing trend of cold-stunned Kemp's ridleys in Cape Cod Bay, Massachusetts, United States of America. Using machine learning and Bayesian inference modeling techniques, we demonstrate higher cold-stunning years occur when the Gulf of Maine has warmer sea surface temperatures in late October through early November. Surprisingly, hatchling numbers in Mexico, a proxy for population abundance, was not identified as an important factor. Further, using our Bayesian count model and forecasted sea surface temperature projections, we predict more than 2,300 Kemp's ridley turtles may cold-stun annually by 2031 as sea surface temperatures continue to increase within the Gulf of Maine. We suggest warmer sea surface temperatures may have modified the northerly distribution of Kemp's ridleys and act as an ecological bridge between the Gulf Stream and nearshore waters. While cold-stunning may currently account for a minor proportion of juvenile mortality, we recommend continuing efforts to rehabilitate cold-stunned individuals to maintain population resiliency for this critically endangered species in the face of a changing climate and continuing anthropogenic threats.
Non‐native, invasive Bromus tectorum (cheatgrass) is pervasive in sagebrush ecosystems in the Great Basin ecoregion of the western United States, competing with native plants and promoting more ...frequent fires. As a result, cheatgrass invasion likely alters carbon (C) storage in the region. Many studies have measured C pools in one or more common vegetation types: native sagebrush, invaded sagebrush and cheatgrass‐dominated (often burned) sites, but these results have yet to be synthesized.
We performed a literature review to identify studies assessing the consequences of invasion on C storage in above‐ground biomass (AGB), below‐ground biomass (BGB), litter, organic soil and total soil. We identified 41 articles containing 386 unique studies and estimated C storage across pools and vegetation types. We used linear mixed models to identify the main predictors of C storage.
We found consistent declines in biomass C with invasion: AGB C was 55% lower in cheatgrass (40 ± 4 g C/m2) than native sagebrush (89 ± 27 g C/m2) and BGB C was 62% lower in cheatgrass (90 ± 17 g C/m2) than native sagebrush (238 ± 60 g C/m2). In contrast, litter C was >4× higher in cheatgrass (154 ± 12 g C/m2) than native sagebrush (32 ± 12 g C/m2). Soil organic C (SOC) in the top 10 cm was significantly higher in cheatgrass than in native or invaded sagebrush. SOC below 20 cm was significantly related to the time since most recent fire and losses were observed in deep SOC in cheatgrass >5 years after a fire. There were no significant changes in total soil C across vegetation types.
Synthesis and applications. Cheatgrass invasion decreases biodiversity and rangeland productivity and alters fire regimes. Our findings indicate cheatgrass invasion also results in persistent biomass carbon (C) losses that occur with sagebrush replacement. We estimate that conversion from native sagebrush to cheatgrass leads to a net reduction of C storage in biomass and litter of 76 g C/m2, or 16 Tg C across the Great Basin without management practices like native sagebrush restoration or cheatgrass removal.
Cheatgrass invasion decreases biodiversity and rangeland productivity and alters fire regimes. Our findings indicate cheatgrass invasion also results in persistent biomass carbon (C) losses that occur with sagebrush replacement. We estimate that conversion from native sagebrush to cheatgrass leads to a net reduction of C storage in biomass and litter of 76 g C/m2, or 16 Tg C across the Great Basin without management practices like native sagebrush restoration or cheatgrass removal.
Receptors that distinguish the multitude of microbes surrounding plants in the environment enable dynamic responses to the biotic and abiotic conditions encountered. In this study, we identify and ...characterise a glycan receptor kinase, EPR3a, closely related to the exopolysaccharide receptor EPR3. Epr3a is up-regulated in roots colonised by arbuscular mycorrhizal (AM) fungi and is able to bind glucans with a branching pattern characteristic of surface-exposed fungal glucans. Expression studies with cellular resolution show localised activation of the Epr3a promoter in cortical root cells containing arbuscules. Fungal infection and intracellular arbuscule formation are reduced in epr3a mutants. In vitro, the EPR3a ectodomain binds cell wall glucans in affinity gel electrophoresis assays. In microscale thermophoresis (MST) assays, rhizobial exopolysaccharide binding is detected with affinities comparable to those observed for EPR3, and both EPR3a and EPR3 bind a well-defined β-1,3/β-1,6 decasaccharide derived from exopolysaccharides of endophytic and pathogenic fungi. Both EPR3a and EPR3 function in the intracellular accommodation of microbes. However, contrasting expression patterns and divergent ligand affinities result in distinct functions in AM colonisation and rhizobial infection in Lotus japonicus. The presence of Epr3a and Epr3 genes in both eudicot and monocot plant genomes suggest a conserved function of these receptor kinases in glycan perception.
Data availability remains a principal factor limiting the use of species distribution models (SDMs) as tools for wildlife conservation and management of rare species. Although data collected in ...systematic and rigorous fashion are preferable, available data for most species of conservation interest are usually low in both quality and number. Here we show that combining records published in peer-reviewed journals and gray literature sources (e.g., theses, government, and NGO reports) with unpublished records obtained by personal communications from relevant stakeholders affect the predicted distribution of spectacled bears (
Tremarctos ornatus
) in Peru. We built SDMs using generalized linear models, random forest, and Maxent, first using a dataset that only included published records, and second with a dataset using both published and unpublished records. All models were replicated ten times with random subsets with controlled sample size. Models that combined published and unpublished spectacled bear records had a better performance, irrespective of with SDM method used, increasing the connectivity of the species’ range, and increasing the overall predicted distribution area than models that only included published records. This was because unpublished records added key new localities, reducing spatial sampling biases. Our study shows that the inclusion of commonly disregarded data such as opportunistic records, reports from natural park rangers, student theses, and data-deficient small studies can make an important contribution to the overall ecological knowledge of rare and difficult-to-study species such as the spectacled bear.
The European Society for Medical Oncology (ESMO) held a virtual consensus-building process on epidermal growth factor receptor (EGFR)-mutant non-small-cell lung cancer in 2021. The consensus included ...a multidisciplinary panel of 34 leading experts in the management of lung cancer. The aim of the consensus was to develop recommendations on topics that are not covered in detail in the current ESMO Clinical Practice Guideline and where the available evidence is either limited or conflicting. The main topics identified for discussion were: (i) tissue and biomarkers analyses; (ii) early and locally advanced disease; (iii) metastatic disease and (iv) clinical trial design, patient’s perspective and miscellaneous. The expert panel was divided into four working groups to address questions relating to one of the four topics outlined above. Relevant scientific literature was reviewed in advance. Recommendations were developed by the working groups and then presented to the entire panel for further discussion and amendment before voting. This manuscript presents the recommendations developed, including findings from the expert panel discussions, consensus recommendations and a summary of evidence supporting each recommendation.
•A virtual consensus on the management of EGFR-mutant NSCLC was organized by the ESMO, including 34 experts from 18 countries.•The experts compiled recommendations with supporting evidence on controversial topics about the EGFR-mutant lung cancer.•Recommendations were formulated for tissue and biomarkers analyses; early, locally advanced and metastatic disease; miscellaneous.
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