Realized ecological forecast through an interactive Ecological Platform for Assimilating Data (EcoPAD, v1.0) into models

Predicting future changes in ecosystem services is not only highly desirable but is also becoming feasible as several forces (e.g., available big data, developed data assimilation (DA) techniques, and advanced cyber-infrastructure) are converging to transform ecological research into quantitative forecasting. To realize ecological forecasting, we have developed an Ecological Platform for Assimilating Data (EcoPAD, v1.0) into models. EcoPAD (v1.0) is a web-based software system that automates data transfer and processing from sensor networks to ecological forecasting through data management, model simulation, data assimilation, forecasting, and visualization. It facilitates interactive data–model integration from which the model is recursively improved through updated data while data are systematically refined under the guidance of model. EcoPAD (v1.0) relies on data from observations, process-oriented models, DA techniques, and the web-based workflow. We applied EcoPAD (v1.0) to the Spruce and Peatland Responses Under Climatic and Environmental change (SPRUCE) experiment in northern Minnesota. The EcoPAD-SPRUCE realizes fully automated data transfer, feeds meteorological data to drive model simulations, assimilates both manually measured and automated sensor data into the Terrestrial ECOsystem (TECO) model, and recursively forecasts the responses of various biophysical and biogeochemical processes to five temperature and two CO2 treatments in near-real time (weekly). Forecasting with EcoPAD-SPRUCE has revealed that mismatches in forecasting carbon pool dynamics are more related to model (e.g., model structure, parameter, and initial value) than forcing variables, opposite to forecasting flux variables. EcoPAD-SPRUCE quantified acclimations of methane production in response to warming treatments through shifted posterior distributions of the CH4:CO2 ratio and the temperature sensitivity (Q10) of methane production towards lower values. Different case studies indicated that realistic forecasting of carbon dynamics relies on appropriate model structure, correct parameterization, and accurate external forcing. Moreover, EcoPAD-SPRUCE stimulated active feedbacks between experimenters and modelers to identify model components to be improved and additional measurements to be taken. It has become an interactive model–experiment (ModEx) system and opens a novel avenue for interactive dialogue between modelers and experimenters. Altogether, EcoPAD (v1.0) acts to integrate multiple sources of information and knowledge to best inform ecological forecasting.</p

Predicting malaria dynamics under climate change

Malaria dynamics are closely tied to climate, as rainfed water pools provide the habitat for the Anopheles mosquitoes, and temperature influences this vector's ability to spread disease. Climate change drives shifts in microtopographic controls on the persistence of mosquito habitat and the life cycles of Anopheles vector and Plasmodium parasite, which affect the transmission of malaria. The ability to accurately predict malaria dynamics in the future requires the consideration of the impacts of modifications in ecohydrologic system under climate change on these shifts. The primary goal of this research is to investigate the relationships between the dynamics of malaria and changes in the ecohydrologic system due to the acclimation of vegetation under elevated atmospheric CO2 condition and temperature increase. We also aim to understand how the dominant controls of malaria interact under environmental perturbations by quantitatively analyzing changes in malaria incidence rates. Here, a coupled ecohydrology-malaria dynamics model is developed to predict malaria dynamics under projected climate change. The impacts of ecologic acclimation on soil moisture and persistence of ponded water that provide habitat for mosquitoes are captured using a coupled multi-layer canopy and physically-based flow surface-subsurface modeling approach. The transmission of malaria in response to these impacts and temperature increase are assessed by using a stochastic meta-popolation simulation model. We show that impacts of elevated CO2 and temperature have opposing effects on malaria prevalence. While air temperature increase shortens the life cycles of Anopheles and Plasmodium and increases the risk of spreading the disease, lower soil moisture resulting from increasing evapotranspiration reduces the habitat suitability for mosquitoes. The interplay between air temperature increases and soil moisture reduction under climate change leads to a smaller net increase in environmental suitability for malaria transmission than previously thought. In addition, we found larger net increase of malaria incidence under high temperature increase due to its nonlinear effects on the life cycles of vectors and parasites. The models and methods used are generalized and can be applied to other mosquito-borne diseases

Customization, extension and reuse of outdated hydrogeological software

Each scientist is specialized in his or her field of research and in the tools that he or she uses during the research in a specified site. Thus, he or she is the most suitable person for improving the tools by overcoming their limitations to realize faster and higher quality analysis. However, most scientists are not software developers. Hence, it is necessary to provide them with an easy approach that enables non-software developers to improve and customize their tools. This paper presents an approach for easily improving and customizing any hydrogeological software. It is the result of experiences with updating several interdisciplinary case studies. The main insights of this approachhave been demonstrated using four examples: MIX (FORTRAN-based), BrineMIX (C++-based), EasyQuim and EasyBal (both spreadsheet-based). The improved software has been proven to be a better tool for enhanced analysis by substantially reducing the computation time and the tedious processing of the input and output data files

2016 International Land Model Benchmarking (ILAMB) Workshop Report

As earth system models (ESMs) become increasingly complex, there is a growing need for comprehensive and multi-faceted evaluation of model projections. To advance understanding of terrestrial biogeochemical processes and their interactions with hydrology and climate under conditions of increasing atmospheric carbon dioxide, new analysis methods are required that use observations to constrain model predictions, inform model development, and identify needed measurements and field experiments. Better representations of biogeochemistryclimate feedbacks and ecosystem processes in these models are essential for reducing the acknowledged substantial uncertainties in 21st century climate change projections

Assessing the agricultural system and the Carbon cycle under climate change in Europe using a dynamic global vegetation model

Several recent studies predicted changes in the climatic conditions in Europe driven by the increased atmospheric CO2 concentration due anthropogenic activities. The climate change can affect the agriculture through many aspects of crop production over the European continent. Not only plant productivity, but also geographical shifts of cultivation areas, changes in crop phenology, in land use, and in soil carbon stocks have to be taken into account for assessments of the next future. This study provides a potentially powerful baseline to perform integrated assessments on the impacts of the changing climate by assessing crop production with a single integrated framework for large-scale studies. Not only crops and natural vegetation in a single Dynamic Global Vegetation Model, the LPJ-C, but also potential and water-limited crop production are included within the same biosphere scheme. The LPJ-C is extended to simulate not only natural biomes, but also crops. We perform an optimization procedure, which provides a set of crop parameters used in the regional assessment over Europe. Further, we used the resulting modelling framework to study the changes of potential production of maize and wheat together with the shift in their potential growing area. The results show that wheat yield will suffer from a decline, but fertilization due to the CO2 enriched atmosphere will compensate this effect. For maize, cultivation will clearly expand towards north and east. Since maize, as a C4 plant, is mostly unaffected by the CO2 fertilization effect, the shorter growing season will lead to a lower net primary productivity, while the mean over the continent will increase according to the large geographical spread. Furthermore, LPJ-C is able to reproduce the observed relative increase of water use efficiency under water-limited conditions and a CO2 fertilization effect. The improved water use efficiency of wheat leads to a relatively smaller transpiration per unit of biomass, so that precipitation will partially satisfy the transpiration demand. On the other hand, wheat will suffer from an increase of yield variability and a higher frequency of extreme crop failures. Even though maize potential distribution will be enlarged, the yield will be affected by strong losses, unless largely improved irrigation will satisfy the increased water demand. We perform also the coupling of LPJ-C with the land-use model KLUM, as a connection between a profit maximization procedure for land allocation and a process-based description of crop production. The coupled system showed that temperature would play a major role in the soil carbon dynamics over the expected northward shift of crops. However, important changes have to be expected for distribution of "warm" cereals as rice and maiz

Modelação de pradarias marinhas intertidais numa laguna costeira mesotidal

Seagrass meadows are important habitats of marine plants, adapted to the colonization of coastal and estuarine environments, which provide important functions within the ecosystem. The remarkable decline of seagrass meadows at regional/local (Ria de Aveiro) and global scales has presented however negative implications for the sustainability of the ecosystems where they follow this trend. In this context, the main objective of this work was to improve the present knowledge about seagrass dynamics in the Ria de Aveiro, from a multidisciplinary viewpoint (experimental data collection and treatment and numerical modelling), as well as to anticipate potential changes at the system level in these communities. Therefore, it is intended to contribute to the promotion of adequate management and conservation strategies to minimize its decline and enhance its recovery. From the application of a conceptual DSPIR framework (Drivers-Pressures-State-Impacts- Responses), the results pointed that gradual changes in hydrodynamic characteristics are the basis of the local decline of these communities, presently colonized by monospecific intertidal meadows of Zostera noltei. The scarce availability of seagrass models is even more prominent when dealing with intertidal communities, subject to alternating periods of exposure to air and submergence. As so, the inherent peculiarities of intertidal seagrass Z. noltei communities were investigated, showing a greater influence of the sedimentary characteristics on the relative water content of the plant, rather than the air exposure time. Afterwards, it was developed a seagrass biological model together with a desiccation model of the plant, in order to suppress the previously identified gap, both of which were later coupled to the water quality model (Delft3D-WAQ). The numerical model was calibrated using experimental data collected in the study area (Mira Channel), showing a reliable reproduction of the state variables described by means of above and belowground biomass. However, the present set up needs to be improved, namely in what regards sedimentplant interface and internal nutrient dynamics, before it can be applied to other systems with similar challenges. The performance of the numerical model was analysed through different methodologies that presented divergent results, which suggests the application of further approaches for a robust conclusion. A sensitivity analysis was computed, showing that the parameters used to describe the dependence of the ambient temperature (water and air) are the most sensitive, suggesting that these should be particularly addressed in future experimental surveys, by increasing the frequency of the in situ measurements. Two exploratory simulations of extreme event, extreme river flow and heat-wave, respectively showed a decrease in the favourable conditions for seagrass presence, according to the water velocity and salinity; and clear negative impacts on seagrass growth. Following a prospective viewpoint, different evolutionary scenarios to the future, resulting from the foreseen climate change, were set according to the more and less pessimistic projection (RCP 4.5 and RCP 8.5). The numerical model projections pointed out for a noticeable loss of colonised areas by seagrass (between around 30 and 70%, respectively) compared to the present situation. The multiple stressors analysed generally showed a synergistic effect on the loss of the relative area of seagrass, compared to the isolated sum of each of the factors, which highlights the complex and intrinsic relations established between them. The areas colonized by seagrass meadows that showed greater resilience, to the two simulated climate change scenarios, are located in the south and northwest areas of the central lagoon. The spatial distribution of the anomalies between the reference and the climate change scenarios, showed no uniform pattern of variation, occurring areas with descreased favourable conditions for seagrass presence, but also some areas that verified an improvement of these conditions. For a more effective and holistic approach to the natural evolution and modelling of these systems, a wider spatial and temporal coverage of biotic and abiotic descriptors of these communities should be performed. Moreover, the overview of the ongoing and forthcoming anthropogenic actions must also be included, in the context of the socio-economic development of the region, as well as the framework of the future scenarios in the scope of climate change (temporal scale referred to the end of the century). As so, the management actions can be implemented to promote the resilience of these habitats and assure the services provided by the ecosystem.As pradarias marinhas constituem importantes habitats de plantas superiores, adaptadas à colonização de ambientes costeiros e estuarinos, que desempenham importantes funções nestes ecossistemas. O seu declínio acentuado verificado a escalas regionais/locais (Ria de Aveiro) e globais tem, no entanto, apresentado implicações nefastas para a sustentabilidade dos ecossistemas onde estão inseridas. Neste contexto, o objectivo principal deste trabalho consistiu em aprofundar o conhecimento presente da dinâmica das pradarias marinhas na Ria de Aveiro, sob o ponto de vista multidisciplinar (colheita e tratamento de dados experimentais e modelação numérica), bem como prever as potenciais alterações ao nível do sistema nestas comunidades. Desta forma, pretende-se contribuir para a promoção de estratégias de conservação adequadas para minimizar o seu declínio e potenciar a sua recuperação. Partindo da aplicação de um modelo conceptual DPSIR (Drivers-Pressures- State-Impacts-Responses), concluiu-se que as alterações graduais nas características hidrodinâmicas estão na base do declínio local destas comunidades, presentemente colonizadas por pradarias monoespecíficas intertidais de Zostera noltei. A escassez de modelos numéricos de pradaria é acentuada, sendo ainda mais proeminente quando se tratam de comunidades intertidais, sujeitas a períodos alternados de exposição ao ar e submersão. Desta forma, as particularidades inerentes às comunidades de pradarias intertidais foram investigadas, mostrando maior influência das características sedimentares no teor relativo de água da planta, em detrimento do tempo de exposição ao ar. Posteriormente, foi desenvolvido um modelo biológico de pradaria, juntamente com um modelo de dessecação da planta, com vista a suprimir a lacuna previamente identificada, sendo ambos posteriormente acoplados ao modelo de qualidade da água (Delft3D-WAQ). Utilizando os dados experimentais colhidos na área de estudo (Canal de Mira) calibrou-se o modelo numérico, tendo-se verificado uma reprodução fiável das variáveis-estado descritas pela biomassa aérea e subterrânea. Porém, a presente configuração requer melhorias adicionais, nomeadamente no que respeita à interface sedimento-planta e dinâmica interna de nutrientes, previamente a ser passível de ser aplicado a outros sistemas com desafios semelhantes. O desempenho do modelo numérico foi analisado por diferentes metodologias que apresentaram resultados divergentes, o que sugere a necessidade de desenvolvimento e aplicação de metodologias adicionais para uma conclusão robusta. Foi realizada uma análise de sensibilidade, que permitiu aferir que os parâmetros usados para descrever a dependência da temperatura ambiente (água e ar) são os mais sensíveis. Deste modo, salienta-se a sua potencial importância e sugere-se a sua consideração em planeamentos experimentais futuros com maior frequência de amostragem nas medições in situ. Numa abordagem exploratória, simularam-se dois eventos extremos, caudal fluvial extremo e onda de calor, tendo os resultados apresentado, respectivamente, uma diminuição das condições favoráveis para a presença de pradarias em termos de velocidade da corrente e salinidade, e um claro decréscimo no crescimento da planta. Seguindo uma abordagem prospectiva, estabeleceram-se diferentes cenários evolutivos para o futuro, resultantes das expectáveis alterações climáticas, de acordo com a projecção mais e menos pessimista (RCP 4.5 e RCP 8.5). As previsões numéricas obtidas indicam uma perda acentuada de áreas colonizadas por pradarias marinhas (entre aproximadamente 30 e 70%, respectivamente) comparativamente à situação presente. As áreas colonizadas por pradarias que mostraram uma maior resiliência, nos dois cenários de alterações climáticas, situam-se na zona sul e noroeste da laguna central. Na análise espacial da anomalia entre o cenário de referência e de alterações climáticas, não se verificou um padrão uniforme, havendo áreas que apresentam um decréscimo nas condições favoráveis para a presença de pradarias marinhas, simultaneamente à ocorrência de áreas que apontam para um melhoramento das mesmas condições. Para uma abordagem mais efectiva e holística da evolução natural e modelação destes sistemas, deve considerar-se uma maior cobertura espacial e temporal dos descritores bióticos e abióticos destas comunidades. Deve ser ainda incluído o levantamento das actividades antropogénicas decorrentes e previstas no contexto do desenvolvimento socio-económico da região (escala temporal até meio do século), e ainda, deve ser feito o enquadramento nos cenários futuros no contexto das alterações climáticas (escala temporal até final do século), para que medidas de gestão possam ser implementadas no sentido de promover a resiliência destes habitats, de forma a garantir os serviços prestados.Projecto LAGOONS – FP7/2007-2013; Projecto AquiMap (MAR-02.01.01-FEAMP-0022)Programa Doutoral em Biologi

Modelling Human-Fire Interactions: Combining Alternative Perspectives and Approaches

Although it has long been recognised that human activities affect fire regimes, the interactions between humans and fire are complex, imperfectly understood, constantly evolving, and lacking any kind of integrative global framework. Many different approaches are used to study human-fire interactions, but in general they have arisen in different disciplinary contexts to address highly specific questions. Models of human-fire interactions range from conceptual local models to numerical global models. However, given that each type of model is highly selective about which aspects of human-fire interactions to include, the insights gained from these models are often limited and contradictory, which can make them a poor basis for developing fire-related policy and management practices. Here, we first review different approaches to modelling human-fire interactions and then discuss ways in which these different approaches could be synthesised to provide a more holistic approach to understanding human-fire interactions. We argue that the theory underpinning many types of models was developed using only limited amounts of data and that, in an increasingly data-rich world, it is important to re-examine model assumptions in a more systematic way. All of the models are designed to have practical outcomes but are necessarily simplifications of reality and as a result of differences in focus, scale and complexity, frequently yield radically different assessments of what might happen. We argue that it should be possible to combine the strengths and benefits of different types of model through enchaining the different models, for example from global down to local scales or vice versa. There are also opportunities for explicit coupling of different kinds of model, for example including agent-based representation of human actions in a global fire model. Finally, we stress the need for co-production of models to ensure that the resulting products serve the widest possible community