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The extent, duration, and seasonality of sea ice and glacial discharge strongly influence Antarctic marine ecosystems. Most organisms' life cycles in this region are attuned to ice seasonality. The annual retreat and melting of sea ice in the austral spring stratifies the upper ocean, triggering large phytoplankton blooms. The magnitude of the blooms is proportional to the winter extent of ice cover, which can act as a barrier to wind mixing. Antarctic krill, one of the most abundant metazoan populations on Earth, consume phytoplankton blooms dominated by large diatoms. Krill, in turn, support a large biomass of predators, including penguins, seals, and whales. Human activity has altered even these remote ecosystems. The western Antarctic Peninsula region has warmed by 7°C over the past 50 years, and sea ice duration has declined by almost 100 days since 1978, causing a decrease in phytoplankton productivity in the northern peninsula region. Besides climate change, Antarctic marine systems have been greatly altered by harvesting of the great whales and now krill. It is unclear to what extent the ecosystems we observe today differ from the pristine state.

Plant phenology research has gained increasing attention because of the sensitivity of phenology to climate change and its consequences for ecosystem function. Recent technological development has made it possible to gather invaluable data at a variety of spatial and ecological scales. Despite our ability to observe phenological change at multiple scales, the mechanistic basis of phenology is still not well understood. Integration of multiple disciplines, including ecology, evolutionary biology, climate science, and remote sensing, with long‐term monitoring data across multiple spatial scales is needed to advance understanding of phenology. We review the mechanisms and major drivers of plant phenology, including temperature, photoperiod, and winter chilling, as well as other factors such as competition, resource limitation, and genetics. Shifts in plant phenology have significant consequences on ecosystem productivity, carbon cycling, competition, food webs, and other ecosystem functions and services. We summarize recent advances in observation techniques across multiple spatial scales, including digital repeat photography, other complementary optical measurements, and solar‐induced fluorescence, to assess our capability to address the importance of these scale‐dependent drivers. Then, we review phenology models as an important component of earth system modeling. We find that the lack of species‐level knowledge and observation data leads to difficulties in the development of vegetation phenology models at ecosystem or community scales. Finally, we recommend further research to advance understanding of the mechanisms governing phenology and the standardization of phenology observation methods across networks. With the opportunity for “big data” collection for plant phenology, we envision a breakthrough in process‐based phenology modeling.

This work embeds a multilevel Monte Carlo sampling strategy into the Monte Carlo step of the ensemble Kalman filter (EnKF) in the setting of finite dimensional signal evolution and noisy discrete-time observations. The signal dynamics is assumed to be governed by a stochastic differential equation (SDE), and a hierarchy of time grids is introduced for multilevel numerical integration of that SDE. The resulting multilevel EnKF is proved to asymptotically outperform EnKF in terms of computational cost versus approximation accuracy. The theoretical results are illustrated numerically.

We use the Multiple Element Limitation (MEL) model to examine responses of 12 ecosystems to elevated carbon dioxide (CO₂), warming, and 20% decreases or increases in precipitation. Ecosystems respond synergistically to elevated CO₂, warming, and decreased precipitation combined because higher water-use efficiency with elevated CO₂ and higher fertility with warming compensate for responses to drought. Response to elevated CO₂, warming, and increased precipitation combined is additive. We analyze changes in ecosystem carbon (C) based on four nitrogen (N) and four phosphorus (P) attribution factors: (1) changes in total ecosystem N and P, (2) changes in N and Pdistribution between vegetation and soil, (3) changes in vegetation C:N and C: P ratios, and (4) changes in soil C:N and C:P ratios. In the combined CO₂ and climate change simulations, all ecosystems gain C. The contributions of these four attribution factors to changes in ecosystem C storage varies among ecosystems because of differences in the initial distributions of N and P between vegetation and soil and the openness of the ecosystem N and P cycles. The net transfer of N and P from soil to vegetation dominates the C response of forests. For tundra and grasslands, the C gain is also associated with increased soil C: N and C:P. In ecosystems with symbiotic N fixation, C gains resulted from N accumulation. Because of differences in N versus P cycle openness and the distribution of organic matter between vegetation and soil, changes in the N and P attribution factors do not always parallel one another. Differences among ecosystems in C-nutrient interactions and the amount of woody biomass interact to shape ecosystem C sequestration under simulated global change. We suggest that future studies quantify the openness of the N and P cycles and changes in the distribution of C, N, and P among ecosystem components, which currently limit understanding of nutrient effects on C sequestration and responses to elevated CO₂ and climate change.

The 24 projects of the National Science Foundation's Long Term Ecological Research Network, whose sites range from the poles to the Tropics, from rain forests to tundras and deserts, and from offshore marine to estuarine and freshwater habitats, address fundamental and applied ecological issues that can be understood only through a long-term approach. Each project addresses different ecological questions; even the scale of research differs across sites. Projects in the network are linked by the requirement for some research at each site on five core areas, including primary production, decomposition, and trophic dynamics, and by cross-site comparisons, which are aided by the universally available databases. Many species and environmental variables are studied, and a wide range of synthetic results have been generated.

Until recently, it was believed that biological assimilation and gaseous nitrogen (N) loss through denitrification were the two major fates of nitrate entering or produced within most coastal ecosystems. Denitrification is often viewed as an important ecosystem service that removes reactive N from the ecosystem. However, there is a competing nitrate reduction process, dissimilatory nitrate reduction to ammonium (DNRA), that conserves N within the ecosystem. The recent application of nitrogen stable isotopes as tracers has generated growing evidence that DNRA is a major nitrogen pathway that cannot be ignored. Measurements comparing the importance of denitrification vs. DNRA in 55 coastal sites found that DNRA accounted for more than 30% of the nitrate reduction at 26 sites. DNRA was the dominant pathway at more than one-third of the sites. Understanding what controls the relative importance of denitrification and DNRA, and how the balance changes with increased nitrogen loading, is of critical importance for predicting eutrophication trajectories. Recent improvements in methods for assessing rates of DNRA have helped refine our understanding of the rates and controls of this process, but accurate measurements in vegetated sediment still remain a challenge.

Abstract We tracked temporal changes in protist diversity at the Long Term Ecological Research (LTER) station MareChiara in the Gulf of Naples (Mediterranean Sea) on eight dates in 2011 using a metabarcoding approach. Illumina analysis of the V4 and V9 fragments of the 18S rDNA produced 869 522 and 1 410 071 sequences resulting in 6517 and 6519 OTUs, respectively. Marked compositional variations were recorded across the year, with less than 2% of OTUs shared among all samples and similar patterns for the two marker tags. Alveolata, Stramenopiles and Rhizaria were the most represented groups. A comparison with light microscopy data indicated an over-representation of Dinophyta in the sequence dataset, whereas Bacillariophyta showed comparable taxonomic patterns between sequence and light microscopy data. Shannon diversity values were stable from February to September, increasing thereafter with a peak in December. Community variance was mainly explained by seasonality (as temperature), trophic status (as chlorophyll a), and influence of coastal waters (as salinity). Overall, the background knowledge of the system provided a sound context for the result interpretation, showing that LTER sites provide an ideal setting for high-throughput sequencing (HTS) metabarcoding characterisation of protist assemblages and their relationships with environmental variations. Temporal diversity and community structure of the entire protist assemblage from the Gulf of Naples assessed using high throughput sequencing and light microscopy.

Airborne microbes (bacteria, archaea, protists, and fungi) were surveyed over a 7-y period via high-throughput massive sequencing of 16S and 18S rRNA genes in rain and snow samples collected fortnightly at a high-elevation mountain Long-Term Ecological Research (LTER) Network site (LTER-Aigüestortes, Central Pyrenees, Spain). This survey constitutes the most comprehensive mountain-top aerobiology study reported to date. The air mass origins were tracked through modeled back-trajectories and analysis of rain water chemical composition. Consistent microbial seasonal patterns were observed with highly divergent summer and winter communities recurrent in time. Indicative microbial taxa were unveiled as a forensic signature, and ubiquitous taxa were observed as common atmosphere inhabitants, highlighting aerosols as a potentially successful mechanism for global microbial dispersal. Source-tracking analyses identified freshwater, cropland, and urban biomes as the most important sources for airborne bacteria in summer, while marine and forest biomes prevailed in winter, in agreement with air mass retrotrajectories and the prevailing general and regional atmospheric circulation.

The processes leading to the emergence of new species are poorly understood in marine plankton, where weak physical barriers and homogeneous environmental conditions limit spatial and ecological segregation. Here, we combine molecular and ecological information from a long‐term time series and propose Pseudo‐nitzschia allochrona, a new cryptic planktonic diatom, as a possible case of speciation by temporal segregation. The new species differs in several genetic markers (18S, 28S and ITS rDNA fragments and rbcL) from its closest relatives, which are morphologically very similar or identical, and is reproductively isolated from its sibling species P. arenysensis. Data from a long‐term plankton time series show P. allochrona invariably occurring in summer–autumn in the Gulf of Naples, where its closely related species P. arenysensis, P. delicatissima, and P. dolorosa are instead found in winter–spring. Temperature and nutrients are the main factors associated with the occurrence of P. allochrona, which could have evolved in sympatry by switching its phenology and occupying a new ecological niche. This case of possible speciation by time shows the relevance of combining ecological time series with molecular information to shed light on the eco‐evolutionary dynamics of marine microorganisms. We describe a new cryptic species in the marine diatom genus Pseudo‐nitzschia, P. allochrona, based on different phylogenetic markers and with the support of mating incompatibility with the sibling species P. arenysensis. Compared with its closest congeneric species in the Gulf of Naples, P. allochrona occupies a distinct temporal niche, which suggests it may have evolved in sympatry by switching its phenology and occupying a new ecological niche.

Detecting and understanding disturbance is a challenge in ecology that has grown more critical with global environmental change and the emergence of research on social–ecological systems. We identify three areas of research need: developing a flexible framework that incorporates feedback loops between social and ecological systems, anticipating whether a disturbance will change vulnerability to other environmental drivers, and incorporating changes in system sensitivity to disturbance in the face of global changes in environmental drivers. In the present article, we review how discoveries from the US Long Term Ecological Research (LTER) Network have influenced theoretical paradigms in disturbance ecology, and we refine a framework for describing social–ecological disturbance that addresses these three challenges. By operationalizing this framework for seven LTER sites spanning distinct biomes, we show how disturbance can maintain or alter ecosystem state, drive spatial patterns at landscape scales, influence social–ecological interactions, and cause divergent outcomes depending on other environmental changes.