Accurate estimations of animal populations are necessary for management, conservation, and policy decisions. However, methods for surveying animal communities disproportionately represent specific groups or guilds. For example, transect surveys can provide robust data for large arboreal species but underestimate cryptic or small‐bodied terrestrial species, whereas camera traps have the inverse tendency. The integration of information from multiple methodologies would provide the most complete inference on population size or responses to putative covariates, yet a simple, robust framework that allows integration and comparison of multiple data sources has been lacking. We use 27,813 counts of 35 species or species groups derived from concurrent visual transects, dung transects, and camera trap surveys in tropical forests and compare them within a generalized joint attribute modeling framework (GJAM) that both compares and integrates field‐collected dung, visual, and camera trap data to quantify the species‐ and trait‐specific differences in detection for each method. The effectiveness of survey method was strongly dependent on species, as well as animal traits. These differences in effectiveness contributed to meaningful differences in the reported strength of a known important covariate for animal communities (distance to nearest village). Data fusion through GJAM allows clear and unambiguous comparisons of the counts provided from each different methodology, the incorporation of trait information, and fusion of all three data streams to generate a more complete estimate of the effects of an anthropogenic disturbance covariate. Research and conservation resources are extremely limited, which often means that field campaigns attempt to maximize the amount of information gathered especially in remote, hard‐to‐access areas. Advances in these understudied areas will be accelerated by analytical methods that can fully leverage the total body of diverse biodiversity field data, even when they are collected using different methods. We demonstrate that survey methods vary in their effectiveness for counting species based on biological traits, but more importantly that generative models like GJAM can integrate data from multiple sources in one cohesive statistical framework to make improved inference in understudied environments.

Fieldwork is often an important aspect of research in Ecology, Evolution, and Conservation Biology (EECB), but individuals with marginalized identities are likely to experience compromised wellness. The responsibility for structurally changing fieldwork to improve experiences and outcomes falls on the entire EECB community. We propose a Fieldwork Wellness Framework to replace traditional fieldwork approaches, which are dangerous and ill-suited to today’s increasingly diverse EECB community and its goals. This Framework aims to prevent and manage risk while also promoting holistic wellbeing and belonging for all field research participants. We outline nine facets of the Framework: acknowledge and address identity, create a code of conduct, promote and practice self-care, form local connections, use support structures in decision-making, host and attend trainings, address financial concerns, enact emergency plans, and debrief. By centering wellness in planning and performing fieldwork, EECB can make space for a more diverse, equitable, inclusive, healthy, and productive community.

Fieldwork is often an important aspect of research in ecology, evolution, and conservation biology (EECB), but individuals of marginalized identities are likely to experience compromised wellness. The responsibility for structurally changing fieldwork to improve experiences and outcomes falls on the entire EECB community. We propose a Fieldwork Wellness Framework to replace traditional fieldwork approaches, which are hazardous and ill‐suited to today's increasingly diverse EECB community and its goals. The purpose of this Framework is to prevent and manage risk while also promoting holistic well‐being for all field research participants. We outline nine facets of the Framework: acknowledge and address identity, create a code of conduct, promote and practice self‐care, form local connections, use support structures in decision making, host and attend trainings, address financial concerns, enact emergency plans, and debrief. By centering wellness in the planning and performing of fieldwork, EECB can cultivate a more diverse, equitable, inclusive, healthy, and productive community.

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