El Nino Southern Oscillation (ENSO) Enhances CO2 Exchange Rates in Freshwater Marsh Ecosystems in the Florida Everglades

This research examines the relationships between El Nino Southern Oscillation (ENSO), water level, precipitation patterns and carbon dioxide (CO2) exchange rates in the freshwater wetland ecosystems of the Florida Everglades. Data was obtained over a 5-year study period (2009-2013) from two freshwater marsh sites located in Everglades National Park that differ in hydrology. At the short-hydroperiod site (Taylor Slough; TS) and the long-hydroperiod site (Shark River Slough; SRS) fluctuations in precipitation patterns occurred with changes in ENSO phase, suggesting that extreme ENSO phases alter Everglades hydrology which is known to have a substantial influence on ecosystem carbon dynamics. Variations in both ENSO phase and annual net CO2 exchange rates co-occurred with changes in wet and dry season length and intensity. Combined with site-specific seasonality in CO2 exchanges rates, El Nino and La Nina phases magnified season intensity and CO2 exchange rates at both sites. At TS, net CO2 uptake rates were higher in the dry season, whereas SRS had greater rates of carbon sequestration during the wet season. As La Nina phases were concurrent with drought years and extended dry seasons, TS became a greater sink for CO2 on an annual basis (-11 to -110 g CO2 m(-2) yr(-1)) compared to El Nino and neutral years (-5 to -43.5 g CO2 m(-2) yr(-1)). SRS was a small source for CO2 annually (1.81 to 80 g CO2 m(-2) yr(-1)) except in one exceptionally wet year that was associated with an El Nino phase (-16 g CO2 m(-2) yr(-1)). Considering that future climate predictions suggest a higher frequency and intensity in El Nino and La Nina phases, these results indicate that changes in extreme ENSO phases will significantly alter CO2 dynamics in the Florida Everglades

Amplification and dampening of soil respiration by changes in temperature variability

Accelerated release of carbon from soils is one of the most important feedbacks related to anthropogenically induced climate change. Studies addressing the mechanisms for soil carbon release through organic matter decomposition have focused on the effect of changes in the average temperature, with little attention to changes in temperature variability. Anthropogenic activities are likely to modify both the average state and the variability of the climatic system; therefore, the effects of future warming on decomposition should not only focus on trends in the average temperature, but also variability expressed as a change of the probability distribution of temperature. Using analytical and numerical analyses we tested common relationships between temperature and respiration and found that the variability of temperature plays an important role determining respiration rates of soil organic matter. Changes in temperature variability, without changes in the average temperature, can affect the amount of carbon released through respiration over the longterm. Furthermore, simultaneous changes in the average and variance of temperature can either amplify or dampen the release of carbon through soil respiration as climate regimes change. These effects depend on the degree of convexity of the relationship between temperature and respiration and the magnitude of the change in temperature variance. A potential consequence of this effect of variability would be higher respiration in regions where both the mean and variance of temperature are expected to increase, such as in some low latitude regions; and lower amounts of respiration where the average temperature is expected to increase and the variance to decrease, such as in northern high latitudes

Seasonal evolution of Aleutian low pressure systems: Implications for the North Pacific subpolar circulation

The seasonal change in the development of Aleutian low pressure systems from early fall to early winter is analyzed using a combination of meteorological reanalysis fields, satellite sea surface temperature (SST) data, and satellite wind data. The time period of the study is September–December 2002, although results are shown to be representative of the long-term climatology. Characteristics of the storms were documented as they progressed across the North Pacific, including their path, central pressure, deepening rate, and speed of translation. Clear patterns emerged. Storms tended to deepen in two distinct geographical locations—the Gulf of Alaska in early fall and the western North Pacific in late fall. In the Gulf of Alaska, a quasi-permanent “notch” in the SST distribution is argued to be of significance. The signature of the notch is imprinted in the atmosphere, resulting in a region of enhanced cyclonic potential vorticity in the lower troposphere that is conducive for storm development. Later in the season, as winter approaches and the Sea of Okhotsk becomes partially ice covered and cold, the air emanating from the Asian continent leads to enhanced baroclinicity in the region south of Kamchatka. This corresponds to enhanced storm cyclogenesis in that region. Consequently, there is a seasonal westward migration of the dominant lobe of the Aleutian low. The impact of the wind stress curl pattern resulting from these two regions of storm development on the oceanic circulation is investigated using historical hydrography. It is argued that the seasonal bimodal input of cyclonic vorticity from the wind may be partly responsible for the two distinct North Pacific subarctic gyres

Building a Global Ecosystem Research Infrastructure to Address Global Grand Challenges for Macrosystem Ecology

The development of several large-, "continental"-scale ecosystem research infrastructures over recent decades has provided a unique opportunity in the history of ecological science. The Global Ecosystem Research Infrastructure (GERI) is an integrated network of analogous, but independent, site-based ecosystem research infrastructures (ERI) dedicated to better understand the function and change of indicator ecosystems across global biomes. Bringing together these ERIs, harmonizing their respective data and reducing uncertainties enables broader cross-continental ecological research. It will also enhance the research community capabilities to address current and anticipate future global scale ecological challenges. Moreover, increasing the international capabilities of these ERIs goes beyond their original design intent, and is an unexpected added value of these large national investments. Here, we identify specific global grand challenge areas and research trends to advance the ecological frontiers across continents that can be addressed through the federation of these cross-continental-scale ERIs.Peer reviewe

Integrating data and analysis technologies within leading environmental research infrastructures: Challenges and approaches

When researchers analyze data, it typically requires significant effort in data preparation to make the data analysis ready. This often involves cleaning, pre-processing, harmonizing, or integrating data from one or multiple sources and placing them into a computational environment in a form suitable for analysis. Research infrastructures and their data repositories host data and make them available to researchers, but rarely offer a computational environment for data analysis. Published data are often persistently identified, but such identifiers resolve onto landing pages that must be (manually) navigated to identify how data are accessed. This navigation is typically challenging or impossible for machines. This paper surveys existing approaches for improving environmental data access to facilitate more rapid data analyses in computational environments, and thus contribute to a more seamless integration of data and analysis. By analysing current state-of-the-art approaches and solutions being implemented by world‑leading environmental research infrastructures, we highlight the existing practices to interface data repositories with computational environments and the challenges moving forward. We found that while the level of standardization has improved during recent years, it still is challenging for machines to discover and access data based on persistent identifiers. This is problematic in regard to the emerging requirements for FAIR (Findable, Accessible, Interoperable, and Reusable) data, in general, and problematic for seamless integration of data and analysis, in particular. There are a number of promising approaches that would improve the state-of-the-art. A key approach presented here involves software libraries that streamline reading data and metadata into computational environments. We describe this approach in detail for two research infrastructures. We argue that the development and maintenance of specialized libraries for each RI and a range of programming languages used in data analysis does not scale well. Based on this observation, we propose a set of established standards and web practices that, if implemented by environmental research infrastructures, will enable the development of RI and programming language independent software libraries with much reduced effort required for library implementation and maintenance as well as considerably lower learning requirements on users. To catalyse such advancement, we propose a roadmap and key action points for technology harmonization among RIs that we argue will build the foundation for efficient and effective integration of data and analysis.This work was supported by the European Union’s Horizon 2020 research and innovation program under grant agreements No. 824068 (ENVRI-FAIR project) and No. 831558 (FAIR- sFAIR project). NEON is a project sponsored by the National Science Foundation (NSF) and managed under cooperative support agreement (EF-1029808) to Battell