Ecosystem modeling, a pillar of the systems ecology paradigm (SEP), addresses questions such as, how much carbon and nitrogen are cycled within ecological sites, landscapes, or indeed the earth system? Or how are human activities modifying these flows? Modeling, when coupled with field and laboratory studies, represents the essence of the SEP in that they embody accumulated knowledge and generate hypotheses to test understanding of ecosystem processes and behavior. Initially, ecosystem models were primarily used to improve our understanding about how biophysical aspects of ecosystems operate. However, current ecosystem models are widely used to make accurate predictions about how large-scale phenomena such as climate change and management practices impact ecosystem dynamics and assess potential effects of these changes on economic activity and policy making. In sum, ecosystem models embedded in the SEP remain our best mechanism to integrate diverse types of knowledge regarding how the earth system functions and to make quantitative predictions that can be confronted with observations of reality. Modeling efforts discussed are the Century ecosystem model, DayCent ecosystem model, Grassland Ecosystem Model ELM, food web models, Savanna model, agent-based and coupled systems modeling, and Bayesian modeling.

The systems ecology paradigm (SEP) is presented as the right science and analytical approach at the right time for resolving many of the Earth’s natural resource, environmental, and societal challenges. SEP embodies two major parts. One, the systems ecology approach, which is the holistic, systems thinking perspective and methodology developed for the rigorous study of ecosystems, including humans. Two, the use of ecosystem science, the vast body of scientific knowledge, much of which has been assembled using the ecosystem and systems ecology approaches. The fundamental philosophy, evolution, and application of the SEP are defined in this chapter. The organizing principles of the SEP include: many problems are complex and complicated and may have multiple causes; precise definitions of problems and their spatial, temporal, and organizational hierarchical scales are critical; collaborative decision making including scientists, technical and administrative staff members, and essential stakeholders is essential; transparent, honest, and effective communication is required; globalization of collaboration within interdisciplinary networks has been a hallmark of the paradigm; and integration of simulation modeling, field and laboratory studies has proven indispensable for many scientific breakthroughs. A call for integration of transdisciplinary science, policy making, and management is presented.

The evolution of ecosystem science and systems ecology as legitimate branches of science has occurred since the late 1960s. They have flourished because of their essential contributions to understanding and management of natural resources and the environment. Scientific knowledge about the structure and functioning of ecosystems, the services ecosystems provide to people, and the roles people play therein, have become commonplace. Scientists know what challenges face Earth’s environments and they know many of the solutions available to resolve them. But scientific knowledge alone is insufficient to implement change. Knowledge transfer to people who manage our lands, waters, and other natural resources is essential and they must become engaged in implementing solutions to major natural resource and environmental challenges. Adoption of new concepts and technologies is critical. Overcoming the barriers to adoption of best management practices is critically needed. Many of the barriers are created by adherence to dogmatic cultural norms and ideologies by landowners, managers, and policy makers. Behavioral, organizational, learning, and marketing professionals study behavioral change. The systems ecology paradigm must incorporate behavioral, organizational, learning, and marketing professionals as partners in implementing concepts of adoption cycles and community-based social marketing to solve wicked problems.

The systems ecology paradigm (SEP) emerged in the late 1960s at a time when societies throughout the world were beginning to recognize that our environment and natural resources were being threatened by their activities. Management practices in rangelands, forests, agricultural lands, wetlands, and waterways were inadequate to meet the challenges of deteriorating environments, many of which were caused by the practices themselves. Scientists recognized an immediate need was developing a knowledge base about how ecosystems function. That effort took nearly two decades (1980s) and concluded with the acceptance that humans were components of ecosystems, not just controllers and manipulators of lands and waters. While ecosystem science was being developed, management options based on ecosystem science were shifting dramatically toward practices supporting sustainability, resilience, ecosystem services, biodiversity, and local to global interconnections of ecosystems. Emerging from the new knowledge about how ecosystems function and the application of the systems ecology approach was the collaboration of scientists, managers, decision-makers, and stakeholders locally and globally. Today’s concepts of ecosystem management and related ideas, such as sustainable agriculture, ecosystem health and restoration, consequences of and adaptation to climate change, and many other important local to global challenges are a direct result of the SEP.

National and international agencies and organizations have published reports outlining critical natural resource, environmental, and societal challenges facing global inhabitants. These reports include the UN Sustainability Goals, Future Earth, Global Land Project, and the Resilience Alliance. Recognizing many of the topics listed in these reports are broad and aspirational, the authors of this chapter have disaggregated many topics into research and management challenges for which the systems ecology paradigm is well suited. Disaggregation is based on challenges at different spatial hierarchical scales: organisms/populations; ecological sites; landscapes; small regions/watersheds; regions/nations; continents; and the globe. Emphasis is placed on research needs at landscape and larger hierarchical levels. Biophysical knowledge acquired during the past 50 years about organism/population and ecological site levels is available now to better manage ecosystems and natural resources. However, research blending the ecosystem knowledge base with behavioral, learning, organizational, and marketing sciences is vitally needed to affect management practice change at scales where people manage land and waters. The goal is to engage managers, policy makers, thought leaders, and concerned citizens to resolve critical problems and adopt best management practices to meet current and future environmental challenges (e.g., provision of ecosystem services and climate change effects on ecosystem).

Emerging from the warehouse of knowledge about terrestrial ecosystem functioning and the application of the systems ecology paradigm, exemplified by the power of simulation modeling, tremendous strides have been made linking the interactions of the land, atmosphere, and water locally to globally. Through integration of ecosystem, atmospheric, soil, and more recently social science interactions, plausible scenarios and even reasonable predictions are now possible about the outcomes of human activities. The applications of that knowledge to the effects of changing climates, human-caused nitrogen enrichment of ecosystems, and altered UV-B radiation represent challenges addressed in this chapter. The primary linkages addressed are through the C, N, S, and H2O cycles, and UV-B radiation. Carbon dioxide exchanges between land and the atmosphere, N additions and losses to and from lands and waters, early studies of SO2 in grassland ecosystem, and the effects of UV-B radiation on ecosystems have been mainstays of research described in this chapter. This research knowledge has been used in international and national climate assessments, for example the IPCC, US National Climate Assessment, and Paris Climate Accord. Likewise, the knowledge has been used to develop concepts and technologies related to sustainable agriculture, C sequestration, and food security.