C. Michael Barton - US grants

With National Science Foundation support Dr. Michael Barton and his team of international collaborators will excavate four prehistoric (Mesolithic and Neolithic) settlements in upland valleys of the Rio Serpis, a major drainage system in Alciante province of Spain. The goal of the work is to understand the transition from a hunting and gathering to an agricultural subsistence mode and the project builds on nearly a decade of prior research, primarily in the form of intensive, landscape oriented archaeological survey. Excavations will take place over the course of two summer field seasons, each focusing on one hunting and gathering (Mesolithic) and one agricultural (Neolithic) site. Each site will be grided and surface artifacts systematically collected. Surface artifact densities and features will be used to create a sampling design and an integrated field strategy using auger coring, backhoe trenching and hand excavation will be employed to acquire information about the density and distribution of cultural materials (including artifacts, floral and faunal remains) features, paleoenvironmental indicators and radiocarbon samples. GIS databases will be developed. In conjunction with regional data this information will be used to reconstruct changes in subsistence, social and spatial organization over time. The team will also examine the effect of these behavioral changes on the landscape.

The transition from hunting and gathering to agriculture is one of the most significant in the human past, and its repercussions are still felt today. With the advent of agricultural economies, humans began to experience widespread sedentism, urban life, and social complexity with multiple ramifications: social ranking and stratification, occupational specialization, centralized political power and organized warfare. Only after humans become dependent on agricultural economies did the human impact on the environment result in massive, long term or permanent changes in vegetation communities, denudation and anthropogenic soil changes. While this transition has long been a focus for archaeological research, the factors which underlie it are still poorly understood. This research should shed additional light.

All of modern society depends ultimately on the products of agriculture and animal herding. When this agropastoral economy first appeared in the Mediterranean basin in the early Holocene, nearly 10,000 years ago, it represented a dramatic reorganization of human ecology. It involved increasingly intensive efforts by farming peoples to control environmental factors favorable to the life cycle of domestic plants and animals, with a consequent cascade of complexly interlinked effects on regional landscapes and human society. Agropastoral land use remains the most significant way in which humans impact natural landscapes, and the recursive social effects of these impacts are important global issues. However, landscape evolution takes place over the course of decades, centuries, and even millennia. Even the loss of a landscape's ability to support a people and their subsistence economy is often the result of longer-term changes that are most apparent at the resolution of the prehistoric record. Only by studying this long-term record can people truly begin to appreciate the real consequences of past and present land-use decisions on earth's landscapes and society and use this understanding to make more informed decisions today. The longest and best-studied record of the ways in which human activities have transformed the world is found in the Mediterranean Basin, encompassing both the earliest known agricultural land use and the earliest civilizations to become dependent on these human-managed socioecosystems. Decades of intensive study by archaeologists, geoscientists, and ecologists have amassed rich and diverse data about human-environmental interaction in this region. This interdisciplinary research project will integrate this information with recent advances in geospatial modeling and agent simulation to create a natural laboratory for investigating the long-term social and ecological consequences of alternate land-use practices. In this project, the modeling laboratory will be used to study (1) the effects the of growth in agropastoral systems on biodiversity; (2) the changing impacts of land-use intensification and diversification on landscapes, their resilience, and vulnerability to degradation; and (3) the long-term sustainability of human maintained socioecosystems in varying environmental and social contexts. The study will focus on two ecologically diverse regions at opposite ends of the Mediterranean Basin, eastern Spain and the southern Levant in Jordan. These two regions encompass much of the social and natural variability of the entire Mediterranean Basin.

This project will generate significant new knowledge about long-term consequences of alternative land-use practices that can help communities make more responsible and effective decisions about land use today. It will also generate integrated archaeological and paleoenvironmental datasets, and dynamic land use-landscape modeling algorithms that will be disseminated via the internet, conferences, and publications for use by researchers addressing other socioecological questions. The research is tightly integrated with an active educational program for undergraduate and graduate students especially geared towards hands on training in the research process, and collaborative transdisciplinary work. This includes a K-12 outreach partnership with the Arizona Geographic Alliance and collaboration with educators to co-develop and disseminate curricula that enables science learning within the context of core requirements of the No Child Left Behind legislation. This project is supported by an award resulting from the FY 2004 special competition in Biocomplexity in the Environment focusing on the Dynamics of Coupled Natural and Human Systems.

With NSF funding and under the supervision of Dr. C. Michael Barton and Dr. Geoffrey A. Clark, Julien Riel-Salvatore will investigate the archeology of the last Neanderthals and the first modern humans in southern Italy. This region, known as the Mezzogiorno, constituted a stable, relatively isolated geographical area during the Late Pleistocene, and has yielded cave sites containing Mousterian, Uluzzian, and Aurignacian archaeological assemblages. The first two industries are thought to have been the handiwork of Neanderthals, while the Aurignacian is more recent and usually attributed to the first modern humans of the Italian peninsula. The archaeological investigation will focus on stone tool technology and economic behavior to test the proposition that the Aurignacian represented a fundamentally different adaptation than either of the earlier industries, and to highlight the unique features of the Uluzzian which was made by some of the last Neanderthals. Stone tools, the most durable and abundant facet of the archaeological record, will be studied to reconstruct land-use patterns and lithic resource utilization, and a study of the patterns of utilization of given rock outcrops will be undertaken to reconstruct the three industries' geographical and social landscapes. A comprehensive radiocarbon dating program will furnish a timeline for the arrival of the Aurignacian in the area and gauge the pace of cultural change during that period, while paleoenvironmental reconstruction based on magnetic susceptibility will test the potential correlation of this arrival with an episode of climatic deterioration.

The proposed research focuses on the behavioral differences that might have given modern humans an adaptive edge over Neanderthals in an ecological refugium located in a geographical cul-de-sac between roughly 40-30,000 years ago. This work will provide fine-grained information on whether the two hominids coexisted in the Mezzogiorno at any point before the disappearance of Neanderthals and, if so, highlight the defining characteristics of the resulting interactions. By framing forager behavior in its larger ecological context, the research will lead to a better understanding of human-environment interactions during that period as well as enable the integration of data from the Mezzogiorno with those from neighboring regions. These insights will ultimately help clarify what it means to be fully human and whether the period under scrutiny attests to the gradual and piecemeal, or relatively rapid and conclusive, apparition of the indicators of behavioral modernity outside of Africa.

More broadly, the project will train the author in the use of innovative analytical methods to directly compare Late Pleistocene hunter-gatherer adaptations with those of their ethnographically-documented counterparts, and potentially identify extinct idiosyncratic behavioral modes not known from extant foragers. By fostering collaboration between Italian and US-based researchers, this project will also encourage scientific dialogue across different research traditions and spur the development of international collaborations. Publication in Italian and Anglo-American peer-reviewed journals will ensure diffusion of the research results to an international scientific audience, while public lectures in the US and Italy will foster an enhanced understanding of the principles of biological and behavioral evolution and of the process of scientific research in the public at large.

This project establishes a consortium in the social and natural sciences for facilitating agent based modeling (ABM) of socioecological dynamics. This organization will serve the scientific community as a framework for collaboration and interdisciplinary research, emphasizing the complex interactions between humans and the environment. A workshop, to be held in early 2007 will bring together leading and innovative practitioners of ABM research in social and natural sciences to organize the consortium, using successful examples of community frameworks for cybertool development in other research domains. Invited participants span a wide range of scientists employing ABM in socio-ecological research and ABM platform developers. The workshop will be followed by a pilot project to develop and evaluate a suite of resources that will help consortium members -- and practitioners in the social and natural sciences more broadly -- make more effective use of advanced ABM simulation protocols in ongoing and planned research. These resources include an archive of agent based models and library of ABM components that can be used by researchers to initiate new modeling efforts and assist peer-review of publications of research involving ABM; a server for collaborative development of better ABM interfaces and cybertools to improve the usability and usefulness of ABM for socioecological research (e.g., concurrent version server, or cvs); and a testbed of standard data for developing model evaluation protocols. The consortium also will promote a community-wide set of best practices for model dissemination and frameworks for model interchange, and initiate a training program in ABM aimed at social and natural scientists.

The initial organizing workshop and pilot project are a collaboration between the School of Human Evolution & Social Change (Arizona State University), the Resilience and Adaptive Management Group (University of Alaska), the Department of Anthropology (University of Arizona), the Center for Social Dynamics and Complexity ((Arizona State University), and the Santa Fe Institute. The workshop will take place at the Center for Social Dynamics and Complexity, and the pilot project resources server will be managed there.

The interactions between humans and their environments are both dynamic and complex. This complexity has intersected over the past century with increasingly rapid population growth, urbanization, and technological development to make human society an important driver of environmental change. This has created a rate and degree of social-environmental change that threatens to exceed our abilities to adapt using traditional strategies. Hence, it is imperative that humans find better ways to understand these global socio-ecological systems (or "socioecosystems"), and anticipate their social and natural consequences in order to lessen the risk of potentially severe socio-natural catastrophes. Recent advances in information technology offer powerful new tools to assist in understanding and managing these coupled social and natural systems. In this context, agent based models have recently emerged as a promising cybertool to study the dynamics of complex human and biological systems, integrating individual perceptions and behaviors in the contexts behavioral ecology, game theory of decision-making, and geospatial representations of the world. The consortium created through this project will establish a community-wide framework to promote more effective use of agent based modeling in socioecological research, and make its results accessible and useful to diverse audiences. Since questions about the dynamics of socio-ecological systems lie at the heart of increasingly critical policy debates at global scale, the long-term agenda of the program initiated here also offers the potential to better inform discussions of environmental policy and its consequences on human society.

This project is a case study designed to identify the dynamics of local subsistence adaptations to the climate-induced environmental transformation of the Pleistocene-Holocene transition. Set in the Mediterranean region of southeast Spain, it includes two systematic archaeological surveys and the geochemical analysis of stone tools collected during the past decade of archaeological research in the study area. The surveys sample the sources of raw material, from which stone tools were made, along three natural corridors connecting major ecological zones from the Mediterranean coast through the mountains to Spain's interior plain and establish the archaeological presence or absence of late Pleistocene human groups where the natural corridors intersect the interior plain. Each survey is the first of its kind in the region. Two previous pilot projects leading to the current dissertation project have helped pioneer the use of Proton Induced X-ray Emission (PIXE) analysis to produce quantifiable geochemical signatures from stone tools and the raw material used to make them. Geochemical signatures are used here to link archaeological sites on a chronological scale, to track the movement and land-use patterns of human groups, and to establish the economic territories of groups with access to specific raw material sources.

The Pleistocene-Holocene transition is the only previous global environmental transformation confronted by modern humans - making it the best available analog for understanding potential human reactions to future climate change. However, late Pleistocene archaeological records in most of Europe are dominated by the Last Glacial Maximum (LGM), which forced major shifts in demography. Human populations abandoned continental Europe west of the Ural Mountains at the LGM and packed into defined refugium areas. As the ice receded, and the Pleistocene began its transition to the Holocene climate regimes in which we now live, refugia populations dispersed outward and recolonized Europe. Mediterranean Spain was an exception, where the interval between late Pleistocene and early Holocene remained a relative continuum. For example, no territory in the study area was excluded from the subsistence base by glaciation. Changes in land-use can be considered responses to the ecological aspects of climate transformation and not simply a response to newly available land. As a result, Mediterranean Spain is a natural venue for studying the ecodynamics of human adaptation to the Pleistocene-Holocene transition.

Resilience in subsistence adaptations is a function of access to sufficient resources. Viewed from this perspective, late Pleistocene and early Holocene hunter-gatherer subsistence economies balanced a set of variables roughly analogous to those of local subsistence economies in climate-sensitive developing nations today. Exponential changes in population density between the Holocene and now redefine what is sufficient, as differences in technology modify the degree and pathways of access, but neither alters the fundamental relationships. An archaeological perspective allows a better understanding of ultimate, rather than proximate, causes of social and ecological system resilience - and that is the broader impact of this research. It recognizes global climate transformation as a challenge that local human groups have previously confronted, and it creates a conceptual framework within which to examine the decision-making processes and that allowed them to adapt in a world of unprecedented change.

This project establishes a scientific research collaboration network to support and expand the development and use of computational modeling in the social and life sciences. The COMSES (COmputational Modeling for SocioEcological Science) network aims to be broadly inclusive of social and natural scientists using (and desiring to use) advanced modeling to study coupled natural and human, or 'socioecological systems' (SES).

The often non-linear, non-intuitive, and even surprising relationships and consequences that emerge from complex interactions between human social practice and the biophysical environment make it imperative that scientific models - including their underlying assumptions, algorithmic processes, logical consistency, and connections with empirical data - be transparent and quantitative. For this reason, computational modeling in general and agent-based modeling (ABM) in particular are important tools for research in socioecological sciences. Yet ABM remains little used or understood in the broader scientific communities involved in the science of coupled natural and human systems. Rather, it is widely perceived as inaccessible to social and natural scientists in spite of the fact that ABM has existed as a potential research tool for nearly two decades.

The primary goal of the COMSES network is to serve as a coordinated community of practice and a conduit to expedite knowledge exchange for computational modeling in SES. The network will build on the NSF-funded OpenABM Consortium http://www.openabm.org. It will seek to grow scientific infrastructure so as to better serve research that uses computational modeling by:

- establishing an interactive, online archive for computational models and providing standard tools and data for model evaluation;
- promoting a common standard for describing models;
- developing educational curricula for embedding modeling and computational thinking in the interdisciplinary study of social and natural sciences.
- establishing a new e-journal dedicated to publishing research in the social and natural sciences that involves computational modeling, and studies of modeling methods and empirical evaluation.

Through the development of exemplar curricula and training opportunities, the project will endeavor to stimulate new interdisciplinary learning opportunities for students at multiple levels who represent the next generation of scientists. With the ever-increasing importance of information technology and related cybertools in today's world, training in advanced modeling techniques and their application in the social sciences will broadly benefit students' careers.

Many of the environmental challenges that we face in the 21st century may also be considered social problems because they affect our quality of life and can only be addressed by human actions. The COMSES network has the potential to transform the social and natural sciences in profound ways by developing computational tools and expertise that will help us to gain a much deeper understanding of the relationships between humans and their environment, and allow us to better predict the likely effects of future policies and decisions.

Within the next three decades, climate variability, climate change and global development trends could have varied and profound effects on human well-being, especially in the developing world. Understanding how human and earth system trajectories will interact is essential to making better decisions that can reduce negative consequences for society and ecosystems. Research related to climate impacts has traditionally been separated into a number of poorly coordinated tasks, with independent models and research groups developing a) socio-economic development pathways, b) emissions and land use scenarios, c) land cover projections, d) climate simulations, and e) impact assessments. This disjointed approach has led to inconsistencies in assumptions across different components of the problem, lack of incorporation of feedbacks, unmanaged uncertainty propagation, and introduction of errors when upscaling or downscaling information across components.

To address these issues, better approaches to impact assessment are required that provide richer, higher resolution, and more internally consistent information about future societal and earth system conditions, and that link models of human and earth systems more effectively. The central objective of this proposal is to improve understanding of the joint consequences of socio-economic development and regional climate change by developing and applying tools to better integrate human and earth system models. This objective will be pursued by focusing on impacts in three key systems - urban areas, agriculture, and forests - in three regional case studies in rapidly developing countries - China, India, and Brazil. The project will develop an integrated suite of community tools for linking the most relevant type of global human system model, integrated assessment models (IAMs), with the Community Earth System Model (CESM), developed and validated through broad-based scientific collaboration and community support over the past 15 years. It will employ these tools to link the CESM with one IAM, the integrated Population-Economy-Technology-Science (iPETS) model, and carry out end-to-end impact assessments for our case study regions, from socio-economic scenario development through earth system analysis to impact and adaptation assessment. These assessments will serve as a proof-of-concept for this new modeling framework as well as produce valuable assessment information. Importantly, the research framework will be applicable in other human systems, in other regions, and with other IAMs than those employed here, to contribute to an even broader understanding of the human consequences of climate change.

The Mediterranean region has one of the longest histories of intensive human use of any part of the world. In some areas, this has led to severe environmental degradation; in other areas, productive landscapes of farms, pastures, towns, and natural areas have been maintained for thousands of years. This project will collect archeological data on ancient human land use, vegetation, and land form at four Neolithic sites in Spain and Italy. These data will guide the development of models of social and natural processes that will attempt to predict the long-term outcomes of alternative patterns of land use. The predictions will be checked against new knowledge of what has actually happened over centuries of use. Based on these checks, the models will be refined to simulate the feedbacks through which human decisions are affected by land cover and terrain, vegetation is affected by land use and landscape change, and the land surface and soils are affected by land cover and use.

By increasing our ability to learn from the past, this project will help the U.S. plan for more sustainable agriculture and development of towns and cities. To help disseminate results, the modeling software created will be available on line. The extensive educational component of the project comprises extensive training of undergraduate and graduate students including members of groups under-represented in science, a summer program to train K-12 teachers to use models of landscape change, and the incorporation of findings into courses at four universities.

Some of the most pressing questions for social scientists -- ranging from efforts to better understand the interactions between humans and the environment to predicting how an aging population will impact the US and global economy -- require making sense of large amounts of data. As a result, social scientists are increasingly using new computational modeling methods to explore the dynamics and consequences of human interactions. These new methods, including agent-based models, provide ways to explore research questions that cannot be investigated using traditional statistical approaches. But appropriate methods to mine, analyze, and synthesis large-scale complex model output data in order to answer social science research questions are still lacking. Traditional analysis methods are designed for data that are linear, continuous, and normally distributed, while data from models of complex socio-ecological systems are non-linear, discontinuous, and power-law distributed. In this project, the researchers seek to address these challenges by developing, applying, and disseminating an integrated environment for analysis and visualization of data generated by complex systems models. An important broader impact is that the research will lead to tools that will allow stakeholders, policy makers, and the general public to explore, interact with, and provide feedback on otherwise difficult-to-understand models.

The project builds on ongoing research by the project team, and uses the NSF-supported CoMSES Net Computational Modeling Library as a platform to make this suite of collaborative, open-source tools broadly available. This community environment will allow any users to post model output along with associated metadata, visualize and analyze output data, comment on and share analyses, and conduct comparative and meta-analysis, drawing on data from other projects. This cyber-infrastructure will provide semi-automated means of discovering relationships that can lead to new theories about how social systems work, test the realism of simulations against knowledge from empirical systems, and propose new research directions to explore.

This workshop will bring together experts to address a national program of capacity building for dynamic and transformed social sciences. It responds to a growing need across multiple scientific disciplines, policy making institutions, and private enterprise for a richer understanding of complex human social systems. Such a program will provide a more thorough scientific assessment of risks and uncertainties in social policies, including unexpected and, especially, undesirable policy consequences. It will also help to better anticipate the potential for rapid and disruptive change (i.e., tipping points and phase changes) that are characteristic of complex systems. Building significant capacity in transdisciplinary science, and employing advanced technologies to understand the dynamics of human society, will promote United States leadership in basic and applied research on the social dimensions of the grand challenges we face in the twenty-first century.

Workshop participants will be charged with developing a roadmap for building national capacity in the social sciences that is needed to meet global challenges facing our world and society in the twenty-first century. There are important scientific problems pertaining to the organization and dynamics of human social systems that are of such scale and complexity that they are intractable to individual researchers, and require a community-scale research organization. The challenges of a world in which human actions are significant drivers of earth systems requires a global-scale science of human society to lead interdisciplinary research by collaborative teams that span social, behavioral, and natural sciences. It requires advanced concepts and methods to manage, synthesize, and model data at the size and complexity needed to match human socio-ecological systems, and computational tools to process the vast quantities of information being generated and captured by these systems today. The rapid pace of technological and social change that is transforming both the domesticated earth and its human managers in unprecedented ways demands an equally dramatic transformation of social science.

The development of social and economic control that leads to inequalities in the distribution of wealth within human societies has been a central theme in understanding how people live. Because archaeology provides a long-term view of past societies, and how they become more or less socially complex through time, it is well suited to provide insight into this phenomenon that occurs within human groups. Using innovative research techniques, Laura Swantek along with colleagues at Arizona State University will undertake research on this process, specifically focusing on understanding how some societies become more complex over time, others do not change, and still others cycle between high and low levels of complexity. Changes in complexity, such as those described here, can be seen today in parts of the world where social and economic changes occur within generations. Understanding what people did in their everyday lives that cause changes in social complexity in the past, will provide insight into how this process occurs today across our changing world.

This research examines how people form socio-economic relationships through time and across space and through these connections are able to exert control of labor, maintain long-distance trade contacts, and differentially access material and ideological resources and as a result become wealthy members of society while others cannot. As a result of these kinds of actions, social networks, or the arrangements of people into complex social structures, change over time can be seen in the archaeological record. This research will be conducted on the Mediterranean island of Cyprus during a 700 year period during which small village level societies exhibited unique characteristics of changes in social complexity. Using data from past excavations of settlements and cemeteries and archaeological surveys, this research will combine methods developed in modern economics, and complex systems and network science, to examine how different social arrangements or network configurations are created by people striving for wealth and control within societies. This interdisciplinary research will foster international scientific collaboration, as well as develop and test new methods for understanding how people exert social and economic control, shaping and reshaping the societies in which they live.

This project will examine mechanisms of social stability and the reasons why some social systems resist change. Social stability, or the persistence of social systems, is a fundamental feature without which human society is not possible. Understanding contexts and processes that resist change and that maintain social stability is crucial to predicting and managing the effects of the intensity and pace of change of the modern world. Previous scholarship has shown that social stability is not an inherent property of a social system and cannot be defined simply as the absence of change but must be explained. Social stability is embedded over time through the cumulative social dependencies created between individuals who choose to form a relationship. The peculiar formations of these dependencies result in different levels of social cohesion, akin to "social glue", that act to promote or thwart social stability. Since the embedding of social stability is a cumulative process that plays out through time, archaeology is uniquely positioned with an established corpus of tools and the long-term perspective necessary to problematize social stability, to establish contexts in which societies resist change, good or bad, and ultimately to understand how, why, and when social transformation does or does not take place.
The research will be conducted by Wendy Cegielski, under the direction of Dr. C. Michael Barton, as part of her doctoral dissertation research It will examine change or lack thereof in social complexity by combining quantitative modeling and the comparative archaeological record where the social system is represented by networks of relations between settlements. From prior sociological research, it has been demonstrated that multiple paths to social cohesion exist and the particular evolution of these paths may be responsible for a society's long-term resistance to change. Subsequently, recognizing the mechanisms governing these paths is important to understanding the evolution of social complexity. In order to accomplish this goal, this project uses formal, abstract modeling techniques called Exponential Random Graph Models from Network Science, the study of relational data. These methods move beyond static snapshots of data toward the investigation of the role of cumulative, bottom-up drivers of stability and change, and their relation to empirical record. The research will be conducted in eastern Spain along the Mediterranean and on the material culture of the Valencian Bronze Age, where prior research appears to indicate little, regional social change for 700 years. Previous scholarship has demonstrated the robusticity across complex social systems of the network theory used in this research; thus the methods proposed can be applied cross-culturally and across disciplines. This research also will increase collaboration between US and international institutions and provide new opportunities for technical training in these innovative techniques.

Nearly a century of fire prevention and suppression in the United States has resulted, counterintuitively, in larger, more frequent wildfires with negative impacts on natural, cultural, and recreational resources. In response, new research focuses on alternative ways to manage the lasting effects of fire, rather than prevent it. To understand the role of fire in modern ecosystems, the long-term history of human influence on fire regimes and biome productivity must be considered. Archaeological and paleoecological research demonstrates that humans have intentionally set fires for millennia to transform the arrangement and diversity of resources within their landscape, with global consequences for terrestrial and atmospheric systems. Anthropogenic fire, meaning fire intentionally set and controlled by humans, has played a vital role in transforming and maintaining agricultural landscapes. Consequently, the beginning of agriculture often coincides with changes in fire frequency and vegetation communities. This project combines multi-dimensional research on anthropogenic burning with archaeological measures of prehistoric agricultural land-use to investigate the origins and evolution of Neolithic (7,700-4,500 cal. BP) agricultural landscapes in three case study areas in eastern Spain.

This work integrates new field and laboratory methods, quantitative models of wildfire and its ecological effects, and an "off-site" archaeological perspective to study the impacts of anthropogenic fire on the human and environmental aspects of ancient agricultural landscapes. The Mediterranean landscape is uniquely suited to investigate prehistoric anthropogenic fire due to its long-term history of agricultural land-use, infrequent naturally caused fires, and fire-sensitive ecosystems. This research encourages international collaboration between archaeologists and fire scientists with implications for long-term management of similar fire-prone ecosystems around the world, including southern California, coastal South Africa, southern Australia, and the entirety of the Mediterranean Basin. Fieldwork for this project is conducted in collaboration with American and Spanish archaeologists, paleoecologists, and fire scientists. This diverse, international team combines multiple perspectives on the role of anthropogenic fire in forest ecosystem function, maintenance, and sustainability. Laboratory work conducted at Arizona State University also provides scientific training and mentorship to undergraduate students studying archaeology, paleoecology, and fire science.

Norms of transparency and knowledge sharing in science encourage new research to build on prior discoveries, leading to rapid innovation and significant societal returns. This project establishes a new activity to help make scientific computation and data science more transparent and accessible. Computation has evolved from tools for assisting scientific research to digital laboratories where fundamental scientific discoveries take place. This is increasingly so for social and ecological sciences, which are combining big data with computational models to better understand the social and earth systems whose complex dynamics underlie many of the grand challenges faced by humanity today. Organized as a Spoke in the National Science Foundation's Big Data Innovation Hub and Spoke network, this project establishes a next generation, online Computational Model Library (CMLX).

In the CMLX, software code for computational models used in social and ecological sciences is published and freely accessible to the scientific community and general public, and linked with an online database of scientific papers reporting on associated model-based science. In addition to the code library, the CMLX is developing an online repository to archive end-to-end workflows of model-based science, where the entire research process can be followed and reproduced, from data synthesis, to modeling, analysis, and visualization. A regional Working Group - including software developers, data providers, and user communities - will provide advice and expertise, as well as help establish community-wide standards for transparency and accessibility in scientific computation. The CMLX is enabling transparent access to scientific procedures, models, and data that can be used to assess the consequences of alternative scenarios, policies, and assumptions for more sustainable management of complexly coupled human and earth systems.

This project is designed to support and advance next generation, interdisciplinary science of the complexly interacting societal and natural processes that are critical to human life and well-being. Computational models are powerful scientific tools for understanding these coupled social-natural systems and forecasting their future conditions for evidenced-based planning and policy-making. This project is led by the Network for Computational Modeling in Social and Ecological Sciences (CoMSES.Net). CoMSES.Net's science gateway promotes knowledge sharing among scientists and with the general public, and enables open, online access to sophisticated computational models of social and ecological systems. CoMSES.Net's partners in this project (the Community Surface Dynamics Modeling System and Consortium of Universities for the Advancement of Hydrologic Science) also enable knowledge sharing and provide open, online repositories of models in the earth sciences. This project will enhance these science gateways and create online educational materials to make these critical technologies easier to find, understand, and use for scientists and non-scientists alike. By integrating innovative technology with training and incentives to engage in best practice standards, this project will stimulate innovation and diversity in modeling science. It will enable researchers to build on each other's work and combine it in new ways to address societal and environmental challenges. The cybertools and educational programs developed in the project will be openly accessible not just to research institutions but also to smaller colleges, state and local governments, and a broader audience beyond the science community. The project will give decision-makers and the data scientists who support them access to a larger and more varied toolkit with which to explore potential solutions to societal and environmental policy issues. A long-term aim of the project is to support an evolving ecosystem of diverse, reusable, and combinable models that are transparently accessible to anyone in the world. Sustainable planetary care and management is a challenge that confronts all of humanity, and requires knowledge, histories, methods, perspectives, and engagement of researchers, decision-makers, and private citizens across the country and throughout the world.

The project will develop an Integrative Cyberinfrastructure Framework (ICF) to enable innovative next-generation modeling of human and natural systems, and build capacity in modeling science. It will support a set of activities that integrate the human and technological components of cyberinfrastructure. 1) Software tools will be developed that augment model codebases with modern software development scaffolding to facilitate reuse, integration, and validation of model code. 2) The project will provide high-throughput computing (HTC) resources for simultaneously running numerous iterations of models needed to capture stochastic variability, explore a parameter space, and generate alternative scenarios; 3) Online training activities will build expertise and capacity to make effective use of the cybertools and the HTC resources; 4) The ICF will engage a global modeling science community to provide professional incentives that encourage researchers to adopt best practices and catalyze innovative science. Leveraging existing NSF investments, the ICF will be developed and deployed by the Network for Computational Modeling in Social and Ecological Sciences (CoMSES.Net), in partnership with the Community Surface Dynamics Modeling System (CSDMS), Consortium of Universities for the Advancement of Hydrologic Science (CUAHSI), Open Science Grid, Big Data Hub/Spoke network, and Science Gateways Community Institute. Computational models have emerged as powerful scientific tools for understanding coupled social-biogeophysical systems and generating forecasts about future conditions under a range of climate, biogeophysical, and socioeconomic conditions. CoMSES.Net, CSDMS, and CUASI are scientific networks, with online science gateways and code archives that enable open access to computational models for an international community of social, ecological, environmental, and geophysical scientists. However, the full value of accessible, well-documented models only can be realized if their code is also widely reproducible and reusable, with a potential for integration with other models. In order to confront critical challenges for understanding the coupled human and natural systems of today's world, modeling scientists also need HTC environments for upscaling models and exploring high-dimensional parameter spaces inherent in representing these systems. The ICF is designed to meet these challenges. By integrating technology with intellectual capacity-building, the ICF will stimulate innovation and diversity in modeling science by letting creative researchers build on each other's work more readily and combine it in new ways to address societal-environmental challenges we have not yet perceived. The tools and training resources will be openly accessible not just to leading research institutions but also to the many smaller colleges, state and local governments, and a broader audience beyond science. They will provide decision-makers and the data scientists who support them access to a much larger and more varied toolkit with which to explore potential solution spaces to social and environmental policy issues. The proposed ICF is also designed to help transform scientific modeling practice, including incentives that can help early career researchers shift from creating models to solve problems specific to a particular project to models that are also useful for others. The project will help support a future evolving ecosystem of diverse, reusable, and integrable models that are transparently accessible to the broader community.

This project is funded by the Office of Advanced Cyberinfrastructure in the Directorate for Computer and Information Science and Engineering, with the Division of Social and Economic Sciences in the Directorate for Social, Behavioral & Economic Sciences also contributing funds.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

This project explores how a portfolio of combined climate intervention strategies including mitigation, carbon dioxide removal, and solar radiation management could achieve a climate-resilient future. The focus is on scientific research activities concerned with climate outcomes that are responsive to the priorities and needs of diverse stakeholder groups. The convergent team encompasses experts from climate science, engineering, behavioral science and ecology. This interdisciplinary team will work to transform the climate interventions research landscape, moving it to more integrated approaches for research and assessments. This will be achieved through the establishment of a shared conceptual and theoretical framework for scenario generation, model application, impact assessment and stakeholder translation.<br/><br/>The project has three main objectives: 1) Advancing state-of-science climate intervention studies through exploring the assumptions, model deficiencies, interactions, and impact assessment methods of a portfolio of climate intervention scenarios consistent with keeping warming within 1.5 degrees C from CMIP6 baseline pathways, with the climate intervention scenarios based on methods already developed by the project investigators; 2) Developing an approach for co-production of modeling products from Earth system evaluations through extensive stakeholder engagement to further actionable research into combined climate intervention scenarios and their evaluation; and 3) Designing scenario and impact assessment toolkits for the wider community to engage in investigating intervention strategies that are responsive to their unique information needs and priorities through the extension of and adaptation of the co-designed scenarios and assessment frameworks.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.