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Kramer, D. B., J. Hartter, A. E. Boag, M. Jain, K. Stevens, K. Ann Nicholas, W. J. McConnell, and J. Liu. 2017. Top 40 questions in coupled human and natural systems (CHANS) research. Ecology and Society 22(2):44.

Top 40 questions in coupled human and natural systems (CHANS) research

1Michigan State University, James Madison College and Department of Fisheries & Wildlife, 2Environmental Studies Program, University of Colorado, Boulder, 3School of Natural Resources and Environment, University of Michigan, 4National Oceanic and Atmospheric Administration, 5Lund University Centre for Sustainability Studies, 6Center for Global Change and Earth Observations, Michigan State University, 7Michigan State University, Center for Systems Integration and Sustainability, Department of Fisheries & Wildlife


Understanding and managing coupled human and natural systems (CHANS) is a central challenge of the 21st century, but more focus is needed to pursue the most important questions within this vast field given limited research capacity and funding. We present 40 important questions for CHANS research, identified through a two-part crowdsourcing exercise within the CHANS community. We solicited members of the International Network of Research on Coupled Human and Natural Systems (CHANS-Net) to submit up to three questions that they considered transformative, receiving 540 questions from 207 respondents. After editing for clarity and consistency, we asked the network’s members to each evaluate a random subset of 20 questions in importance on a scale from 1 (least important) to 7 (extremely important). Questions on land use and agriculture topped the list, with a median importance ranking of 5.7, followed by questions of scale, climate change and energy, sustainability and development, adaptation and resilience, in addition to seven other categories. We identified 40 questions with a median importance of 6.0 or above, which we highlight as the current view of researchers active in the field as research questions to pursue in order to maximize impact on understanding and managing coupled human and natural systems for achieving sustainable development goals and addressing emerging global challenges.
Key words: coupled human and natural systems; horizon scan; human-environment systems; social-ecological systems; sustainability science; top questions


Coupled human and natural systems (CHANS) are integrated systems where humans and nature interact, e.g., social-ecological systems (SES) or human-environment systems (Liu et al. 2007a). CHANS research is broadly integrative and interdisciplinary across the social and natural sciences and seeks to understand the complexity of human-nature interactions at the heart of many contemporary problems and society’s elusive pursuit of sustainability (Turner et al. 2003a). CHANS research is a response to scientific silos, reductionism, and determinism (Michener et al. 2001), a recognition of the reciprocal interactions between human and natural systems that often result in surprise due to thresholds, nonlinearities, lag effects, path dependence, and emergent phenomena across temporal, spatial, and organizational scales (Liu et al. 2007b). This perspective promises insights not easily found using more traditional, less integrative approaches.

A number of analytical features characterize CHANS research. For example, Liu et al. (2007a) note four similarities in a review of six CHANS research projects: (1) attention to feedbacks between CHANS; (2) interdisciplinary research teams; (3) use of methodological tools from diverse disciplines; and (4) longitudinal data collection. Carter et al. (2014) argue for the analytical utility of CHANS research perspectives and in particular awareness of reciprocal relationships and cross-scale interactions in understanding human-wildlife interactions in China and Nepal. Similarly, Seto et al. (2012) introduce urban land teleconnections as an improved analytical approach to understand the processes of urbanization, land change, and their linkages, arguing for more holistic and spatially integrative analyses of what are often treated as distinct knowledge domains. As a final example, Reynolds et al. (2007) advocate for a more synthetic scientific framework to understand and sustainably maintain environmental, economic, and cultural systems of global drylands, emphasizing the coupled nature of such systems, the importance of slow variables and thresholds in driving system dynamics, cross-scale interactions, and the need to maintain local ecological knowledge; each a familiar theme in CHANS research.

Recognizing the complexity of today’s sustainability problems and the potential for CHANS perspectives to offer unique insights, increasing investment by scholars, institutions, and funders demonstrates the growing interest in CHANS research. Since the 1972 United Nations Stockholm Conference on the Human Environment placed sustainable development on the global agenda, CHANS research, as indicated by the number of published peer-reviewed articles, has grown substantially (Fig. 1). Published research related to CHANS accelerated concurrently with two major institutional investments in Sweden and the U.S. In 2006, the Swedish Foundation for Strategic Environmental Research (MISTRA) funded the Stockholm Resilience Centre, a leader in research on social-ecological systems. In 2007, the U.S. National Science Foundation (NSF) created the Dynamics of Coupled Natural and Human Systems (CNH) program to fund new interdisciplinary research as a successor to NSF’s program on Bio-Complexity in the Environment (Baerwald et al. 2016). Many other countries, regions, and international partnerships have made institutional investments in CHANS-related research (Fig. 2).

Although the importance of CHANS perspectives and research is increasingly recognized (Mooney et al. 2013, Liu et al. 2015), there has not yet been an assessment of the most important CHANS research questions as identified by scholars and practitioners. Such efforts have recently been undertaken in diverse fields including agriculture (Pretty et al. 2010), paleoecology (Seddon et al. 2014), and biodiversity conservation (Sutherland et al. 2015) and are potentially useful in prioritizing research and directing policy. Here we present such an assessment for CHANS research. We did this by conducting a two-part crowdsourcing exercise within the CHANS community, soliciting members of the International Network of Research on Coupled Human and Natural Systems (CHANS-Net) to submit and then evaluate questions that would “have the biggest impact on understanding and managing coupled human and natural systems” (Appendix 1). Members of CHANS-Net self-identify as active in and familiar with the CHANS field with many having pursued and procured funding for CHANS research, and thus these results may be used to (1) identify the most pressing problems related to CHANS, (2) prioritize CHANS research, and (3) help direct scarce funding and policy attention.


Collecting candidate questions

To first identify and then rank the top questions for CHANS research, we conducted a two-part voluntary, unpaid online survey of the members of CHANS-Net, a U.S. based organization. Membership in CHANS-Net is also voluntary, having been initiated in 2009 by Principal Investigators (PIs) and co-Principal Investigators (co-PIs) of grants from the NSF CNH program and thereafter growing to include members with little or no connection to the CNH Program from many countries. CHANS-Net has organized and sponsored dozens of symposia, workshops, and conference sessions to advance the CHANS community and facilitate communication and collaborations among community members (Liu et al. 2016).

In the first survey (Appendix 1), begun 1 July 2013 and hereafter referred to as the question collection survey, we asked members to submit up to three important questions related to CHANS research. After two reminders, the question collection survey closed on 1 August 2013. We also asked respondents to report whether or not they have been a PI or co-PI on NSF CNH grants, and if so on how many. We asked respondents their primary occupational sector, whether they consider their work strongly inter- or multidisciplinary, which NSF-identified discipline they consider their primary field (National Science Foundation 2013), age, sex, primary nationality, and country of employment.

We received responses from 207 individuals from a member list of 1173, for a response rate of 17.6%. Four of the coauthors independently determined for each of the 540 questions received (Appendix 2) whether they should be kept, rewritten, or eliminated. Responses were eliminated because they were single words, short phrases, or statements, i.e., rather than questions, or their intent was unclear. Assessments of the submitted questions were discussed among four coauthors until a consensus was reached. Redundant questions were then combined, leaving a final list of 321 distinct questions (Appendix 3) that were lightly edited for spelling, grammar, and clarity.

We undertook a similar process to group questions into 12 categories, working independently and then working toward consensus among all coauthors. The categories were not revealed to respondents of the second survey so as to avoid the possibility of the categories biasing their evaluation.

Evaluating candidate questions

We developed a second online survey for CHANS-Net members (Appendix 4), hereafter referred to as the question evaluation survey, to evaluate the importance of the final list of 321 questions. Similar to the question collection survey, participation was voluntary with no compensation offered. On 30 June 2015, we sent the question evaluation survey to the CHANS-Net email distribution list, which by then had grown to 1373 members. While 481 people began the second survey (35% response rate), 352 people completed it including providing question evaluations (26% response rate). Of the 352 completing the question evaluation survey, 99 had also completed the question collection survey.

The question evaluation survey was developed in Qualtrics, administered through the University of Colorado, Boulder (Qualtrics Labs, Inc., version 12018, Provo, Utah, USA). Because we deemed it too onerous a task for a single participant to evaluate the full question pool (n = 321), each participant was presented with 20 randomly selected questions. The Qualtrics randomization algorithm evenly presents the questions for assessment across all surveys started. Therefore, the number of times a question was scored by those who completed a survey (352) followed a normal distribution, ranging from a minimum of 14 to a maximum of 26, with a median of 22 (Appendix 2). Respondents were asked to assess the importance of the questions they saw on a Likert scale from 1 (Not at all Important), to 7 (Extremely Important) and also had the option of not scoring questions, e.g., if they did not find the question clear. We sent four reminders and closed the question evaluation survey on 18 August 2015.

Prior to our analysis, we decided, admittedly arbitrarily, to present the 40 most highly ranked questions. We ordered all questions across categories by mean Likert score and identified the final set of 40 questions by first selecting a subset of questions with mean scores greater than 6.0 (44 questions) and then choosing the top 40 questions of this subset according to minimum score variance, i.e., prioritizing those questions with highest agreement around a high score. Although we recognize the problems related to using the mean as a measure of central tendency for Likert data, we, nevertheless, have done so to distill focus on a tractable number of questions from a large and diverse pool, e.g., to narrow from the 191 questions with a median of 6.0 including all of the top 40 questions we identified. For readers wanting to categorize or order questions in different ways, Appendix 2 lists all questions as well as their categories, number of evaluations, mean, median, variance, and the number of responses for each Likert category. Below, we present the 12 categories of questions in decreasing order of mean question score by category. The listing of questions within categories follows no particular order.


Survey results

The mean Likert score across all questions was 5.45 based on a seven-point scale with 170 questions scored at or above the mean and 151 below. The minimum mean question score was 3.75, and the maximum was 6.36. Forty-four questions (14%) were rated 6.0 or above and 275 questions (86%) 5.0 or above (Fig. 3).

The majority (61%) of respondents to the question collection survey, i.e., question originators, shown in blue in Fig. 4, had never been a PI or co-PI on a NSF CNH grant while 39% of respondents were a PI or co-PI on at least one. Thirty-eight percent of respondents were female. The mean year of birth of respondents was 1969. A majority of respondents were North Americans (76%) with only 24% nationals of countries in Africa, Asia-Pacific, the Middle East, and South America. An overwhelming percentage of respondents were academics (87%), who noted their NSF-supported discipline in the broad categories of the social sciences (46%), life sciences (37%), geosciences (15%), and either engineering or computer information and systems engineering (3%). Nearly all respondents (94%) considered their work strongly inter- or multidisciplinary, a distinguishing feature of CHANS research. These percentages were very similar to those from the question evaluation survey (Fig. 4).

Word cloud analysis

We present an overview of the 321 questions evaluated, based on the aggregate score given to each word summed across all questions (Fig. 5). In addition to the words indicating CHANS (“human,” “natural,” “environmental,” “systems,” “coupled”), we see an emphasis on “change” and key topics like “climate” and “models.”

To ascertain if there were any differences in score given to questions within each category, we first calculated the mean score given to each of the 321 questions. We then ranked each category by the median score of these mean values for each question. Among our 12 categories, questions concerning “Land Use & Agriculture” had the highest median score and questions concerning “Methods” the lowest (Fig. 6).

Top 40 questions by category

Below, we present the 40 questions ranked most important based on results of the question evaluation survey in order of category importance (Fig. 6), beginning with a short overview of each category.

Land use and agriculture

Respondents found the most important questions to be those examining the trade-offs inherent in the use of land to produce food and the associated demands on water, energy, and the environment (Foley et al. 2005). Land-use change is a key process underlying the food, water, and energy nexus, a growing research area (FAO 2014, Future Earth 2015, NSF 2015) with each component noted in the five questions below.


Human and natural systems and their interactions are complex and heterogeneous. The degree to which this heterogeneity is expressed depends on scale (Pickett and Cadenasso 1995). Understanding processes, causes, effects, and various mitigating factors of human and natural systems across spatial, temporal, and organizational scales is a distinguishing feature of CHANS research. Although the need is apparent, research spanning various scales is itself complex and challenging. Respondents scored two questions highly in this category, one methodological and the other conceptual.

Climate change

Climate change introduces great uncertainty and complexity into our modest understanding of CHANS. The effects of climate change are profound for components of both natural and human systems: resource-based livelihoods, ecosystem services, biodiversity, water, energy, and land use (IPCC 2014a). Although exposure to the effects of climate change is universal, the response of human and natural systems is variable because of differences in climate sensitivity, vulnerability, and adaptive capacity (Smit and Wandel 2006, Dawson et al. 2011, IPCC 2014b). The first question in this category provides an example of the CHANS research community’s interest in complex, iterative feedbacks. While also suggestive of the potential for climate change to disrupt CHANS, the second question is more specifically focused on natural resource-based livelihoods.

Sustainability and development

The global agenda for sustainable development is summarized by 17 sustainable development goals (SDGs) and 169 associated targets, released September 2015 (UNDP 2015). Understanding pathways and processes of development is critical to attaining environmental, social, and economic sustainability and addressing these SDGs. The three questions below depict the dual-directionality of cause and effect between development and environment in CHANS.

Adaptation and resilience

As noted above, global change drivers such as climate change have the potential to disrupt CHANS. Resilience, or “the capacity of a social-ecological system to absorb or withstand perturbations and other stressors such that the system remains within the same regime, essentially maintaining its structure and functions” (Resilience Alliance 2016), depends greatly on the abilities of natural and human systems to adapt. A better understanding of CHANS creates opportunities and insights to assess vulnerability and improve adaptive capacity (Turner et al. 2003b). The questions below ask how we might improve the resilience of both human and natural systems amid the currents of global change.

Society and culture

Along with natural systems, human systems are an important component of the CHANS framework, but they are challenging to understand, model, predict, and integrate into broader conceptual understandings because of the many competing and often conflicting theories on human behavior and societal interactions (Janssen et al. 2015). The questions below position humans as both drivers of environmental change and respondents to these changes.


The questions regarding governance suggest a mismatch between CHANS and those regulatory or management systems affecting them (Biermann et al. 2012), reflecting a concern that spatial and temporal processes of natural systems may not be well-integrated with the spatial, e.g., jurisdictions, and temporal, e.g., election cycles, processes of governance. In addition, many systems of governance, e.g., command-and-control, are ill-suited to managing the uncertainties and complex interactions of CHANS (Holling and Meffe 1996). The five questions below ask not only how governance affects CHANS, but how governance can become better at interacting with often complex, uncertain, and variable CHANS.

Behavior and economics

Understanding human behavior and decision making is critical to understanding the interactions between human and natural systems. CHANS researchers seek representative models of human behavior and decision making, especially models providing insights into decision making under uncertainty (NSF DMUU 2016). Reflecting maturation in related disciplines, CHANS research seems to be moving beyond rational actor models to utilize insights from behavioral economics, psychology, e.g., prospect theory, sociology, e.g., social networks, and other disciplines. Methodologically, more complex models of decision making lend themselves to agent-based models, a common methodological framework in CHANS research (An 2012). The two questions below suggest a need for better models of human decision-making in the face of uncertainty and as a driver of environmental change.

General principles and system dynamics

A common theme in CHANS research is that an understanding of feedbacks, thresholds, surprises, nonlinearities, and emergent phenomena, while complicating prediction, is critical to achieving sustainability. The questions below suggest a broad endeavor to identify and understand general principles of complex system dynamics within and across CHANS.

Education and science communication

Scientists often lament a perceived poor understanding of science, natural systems, natural processes, and anthropogenic influence among the public and policy makers (Weber and Stern 2011). This concern, perhaps owing to the complexities and uncertainties of CHANS, is evident in the two questions below.

Conservation and ecosystem services

Increasingly, conservation science has attempted to account for the role of people in the conservation of biodiversity from community-based conservation (Berkes 2004) to people-friendly conservation (Marvier and Kareiva 2014) to conservation in working landscapes (Phalan et al. 2011). Similarly, perhaps no other paradigm shift in conservation science in the past 30 years eclipses the anthropocentric, ecosystem services framework in importance and influence, reflecting a research agenda that seeks to understand the linkages between ecosystem structure, function, and services with human benefits and values (Potschin and Haines-Young 2011). In addition to offering a bleak assessment of the world’s ecosystems, the Millennium Ecosystem Service Assessment (MEA 2005) added conceptual clarity to the linkages between natural and human systems and argued the importance of holistic ecosystem management for long-term sustainability. Not without its critics (e.g., Norgaard 2010), the concept of ecosystem services, the subject of each of the three questions below, fits well within the CHANS perspective because of its explicit linking of human and natural systems.

Methods in CHANS research

A great challenge in CHANS research is to develop analytical methods that effectively capture the interactions between human and natural systems across temporal, spatial, and organizational scales. Challenges include the integration of disparate kinds of data, e.g., biophysical/social, quantitative/qualitative, and analytical representations of complex ecological, e.g., climate change, and social processes, e.g., social learning. Each of the questions below pertains to the representation of complex social or ecological processes in CHANS models.


The fields of conservation biology (Sutherland et al. 2013, 2014, 2015), agricultural science (Pretty et al. 2010), marine biology (Parsons et al. 2014), plant ecology (Grierson et al. 2011), and others (Seddon et al. 2014) have generated similar “top questions” to focus each community’s research efforts, spark discussion, and build stronger links between research and policy. Reviewing these efforts, we find similarities to the top questions identified here as well as some distinctions.

Similar to results from horizon-scanning efforts in plant ecology and marine biology, we identified effective methods of public engagement or education as a concern in our top questions (Grierson et al. 2011, Parsons et al. 2014). Horizon scans in plant ecology, conservation biology, and agriculture identified a top question focused on the challenge of feeding billions in an environmentally sustainable and socially just way, noted in our top questions as well (Sutherland et al. 2009, Pretty et al. 2010, Grierson et al. 2011). Furthermore, there was much overlap with other disciplines around resilience, such as studying how ecosystem resilience is changing and how we can build or maintain resilient systems (Sutherland et al. 2009, Pretty et al. 2010, Seddon et al. 2014). Finally, interdisciplinarity, a hallmark of CHANS research and identified in the CHANS top questions, was also the focus of top questions from similar reviews in marine conservation and agricultural science, identifying a need for more learning and collaboration across disciplines (Pretty et al. 2010, Parsons et al. 2014).

The set of 40 top CHANS questions presented here are unique relative to similar such question identification exercises in the environment-related sciences in the prevalence of those emphasizing how humans would be affected by and adapt to global environmental change, how human population patterns will change with water availability, and how ecosystem services affect human well-being. This demonstrates a distinguishing aspect of CHANS research, feedbacks in which humans influence natural systems but are also affected by them (Liu et al. 2007a).


Any endeavor seeking to identify or rank the most important research questions in a research field is fraught with methodological and conceptual difficulties. This is true of our efforts as well. Our results are based on questions submitted and evaluated by members of a self-selected set of respondents from among members of CHANS-Net, a self-selected network of CHANS researchers. Although the characteristics of respondents to both surveys were very similar, suggesting some correspondence with the underlying CHANS-Net population, CHANS-Net does not collect this information from its members, and therefore we were unable to assess representativeness. Therefore, respondents, a majority of which were male, North American, employed in academia, and identified with the social sciences, life sciences, and geosciences may not be representative of CHANS-Net members nor the broader CHANS community. Thus, caution is warranted in inferring that our results are representative of the views of the undoubtedly more extensive, more diverse, and more global CHANS community. Furthermore, with regard to the question evaluation survey, it is likely that CHANS-Net respondents, despite a great majority of them characterizing their work as inter- or multidisciplinary, were evaluating questions outside their primary field of expertise potentially affecting their evaluations because of bias or unfamiliarity.

Conceptually, we acknowledge that the questions reviewed here represent the current views of CHANS-Net members. The task of generating truly innovative, transformative, future-orientated questions is difficult. Innovation and imagination are rarely products of consensus. Similarly, emerging issues may be relatively unknown among the community. For example, there seems to be increasing research interest in telecoupling, socioeconomic and environmental interactions between distant CHANS through international trade, migration, knowledge dissemination, technology transfer, and payments for ecosystem services (e.g. Liu et al. 2013, Gasparri et al. 2016, Hulina et al. 2017). Telecoupling, however, was not mentioned in our top 40 questions. Still, despite these difficulties, our efforts to identify the top CHANS-related research questions represent a first assessment of the views of the CHANS community, a worthwhile endeavor we hope continues periodically with increased attention to the limitations of such exercises and exploration of other methods to identify important questions.


We hope the 40 research questions presented in this paper are a useful contribution to researchers, funders, and policy makers in identifying current research ideas and directions, targeting funding investments, and identifying policy needs related to understanding and managing CHANS. As noted above, the CHANS perspective is in part a response to the increased complexity, interconnectedness, and potential for rapid and unexpected change in the world. As such, CHANS research is challenging, requiring scientists to move beyond scientific silos; to collaborate with those adopting different methods, perspectives, and terminology; and to maintain careful and detailed examination of localized phenomena while considering broader temporal, spatial, and organizational scales. These challenges, reflected in the questions presented here and discussed in depth elsewhere (Gershon 2000, Rylance 2015, Van Noorden 2015, Brown et al. 2016), are part of a larger effort to retool and to rethink our approach to meet the goal of sustainability on an increasingly complex and connected planet.


Responses to this article are invited. If accepted for publication, your response will be hyperlinked to the article. To submit a response, follow this link. To read responses already accepted, follow this link.


The authors thank CHANS-Net for providing access to their member list as well as CHANS-Net members for their participation in the crowd-sourcing exercise described above. This collaboration was begun at a CHANS working group in 2012, where KAN and MJ were CHANS Fellows, part of the International Network of Research on Coupled Human and Natural Systems, which is sponsored by the National Science Foundation and coordinated by the Center for Systems Integration and Sustainability at Michigan State University. We thank Theo Aalders for assistance with Figure 4.


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