In efforts to become an independent scholar, I failed to learn enough from other people’s mistakes. I believe this is true for most of us, as biting off more than we can chew is so common. Siloed people and projects can result from drive and pride, and impostorism can lead to overcompensation that is further compounded by our unrealistic optimism. Academic territoriality deemphasizes interdisciplinarity and we can feel forced to work on a narrow set of questions, constraining our creativity. And when we reach out for new methods, we can fall sort for many reasons. We must be candid about our failures. There is much I wish I learned sooner about this, and the present brief message shares some of these thoughts. Foremost, people come first. Honor your collaborators and mentees at least as much as you honor your ideas, efforts, and professional products. Second, embrace mixed methods and step out of your comfort zone, but do not reinvent the wheel. Get a lot of advice during the design stage and be sure to walk before you run. You should dream big, but remember to be humble and realistic. Third, the ‘why’ determines the ‘how.’ Choose methods to best answer your specific questions, and sometimes those methods will not be the ones you default to. Your interpretation of results (and any implications toward causality) will be critically limited by your methods; remain prudent in your conclusions and grateful for the opportunities.

Community-based studies on growth, development, energetics, reproduction, senescence, health and disease, all central to bioanthropological scholarship, have, directly or indirectly engaged with food-related questions around its production, availability and utilization. As scholars expand their interests in documenting the impact of ongoing socio-environmental, economic, technological and cultural transitions on human variation, health and wellbeing, the need to understand how individuals and communities relate to food in specific contexts remains key. Human biologists have developed, adopted and refined a series of standardized methods and techniques to document and assess food-related variables and outcomes that have overall proved effective. However, food has, beyond its universal nutritional and health enhancing properties, a myriad of practical and symbolic connotations that vary as a function of the sociocultural context, and the uses and relevance specific communities give it. In this respect, the toolkit relies on conceptual and procedural assumptions that are not necessarily universal, requiring that the methods, techniques and instruments be adapted to the context in question beyond language and cognitive comprehension; failure to do so may inadvertently lead to incorrect, invalid and meaningless results. Examples collected over a decade-long project with agricultural families in central Veracruz will be shared to: 1)illustrate how ethnographic insights are indispensable to operationalize culturally appropriate food-related questions to yield contextualized valid, reliable and meaningful knowledge that can be easily appropriated by the communities with which it is produced; and 2)argue that an engaged and relational approach to research is a necessary condition for such situated knowledge production to occur.

The founder of the Human Biology Association, Gabriel Lasker, defined adaptation as "the change by which organisms surmount the challenges to life." This definition frames adaptation as a positive feature of the basic biology of all organisms, humans included. It also resonates with the current sense of urgency among climate scientists as humans face the potentially existential challenge of anthropogenic climate change (which is, itself, just one element of a potentially looming polycrisis for humanity). In times of urgency, theory might seem like a luxury we can ill afford. In fact, theory is eminently practical and an absolute necessity when we are faced with uncertainty about the best decisions for the future. In addition to its familiar role of structuring scientific inquiry, theory allows us to understand worlds different from the unique one we currently inhabit. Such alternative worlds include the counterfactual futures that arise from different decision paths or different attempts to surmount the challenges of life. The evolutionary theory that undergirds the science of human biology provides a powerful set of tools for understanding adaptation, species persistence, and alternative futures. Unfortunately, our training in formal evolutionary theory has lagged. Developing the capacity for theory among human biologists, and evolutionary human scientists more broadly, depends on established practitioners prioritizing the acquisition of necessary skills in their students and forming strategic alliances with cognate fields. I provide some examples from own personal journey working with population geneticists, demographers (and other sociologists), statisticians, and epidemiologists.

Secondary datasets offer anthropologists a powerful tool for exploring questions of health, behavior, and social and environmental context at population scale. These datasets, often collected by large teams at national and cross-national levels, can provide access to representative and diverse samples that would be logistically or financially prohibitive through primary data collection. They also allow for analyses that require larger sample sizes or greater power, provide opportunities for student engagement and can guide future research design. However, using secondary data presents distinct challenges. Some challenges, such as missing variables, inconsistent definitions, or differences in survey instruments across time or populations, are common to any secondary data analysis. Others, such as the focus on specific outcomes, lack of behavioral questions, and limited contextual detail about the participants, may be a particular challenge for anthropological studies, necessitating creative strategies to operationalize theoretical constructs and contextualize findings. Drawing on examples from my own work in maternal and child health, this presentation offers some lessons learned (e.g. don’t forget to collect the units, diet patterns differ depending on how mothers are asked about their child’s diet, and measuring size vs. growth may lead to very different interpretations) and some strategies (e.g. make the variable categorical, triangulate quantitative behavioral data to infer beliefs, and combine multiple datasets to provide missing context) for using previously collected data to address key issues in human biology.

One of the perennial strengths of biological anthropology is its emphasis on using interdisciplinary methods, from ethnographic fieldwork to molecular biology and computational statistics, to better understand human evolution. However, as laboratory techniques become more sophisticated and our datasets grow larger, being a biological anthropologist increasingly demands fluency across more disparate methodological domains than a single researcher can ever hope to master. Drawing from my own experiences in anthropological genetics, I explore how disciplinary expectations and our ambition as researchers often collides with practical limits on our time and individual expertise. Rather than framing this as a deficit, I argue that these frictions reveal opportunities for more intentional collaboration and a rethinking of what counts as “independent” scholarship. I discuss the hidden labor of switching between modes of inquiry, the challenges for specialists in branding their research, and the emotional toll of feeling perennially undertrained. By sharing my own growing pains, I hope to contribute to a broader conversation about how we build collaborations that are rigorous, reflexive, and mutually beneficial and to encourage researchers at all levels to recognize when to let go of doing it all ourselves.

Studies of women’s health increasingly draw from two distinct methodological approaches: recruiting participants prospectively in clinical settings, and reanalyzing preexisting datasets collected for other purposes. Each approach offers unique advantages and constraints that shape inference in human biological research. Recruiting within clinical populations allows precise phenotyping, detailed exposure measurement, fresh biosamples, and creating a study design optimally tailored for your research question. However, these studies face rising costs and barriers to recruitment, especially for women with caregiving or financial burdens. In contrast, secondary analyses of preexisting datasets enable larger and more diverse samples at relatively low cost, but are often constrained by missing variables, inconsistent biomarker protocols, or limited contextual data on hormonal, environmental, or behavioral exposures. The methodological tradeoffs between these strategies are not merely logistical but conceptual: they determine which hypotheses can be tested and whose biology is ultimately represented. Drawing on examples from my own research, such as the Mothers’ Cultural Experiences study and the Women’s Health Initiative, this presentation considers how design choices influence hypotheses and interpretation of results in women’s health research. Ongoing methodological dialogue across human biology and medical research is critical to conduct women’s health research in a way that is both rigorous and grounded in evolutionary sciences.

Many complementary methodological approaches contribute to our understanding of human biology. Laboratory work provides precision and control, but here we focus on fieldwork – research conducted in complex, dynamic contexts where human life unfolds. Our experiences conducting studies in environmental extremes – including the Amazon, Himalayas and on a small boat in the Arctic Ocean – have underscored the unparalleled opportunities fieldwork provides to study humans in context-rich real-world settings. However, it also challenges every aspect of a team’s preparation, adaptability and collaboration.

Fieldwork demands flexibility in the face of unpredictable circumstances: data collection at all hours, makeshift field sites and rapidly changing weather and access conditions. Beyond the field, navigating administrative and bureaucratic processes before and after trips can be equally demanding, requiring patience, persistence and coordination across institutions and cultures.

Through these experiences, we have learned that success in the field relies as much on people and relationships as on equipment and protocols. A cohesive, well-prepared team that shares purpose, humour and an understanding of one another’s strengths can adapt effectively when the unexpected occurs. Investing time in collective preparation – anticipating contingencies, practicing procedures and developing mutual trust – builds resilience and flexibility that no checklist can replace.

Reflecting on “what we wish we knew then,” we have come to appreciate that methodological excellence in field settings is inseparable from the social dynamics that sustain it. Fieldwork remains one of the most demanding yet rewarding aspects of human biology, offering enduring lessons about both science and collaboration.

It is the case in human and other primate research that the ability to investigate the multifarious interactions between bodies, neurobiologies, genes, endocrine systems, immune systems, behavior, histories, cultures, ecologies, minds, and experiences is more tangible now than ever. The current methodological, theoretical, and technological landscapes make integrative assessing and engaging all of these variables finally feasible. But the ability to bring together the diverse disciplines and practitioners across these landscapes is less so. A solution is to move towards transdisciplinary teams for work in human biology writ large. With transdisciplinarity there is a goal of developing a relationship that creates an exchange and metalanguage in which the terms and concepts of all the participant disciplines are, or can be, expressed facilitating a systems approach and an intellectual transformation that is thorough, intensive, and generative. Transdisciplinarity can enable different questions, broader visions, and offer novel insights for complex real-world dynamics. In this very brief talk, I look back into my research experience and highlight two cases, one in human-primate pathogen transmission and the other in human mating/social organization, where a more integrative approach would have produced much better results and opine about how to create transdisciplinary teams to tackle such projects in the future.