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Abstract Multi-year El Niño-Southern Oscillation (ENSO) events, where the warming (El Niño) or cooling (La Niña) extends beyond a single year, have become increasingly prominent in recent decades. Using observations and climate model simulations, we show that the South Pacific Oscillation (SPO) plays a crucial, previously unrecognized role in determining whether ENSO evolves into a multi-year event. Specifically, when an El Niño (La Niña) triggers a positive (negative) SPO in the extratropical Southern Hemisphere during its decaying phase, the SPO feedbacks onto the tropical Pacific through the wind-evaporation-sea surface temperature mechanism, helping sustain ENSO into a multi-year event. This SPO–ENSO interaction is absent in single-year ENSO events. Furthermore, whether ENSO can trigger the SPO depends systematically on the central SST anomaly location for El Niños and the anomaly intensity for La Niñas, with interference from atmospheric internal variability. These findings highlight the importance of including off-equatorial processes from the Southern Hemisphere in studies of ENSO complexity dynamics. 

Birds play a crucial role in maintaining the balance and health of ecosystems worldwide, with their significance extending from ecological functions to cultural symbolism. Ecologically, birds contribute to pest control by preying on insects, regulating populations, and mitigating agricultural damage. They also aid in seed dispersal and pollination, facilitating vegetation growth and plant reproduction. Furthermore, birds serve as environmental indicators, reflecting broader ecological shifts. Recently, the National Ecological Observation Network (NEON) has undertaken the task of monitoring bird populations across various U.S. ecosystems. The project aims to decipher bird abundance patterns during peak growing seasons, synthesizing data on variables such as bird counts, beetle populations, latitude, longitude, tree dimensions, and vegetation productivity during 2017-2022 sourced from NEON databases. The findings reveal that bird counts decrease from low to high latitudes, with both beetles and vegetation productivity positively influencing bird abundance, while tree breast height diameter shows weak correlation. Strong inter-annual variations in bird counts were observed nationwide. Both correlation analysis and structural equation modeling underscore vegetation's pivotal role in bird abundance. In essence, the developed bird count data system offers valuable insights into bird and ecosystem health, aiding communities in understanding and preserving these vital ecosystems. 

Northern forest soils are vital for climate change mitigation since upland sandy soils favor the net consumption/oxidation of atmospheric methane (CH4). We are studying biogeochemical CH4 cycle processes in a Northern Forest (Howland Research Forest, Maine), where upland soils are interspersed with wetland (Sphagnum bog), and upland-wetland transition soils along with hummock-hollow microtopography. This complex mosaic of microsites with sources and sinks of CH4 is subjected to change under future wet climates projected for this region, with a potential for these forests to shift from a net CH4 sink to a net CH4 source. Net CH4 emissions in a wet climate can increase either by inhibiting methanotrophs or favoring methanogens, or both. Thus, quantifying underlying processes of gross CH4 production and consumption can reduce the uncertainty of CH4 sink/source estimation in this critical ecosystem. We have collected baseline soil data across the forest's landscape including Total Carbon and Total Nitrogen with the Elemental Analyzer, Gravimetric Soil Moisture, and pH. Furthermore, stable isotope dilution method will serve as a proxy for methanogenic and methanotrophic activities to quantify gross rates of CH4 production and consumption from a flooding (wet-up) experiment in Howland Forest. We will differentiate between CH4 consumption and production by measuring both the change in the amount of CH4 and the ratio between labeled and unlabeled CH4 in a closed system. We will analyze the stable C isotope in 13CH4 to determine gross rates of CH4 production and oxidation in situ and within laboratory incubations. The in situ stable isotope dilution technique will be compared with the gas push-pull method, to test the suitability of a simple, low cost method to quantify gross CH4 oxidation rates. Novel data obtained in this study will constrain CH4 cycle processes in a biogeochemical model to quantify CH4 source-sink potential in Northern Forests under current and future climatic conditions. 

Mosquitoes, deemed the deadliest creatures on Earth due to the diseases they transmit, have caused more fatalities than all recorded wars combined. Investigating the macroecology of mosquitoes on a continental scale is imperative for effective disease management and prevention. Our study utilized observational data from 17 sites within the National Ecological Observation Network across the United States. Extracting information from three NEON databases—mosquito samples, mosquito pathogen status, and weather statistics—we analyzed 45,000 labeled data points to elucidate the spatial distribution of mosquito abundance and its environmental determinants. A discernible biogeographic pattern of mosquito abundance emerged, in major natural ecosystems across the US, with the highest abundance observed in mid-latitudes. Our analysis revealed that wind speed and temperature exert significant controls, whereas air pressure and precipitation exhibited minimal influence over mosquito abundance across space. Specifically, temperature positively correlated with mosquito abundance, while wind speed displayed a negative association. Temporally, substantial inter-annual variability characterized mosquito abundance, with clear seasonal patterns observed at each site. Temperature emerged as the primary driver of seasonal fluctuations in mosquito abundance, with sites in middle latitudes exhibiting more pronounced seasonality compared to those at high and low latitudes, likely due to temperature fluctuations. This work, by comprehensively studying mosquitoes and their environmental controls, contributes to the development of targeted interventions, such as vector control programs and vaccine development, ultimately safeguarding human health and reducing the burden of mosquito-borne illnesses on human society. 

Although the tropical intraseaonal variability (TISV), as the most important predictability sources for subseasonal-to-seasonal (S2S) prediction, is dominated by Madden-Julian oscillation (MJO), its significant fraction does not always share the canonical MJO features, especially when the convective activity arrives at Maritime Continent. In this study, using principal oscillation pattern (POP) analysis on the combined fields of daily equatorial convection and zonal wind, two distinct leading TISV modes with relatively slower e-folding decay rates are identified. One is an oscillatory mode with the period of 51 days and e-folding time of 19 days, capturing the eastward propagating (EP) feature of the canonical MJO. The other is a non-oscillatory damping mode with e-folding time of 13.6 days, capturing a standing dipole (SD) with convection anomalies centered over the Maritime Continent and tropical central Pacific, respectively. Compared to the EP mode, the leading moisture anomalies at low level to the east of convection center are diminish for the SD mode, and instead, the strong negative anomalies of moisture and subsidence motion emerge in the tropical central Pacific area, which may be responsible for the distinct propagation features. Without filtering methods used, timeseries of the two POPs could be applied to the real-time monitoring of EP and SD events in the phase-space diagram. The two modes can serve as the simple and objective approach for a better characterization for diverse natures of TISV beyond the canonical MJO description, which may further shed light on dynamics of the TISV and its predictability. 

Abstract Microbial processes are crucial in producing and oxidizing biological methane (CH₄) in natural wetlands. Therefore, modeling methanogenesis and methanotrophy is advantageous for accurately projecting CH₄cycling. Utilizing the CLM‐Microbe model, which explicitly represents the growth and death of methanogens and methanotrophs, we demonstrate that genome‐enabled model parameterization improves model performance in four natural wetlands. Compared to the default model parameterization against CH₄flux, genomic‐enabled model parameterization added another contain on microbial biomass, notably enhancing the precision of simulated CH₄flux. Specifically, the coefficient of determination (R²) increased from 0.45 to 0.74 for Sanjiang Plain, from 0.78 to 0.89 for Changbai Mountain, and from 0.35 to 0.54 for Sallie's Fen, respectively. A drop inR²was observed for the Dajiuhu nature wetland, primarily caused by scatter data points. Theil's coefficient (U) and model efficiency (ME) confirmed the model performance from default parameterization to genome‐enabled model parameterization. Compared with the model solely calibrated to surface CH₄flux, additional constraints of functional gene data led to better CH₄seasonality; meanwhile, genome‐enabled model parameterization established more robust associations between simulated CH₄production rates and environmental factors. Sensitivity analysis underscored the pivotal role of microbial physiology in governing CH₄flux. This genome‐enabled model parameterization offers a valuable promise to integrate fast‐cumulating genomic data with CH₄models to better understand microbial roles in CH₄in the era of climate change.