Arctic Station Dirigibile Italia

Nutrient cycling, ecosystem functioning and climate change in Arctic lake ecosystems (Eco-Climate)

Call year: 2022 Status: active IADC_id: 192

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Abstract :rnNutrient cycling in Arctic lakes will be affected by changes in snow cover and abundance of migratory birds, with implications for the stability of lake ecosystems and the services they provide. Through field experiments, satellite data and modelling, the project will quantify the effects of seasonal snow cover and bird abundance on the origin and quantity of nutrient inputs in high Arctic lakes, their burial in sediment and soil, uptake by vegetation or recycling into the atmosphere.rnMotivation of the proposed research:rnArctic lake ecosystems are hotspots of biodiversity and productivity in the tundra, and provide important ecosystem services to Arctic human populations and at the global scale (e.g. they are important carbon sinks) (Vincent et al. 2013). Three major factors control nutrient inputs in lakes: i. snow cover and melting, ii. vegetation cover, iii. guano deposition from birds (Vincent et al. 2013; Woelders et al. 2018). Persistence of snow cover and abundance of migratory birds in lake watersheds are changing as a consequence of climate warming, particularly in the high Arctic (Vincent et al. 2013; Woelders et al. 2018). Nevertheless, a high uncertainty remains regarding impacts of these changes on lake ecosystems’ productivity and ability to store nutrients (Wrona et al. 2016). In particular, mechanisms determining the effect of snow cover and the abundance of bird fauna on C and N inputs in lake ecosystems, their transfer to primary producers, storage in soil and sediment, or their microbial-mediated recycling into the atmosphere are poorly understood. This limits predictions and our ability to preserve Arctic lake ecosystems under climate change scenarios. The proposed pilot interdisciplinary research project will shed light on the effects of seasonal snow cover, abundance of migratory birds and their interaction on the origin and quantity of nutrient inputs in Arctic lakes, their sequestration in sediment and soil, their uptake by vegetation or recycling into the atmosphere.rnObjectives and impacts:rnThe aim of the project is to provide a mechanistic understanding of nutrient sequestration, nutrient cycling, and organic matter decomposition in high Arctic lake ecosystems, and their vulnerability to changes in snow cover and abundance of migratory birds. By the integration of field measurements and experiments, in situ image acquisition, remote sensing and data modelling, the relationship between i. nutrient inputs in sediment and soil (C and N), ii. composition and metabolic activity of microbial communities, iii. rate of organic matter decomposition, and iv. nutrient transfer to primary producers, will be investigated along a gradient of bird-mediated nutrient enrichment in lake watersheds differing in seasonal snow cover. These issues are not only of interest in Arctic lakes, having the potential to improve predictions on how lake ecosystems will respond to changes in nutrient input at other latitudes.rnThe project will develop a novel interdisciplinary approach applicable across the whole Arctic. Results will add important information to international research actions, including the European project iCUPE and the Terrestrial Ecology flagship of the NySMAC. Notably, quantification of organic matter decomposition rates and the characterization of the structure and functioning of microbial communities will inform on the potential of C and N storage in soil and sediment of lake watersheds, and the vulnerability of these processes to environmental changes.rnScientific novelty:rnAnticipating effects of climate change on nutrient cycling in Arctic lakes is necessary to conserve Arctic biodiversity and ecosystem services provided to Arctic human populations and at the global scale. This project will provide mechanism-based evidence on effects of seasonal snow cover and migratory birds on the origin, quantity and fate of nutrients fueling Arctic lake ecosystems. The combination of field measurements, experiments, high resolution in situ and satellite image acquisition, and data modelling for the study of lake ecosystems represents a scientific novelty both in polar regions and at lower latitudes. Such interdisciplinary approach will enable to understand how and how much the changes in the above mentioned factors will affect the origin and amount of nutrients stored in soil, sediment and primary producers, as well as the structure and functioning of microbial communities responsible for nutrient recycling into the atmosphere.rnIsotopic analyses of sediment, soil, primary producers and bird feces will provide an unprecedented characterisation of nutrient inputs in Arctic lake watersheds, clarifying their dependence on abiotic (snow cover) and biotic (migratory birds) factors affected by climate change. Field experiments will provide up to date organic matter decomposition rates, enabling comparisons across the Arctic and with ecosystems at lower latitudes. At microbial level, the experimental approach will furnish novel information on metabolic organic matter remineralization rates and microbial community composition in Arctic lakes. These factors determine the fate, extension and rates of organic matter that can be hydrolyzed before the incorporation in new biomass, mineralization to CO2 or burial in sediment, with profound impacts on carbon and nutrient cycles.rnSnow cover distribution will be derived using new generation satellite data (Sentinel 2). Satellite data will be merged with terrestrial images taken from the automatic instrumentation available and to be deployed in the study area. The terrestrial images will be both new and derived from the iCupe project, enabling a continuous monitoring of the distribution of the snowpack area. This will help to determine the beginning of the melting season, and to monitor the evolution of vegetation cover. Products of image processing will be integrated with field data to quantify the contribution of snow melting (Snow Water Equivalent, SWE) to the hydrological cycle, as a main driver of nutrient cycling in watersheds. Morphometry and hydrology of lake watersheds will be modelled in unprecedented detail, and time evolution of pristine, current and future snow water equivalent will be reconstructed at seasonal scale (through IPCC scenarios and local weather data-Climate Change Tower Integrated Project). High quality webcam images will allow a first of its kind automatic quantification of bird presence in the study area, to be related with vegetation and snow cover in watersheds.rnMethodology:rnThe project will focus on the Brøgger peninsula, Spitzbergen, Svalbard. The area represents a natural laboratory for studying ecological effects of climate change in the Arctic. It hosts numerous fishless shallow lakes that differ for the abundance of nesting barnacle geese and the persistence of snow cover during summer. From the coastline to the interior, marked differences in these parameters can be observed over few kilometers (toposvalbard.npolar.no). In parallel, lake watersheds at a similar distance from the coast differ for the abundance of nesting geese. This generates a natural experiment to test the effect of snow cover and geese on i. the origin and quantity of nutrients in sediment and soil, ii. the nutrient transfer to primary producers, iii. the microbial diversity and metabolic activity, and iv. the efficiency of organic matter decomposition in sediment, soil and water. Four groups of three lakes each will be selected. Each group will include watersheds characterized by high, intermediate or low persistence of seasonal snow cover. The four lake groups will differ for the high, intermediate, low or null presence of nesting geese. Lake watersheds will be selected through remote sensing analysis of snow cover (satellite: Sentinel 2), published (www.npolar.no) and previous knowledge of geese abundance owned by the proponents (RIS-10242, RIS-10999), which will be integrated with webcam images and surveys.rnC and N elemental and stable isotope analyses ( ?13C and  ?15N) in sediment, soil, aquatic and terrestrial vegetation, and goose feces will be performed.  ?13C informs on the terrestrial vs. aquatic origin of C;  ?15N informs on the organic vs. inorganic origin of N (Rundel et al. 2012). Physicochemical data and water will be collected to quantify nutrient and eutrophication levels. Runoff patterns will be reconstructed through 3D Digital Elevation Models of watersheds, providing information on the vulnerability of lakes to terrestrial inputs (Calizza et al., 2016), and indicating sites with no risk of flooding for running decomposition experiments. Satellite and webcam images will be merged and used to characterize snow cover (NDSI), vegetation cover and productivity (NDVI), and their seasonal variation. Spectroradiometer field data will be collected to calibrate remote sensing information. An automatic system to quantify the number of geese in watersheds will be developed. Equipment in use for monitoring the physical parameters of lakes in the area of Ny Alesund (RIS- 10999) will be implemented with high resolution cameras to analyse the images with the ethovision system. In 6 out of the 12 study lakes (see supporting material, Fig.1), microbial abundance and diversity, degradative metabolic rates and functionality will be quantified, and leaf litter decomposition rate will be calculated through field experiments (according to Keuskamp et al. 2013, attached). Decomposition coefficients of local vegetation species will be also quantified.rnWorkplan, including deliverables and milestones:rnThe two Partners will be organized into four operational units (OU). 1.OU-Sapienza; 2.OU-ISP Messina (CNR); 3.OU-ISP Rome (CNR); 4.OU-IRSA (CNR). Briefly, OU-Sapienza will coordinate the project, will produce isotopic data, perform decomposition experiments and quantify the abundance of geese; OU-ISP Messina will produce microbiological and chemicophysical data; OU-ISP Rome will produce data on snow and vegetation cover; OU-IRSA will produce 3D digital elevation models, data and models related to runoff patterns.rnThe project will last for 24 months. Two summer field campaigns are planned. In the first phase in Italy, materials for field sampling and experiments will be prepared, and satellite images will be acquired for a first characterisation of lake watersheds. A first kick start meeting will allow the OUs to select the experimental lakes according to what described in the section Methodology, and to coordinate sampling activities in order to reduce at minimum the impact in watersheds. During the first field campaign, spectralradiometrical ground truth and webcam images of snow cover and vegetation will be acquired. Already tested webcams (RIS-10999) monitoring the abundance of geese will be installed. Samples for isotopic, chemicophysical and microbiological analyses will be collected. Short term decomposition experiments will be performed. Long term decomposition experiments will be started. In Italy, 3D Digital Elevation Models and surface runoff models will be produced. Snow and vegetation cover, NDSI and NDVI will be measured through remote sensing analyses. In the second field campaign, collection of samples for the isotopic and elemental characterisation of lake watersheds will continue. Long term decomposition experiments will be completed. Vertical thermal profiles of lakes will be characterised, and field GPS data will be collected to correct watershed morphometry where topographic inaccuracies could have affected data interpolation. A second project meeting will anticipate the second field campaign. In Italy, during the second year, acquisition and processing of satellite images of snow and vegetation cover, NDSI and NDVI will continue. Laboratory analyses and data elaboration will be concluded. A third meeting in the last phase of the project will allow the 4 OUs to compare and merge data. Such comprehensive dataset will enable to quantify effects of experimental factors (i.e. snow cover and bird fauna) on the measured variables, as well as to produce maps and models describing their spatiotemporal variability, their interdependence and potential future variations according to IPCC scenarios.rnDELIVERABLES: Within the two years of the project 1) isotopic and elemental composition of abiotic and biotic components of high- Arctic lake ecosystems differing in seasonal snow cover and nutrient inputs by migratory birds will be quantified, and maps describing spatiotemporal variations will be produced. 2) Diversity and functioning of microbial communities will be quantified. The rates of microbial respiration, enzymatic activities on proteins, polisaccharides and organic phosphates by microorganisms (from both bacteria and phytoplankton) will be determined. 3) Chlorophyll-a and nutrient concentrations will be measured in different trophic conditions and related to snow cover and bird fauna. 4) Experimental measurements of organic matter decomposition rate will be produced through standard protocols, enabling comparisons with other Arctic regions and ecosystems at lower latitudes. 5) Snow cover, vegetation distribution, NDSI and NDVI maps will be derived from satellite high resolution images (Sentinel 2). 6) High resolution 3D digital elevation models and runoff patterns within each watershed will be described in unprecedented details, including slope flow direction and intensity. 7) Time evolution of pristine, current and future (through IPCC scenarios) SWE will be modelled. This will allow to identify main processes and associated watershed properties explaining observed variability in nutrient inputs, and to support modelling of expected impacts of climate change on nutrient load in lakes.rnProduced data and maps will provide an important contribution for hydrological and ecological studies on Arctic terrestrial and freshwater ecosystems, and a necessary baseline to inform future monitoring and conservation plans. Datasets, maps and technical reports on methodologies developed during the project will be made available to the scientific community, being of interest for studies carried out both across the Arctic and in Antarctica. Seminars for PhD students and for middle and high school students will be organized regarding ecological effects of climate change and Italian scientific activities in Arctic. A dedicated web site will be set to disseminate results. Scientific publications on ISI journals and participation to national and international congresses will complete the dissemination of results.rnActivitiesrnFirst year:rn12 fishless shallow lake watersheds will be sampled by OU-Sapienza to determine the C and N isotopic and elemental composition of sediment, soil, aquatic and terrestrial vegetation (6 replicates per lake each). 4 groups of experimental lakes differing in seasonal snow cover and abundance of nesting geese will be considered (see Methodology and the attached Fig.1). Goose feces and feathers (naturally lost by geese) will be also collected where present. Short term (21 days) decomposition experiments will be performed both in soil and in sediment of 6 lake watersheds (experimental groups 1 and 4) following methods in Keuskamp et al. (2013, attached). Local dominant vegetation will be also included in decomposition experiments. Field cameras for the counting of nesting geese will be deployed. Field surveys for manual counting of geese will be conducted to compare results obtained with cameras.rnChanges occurring in the chemicophysical and microbiological parameters of lakes differing in nutrient and eutrophication levels will be evaluated by the OU-ISP Messina in experimental lakes belonging to groups 1 and 4 (6 sediment samples per lake). 6 water samples per lake will be analysed for N and P cycles, Chlorophyll-a total and pico- nano- micro size fractions, particulated organic Carbon and Nitrogen (POC, PON) and microbiological diversity and metabolism. Specifically, enzymatic activities on proteins, polisaccharides and organic phosphates by microorganisms (from both bacteria and phytoplankton) will be determined. Respiratory rates will be measured by the Electron Transport System activity as well as physiological potentials in relation to bacterial biomass. Samples of guano and lake waters (6 x watershed) will be analysed to determining faecal coliforms and enterococci.rnThe OU-IRSA will produce detailed digital elevation models (DEM) to map drainage channels and to partition the watershed into a set of fundamental runoff sub-regions. A detailed DEM will be overlapped to a thematic slope and drainage direction/intensity map to obtain dynamic surface maps and identify the runoff potentially affecting each lake. Pristine, current and future snow water equivalent (SWE) seasonality will be modelled based on available weather data and ad hoc developed modelling tools.rnProcedures for the systematic acquisition of the optical images (Sentinel 2) will be developed by the OU ISP-Rome. From these images, the areas of the study lakes will be classified. An inventory of the images from available webcams will be carried out to merge terrestrial and satellite data. This will allow to define the extension of snow cover during the entire year, filling the gaps that characterise satellite data. A ground truth campaign will be carried out for the collection of spectroradiometric data to support the calibration of the Sentinel 2 products related to snow and vegetation cover, and for the setup of webcams devoted to monitoring the melting season in lake watersheds.rnSecond year :rnElemental and isotopic characterisation of the 12 lake watersheds will be repeated. This will allow to i. take into account potential between-year differences in snow cover and geese abundance on the quantity and origin of nutrients stored in soil, sediment and primary producers, and ii. increase the power of statistical comparisons and data modelling. Long term decomposition experiment will be concluded. Geese count will be repeated both through field cameras and by manual counting, providing a robust statistical comparison of the two methods. Vertical thermal profiles of lakes will be characterised, and field GPS data will be collected to correct watershed morphometry were topographic inaccuracies will be detected based on previous 3D DEM elaborations.rnIn Italy, elemental and isotopic analyses will be completed by OU-Sapienza. Analyses will be performed through an elementar analyser (Elementar vario-MICRO CUBE) coupled with a mass spectrometer (Isoprime 100) owned by the OU. Data will be statistically analysed and the effect of geese abundance, snow cover and melting on the amount and origin of nutrient inputs in soil and sediment, or uptaken by vegetation will be quantified.rnChemicophysicial and microbiological laboratory analyses will be completed in Italy by OU-ISP Messina. The influence of multiple environmental factors (nutrients, chlorophyll, organic C and N) on prokaryotic abundance and microbial activities will be investigated and related to seasonal snow cover and bird abundance in lake watersheds. Variations will be statistically analysed and elaboration of data will be completed.rnThe OU-ISP Rome will merge and process images acquired by remote sensor and terrestrial webcams aimed at the definition of the spatiotemporal variation of the snow cover. The seasonal extension of the snow cover and the computation of the snow index (NDSI) will be integrated with onsite snow physical data in order to evaluate the Snow Water Equivalent (SWE). The SWE will be therefore used by OU-IRSA to characterize the hydrology in the study lakes. Satellite and terrestrial images of the summer period will be integrated with field data. NDVI (vegetation index) maps will be derived and used to evaluate the evolution of vegetation cover and its availability as biomass. Detailed lake geometry, volume and water circulation will be elaborated by OU-IRSA from the data acquired since the beginning of the project. Spatiotemporal variability of data acquired from previous (RIS-10242, Calizza et al., 2016) and planned surveys will be compared to relate variability in eco-hydro-morphological features (e.g. SWE, snow cover extent, NDVI etc.) with nutrient load and origin in lakes and support a conceptual model on expected impact of climate change on Arctic shallow lake ecosystems.rnDuring the second year, data reports, results presentation, and publications will be submitted, and dissemination activities will take place and will continue after the end of the project.rnExpected Results:rnThe effect of snow cover and bird fauna on the origin (i.e. terrestrial vs. aquatic; organic vs. inorganic) and quantity of nutrients stored or recycled in Arctic shallow lake ecosystems will be quantified. For the first time, organic matter decomposition rates will be measured in soil, sediment and water through standard and innovative procedures and made available for future monitoring. The interdisciplinary approach will produce datasets useful for modelling future nutrient load, decomposition rates and microbial activity in relation to projected changes in snow cover and abundance of migratory birds.rnAn increase in nitrogen load and decomposition rate is expected in conditions of high bird abundance and low seasonal snow cover, with implications for the amount of carbon and other nutrients stored in lake watersheds. Isotopic maps describing spatiotemporal variations in nutrient inputs will be produced, providing a baseline for future ecological and conservation studies in the region. Automated bird counting procedures will be developed, improving the classical manual bird count.rnThe diverse environmental conditions characterizing selected lakes will allow to study changes in microbial metabolic patterns and diversity during the snow melting period, in relation to varying nutrient and organic matter inputs. Microorganisms promptly vary their enzymatic profiles in relation to organic matter availability, and microbial biodiversity may also change in relation to trophic conditions of lakes. Major variations between study lakes are thus expected. Accordingly, the project will improve current knowledge on C, N and P cycles with increasing nutrient inputs and snow melting in Arctic lakes.rnThe distribution of seasonal snow cover will be derived by remote sensing imagery. The thickness and density of the snow will be estimated to compute the liquid water availability during the melting season. Based on the experience acquired in the iCUPE project (OU- ISP Rome), satellite and webcam images will be merged. The integration of field spectroradiometric measures and satellite data will also allow to evaluate the seasonal development of the vegetation cover and to build up-to date datasets. Expected results will represent a novel merging methodology to analyse other Arctic areas. Regarding lake hydromorfology and its effect on nutrient cycling, detailed Digital Elevation Models and drainage maps for each water body will be produced (OU-IRSA), including information on morphometry, direction and intensity of potential run-off and total water volume. Data will be modelled in the context of climate change meteorological forcing scenarios and related to snow water equivalent (SWE) scenarios to assess non-stationarity in SWE seasonality. Predicted variations in the hydrologic regime will be related to data on nutrient load in lake watersheds, thus enabling a conceptual model of expected impacts of climate change on nutrient inputs in Arctic shallow lakes.rnDESCRIPTION OF THE CONSORTIUM PARTNERS AND THEIR ROLES IN THE PROJECT:rnThe Consortium will be constituted by two Partners organized into four fully integrated Operational Units (OU). The Consortium will be coordinated by the Department of Environmental Biology, Sapienza University of Rome (OU-Sapienza), and will involve the newly established Institute of Polar Sciences, locations of Messina (OU-ISP Messina) and Rome (OU-ISP Rome), as well as the Water Research Institute-IRSA (OU-IRSA) of the National Research Council of Italy (CNR). Together, the Partners own the most appropriate theoretical background, methodological and experimental experience, equipments and data modelling skills to achieve the proposed aim and objectives.rnThe OU-Sapienza has a long-term experience in the experimental study of trophic-dynamic processes and nutrient transfer among ecosystem compartments through stable isotope data (Calizza et al. 2012, 2018, L. Rossi et al. 2015, 2019). This includes the characterisation of nutrient inputs and food web structures in Mediterranean and polar aquatic ecosystems (Careddu et al. 2015; L. Rossi et al. 2019), including Arctic lakes (RIS-10242, RIS-10999 , Calizza et al. 2016, Pasquali et al. 2019). The OU owns the necessary experience and equipment for the isotopic analysis of samples. Also, OU-Sapienza owns the necessary experience to perform experiments for the determination of organic matter decomposition rates (Costantini et al. 2010, 2014) and to set up field cameras (RIS-10999) for bird counting and in situ snow monitoring (in collaboration with OU-ISP Rome). Accordingly, OU-Sapienza will (i) provide the elemental and isotopic characterisation of nutrient (C and N) inputs in lake sediment and in watershed soil, (ii) determine the origin of nutrients transferred to aquatic and terrestrial primary producers, (iii) perform decomposition field experiments, (iv) perform the manual and automatic geese count.rnOU-ISP Messina has a long-term experience in studying the microbial compartment in polar (and temperate) areas, including marine and lacustrine systems (Caruso et al. 2005; Zaccone et al. 2015; Azzaro et al. 2019; Papale et al 2019). Research efforts are mainly addressed to analyze microbial abundance, diversity and metabolic functions in relation to a number of environmental parameters (also subject to anthropogenic influence, such as climate warming and pollution), by adopting both classical and modern techniques. According to its expertise, the OU will estimate (i) the organic matter remineralisation rates in water trough microbial enzymatic activities and metabolic CO2 production (ETS); ii) microbial abundances and activities (microscopic observations by DAPI staining and physiological groups by Biolog system); iii) the prokaryotic community composition and metabolic potential by a next generation approach; iv) nutrients analysis; v) chlorophyll fractions determination; v) the relationships with the main environmental factors driving microbial community functions and diversity will be statistically analyzed. The OU owns the necessary experience and equipment for the forecasted microbiological analysis of samples.rnThe OU-ISP Rome has a long-term experience in environmental studies in Polar and Mediterranean areas using remote sensed images with different spatial and spectral resolutions. Research activities are focused on the study of the spectroradiometric properties of different natural surfaces in the 350-2500nm spectral range, in order to recognize their patterns and features from remote sensed data. The OU has expertise in carrying out field surveys in Polar Regions (Antarctica and Arctic) to study the spectroradiometric properties of snow and ice, and the interactions at the snow/air interface. The ISP-Rome participated to the development of a system to monitor continuously the snow surface in remote sites following the snow metamorphic process. The group is also qualified in knowledge organization and GIS designing and implementation.rnThe OU-IRSA has decades of multidisciplinary experience in groundwater and surface water dynamics, with particular regard to lakes water mass balance aimed to assessing the availability of water (D. Rossi et al. 2019) and pollutants in saturated and unsaturated media and a widespread experience in field and in laboratory techniques. The development of conceptual and mathematical models for the assessment of water availability, anthropic impact, climate change impacts, pollutant concentrations and for the balance between availability and water demand represents one of the main objectives of the research Institute. OU-IRSA will provide a new and up-date 3D model of the investigated lakes and a characterization of the associated watersheds. Using mathematical and statistical models the OU will provide scenarios on past and expected hydrologic regime non-stationarity, supporting a conceptual model of expected impacts of climate- driven variations in snow cover and bird abundance on nutrient loads in Artic shallow lakes.

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Nutrient cycling, ecosystem functioning and climate change in Arctic lake ecosystems (Eco-Climate)