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ABSTRACT Long-term terrestrial ecosystem monitoring is a critical component of documenting outcomes of land management actions, assessing progress towards management objectives, and guiding realistic long-term ecological goals, all through repeated observation and measurement. Traditional monitoring methods have evolved for specific applications in forestry, ecology, and fire and fuels management. While successful monitoring programs have clear goals, trained expertise, and rigorous sampling protocols, new advances in technology and data management can help overcome the most common pitfalls in data quality and repeatability. This paper presents Terrestrial Laser Scanning (TLS), a specific form of LiDAR (Light Detection and Ranging), as an emerging sampling method that can complement and enhance existing monitoring methods. TLS captures in high resolution the 3D structure of a terrestrial ecosystem (forest, grassland, etc.), and is increasingly efficient and affordable (<$30,000). Integrating TLS into ecosystem monitoring can standardize data collection, improve efficiency, and reduce bias and error. Streamlined data processing pipelines can rigorously analyze TLS data and incorporate constant improvements to inform management decisions and planning. The approach described in this paper utilizes portable, push-button TLS equipment that, when calibrated with initial transect sampling, captures detailed forestry, fuels, and ecological features in less than 5 minutes per plot. We also introduce an interagency automated processing pipeline and dashboard viewer for instant, user-friendly analysis, and data retrieval of hundreds of metrics. Forest metrics and inventories produced with these methods offer effective decision-support data for managers to quantify landscape-scale conditions and respond with efficient action. This protocol further supports interagency compatibility for efficient natural resource monitoring across jurisdictional boundaries with uniform data, language, methods, and data analysis. With continued improvement of scanner capabilities and affordability, these data will shape the future of terrestrial ecosystem monitoring as an important means to address the increasingly fast pace of ecological change facing natural resource managers. 

Behavioral science interventions have the potential to address longstanding policy problems, but their effects are typically heterogeneous across contexts (e.g., teachers, schools, and geographic regions). This contextual heterogeneity is poorly understood, however, which reduces the field’s impact and its understanding of mechanisms. Here, we present an efficient way to interrogate heterogeneity and address these gaps in knowledge. This method a) presents scenarios that vividly represent different moderating contexts, b) measures a short-term behavioral outcome (e.g., an academic choice) that is known to relate to typical intervention outcomes (e.g., academic achievement), and c) assesses the causal effect of the moderating context on the link between the psychological variable typically targeted by interventions and this short-term outcome. We illustrated the utility of this approach across four experiments (total n = 3,235) that directly tested contextual moderators of the links between growth mindset, which is the belief that ability can be developed, and students’ academic choices. The present results showed that teachers’ growth mindset-supportive messages and the structural opportunities they provide moderated the link between students’ mindsets and their choices (studies 1 to 3). This pattern was replicated in a nationally representative sample of adolescents and did not vary across demographic subgroups (study 2), nor was this pattern the result of several possible confounds (studies 3 to 4). Discussion centers on how this method of interrogating contextual heterogeneity can be applied to other behavioral science interventions and broaden their impact in other policy domains. 

Abstract Substantial gender equity gaps in postsecondary degree completion persist within many science, technology, engineering, and mathematics (STEM) disciplines, and these disparities have not narrowed during the 21st century. Various explanations of this phenomenon have been offered; one possibility that has received limited attention is that the sparse representation of women itself has adverse effects on the academic achievement—and ultimately the persistence and graduation—of women who take STEM courses. This study explored the relationship between two forms of gender representation (i.e., the proportion of female students within a course and the presence of a female instructor) and grades within a sample of 11,958 STEM‐interested undergraduates enrolled in 8686 different STEM courses at 20 colleges and universities. Female student representation within a course predicted greater academic achievement in STEM for all students, and these findings were generally stronger among female students than male students. Female students also consistently benefitted more than male students from having a female STEM instructor. These findings were largely similar across a range of student and course characteristics and were robust to different analytic approaches; a notable exception was that female student representation had particularly favorable outcomes for female students (relative to male students) within mathematics/statistics and computer science courses. 

Beliefs play a central role in human development. For instance, a growth mindset—a belief about the malleability of intelligence—can shape how adolescents interpret and respond to academic difficulties and how they subsequently navigate the educational system. But do usually-adaptive beliefs have the same effects for adolescents regardless of the contexts they are in? Answering this question can reveal new insights into classic developmental questions about continuity and change. Here we present the Mindset×Context framework and we apply this model to the instructive case of growth mindset interventions. We show that teaching students a growth mindset is most effective in educational contexts that provide affordances for a growth mindset; that is, contexts that permit and encourage students to view ability as developable and to act on that belief. This evidence contradicts the “beliefs alone” hypothesis, which holds that teaching adolescents a growth mindset is enough and that students can profit from these beliefs in almost any context, even unsupportive ones. The Mindset×Context framework leads to the realization that in order to produce more widespread and lasting change, we must complement the belief-changing interventions that have been aimed at students with new interventions that guide teachers toward classroom policies and practices that allow students' growth mindset beliefs to take root and yield benefits. 

Students who speak English as a second language (ESL) are underserved and underrepresented in postsecondary science, technology, engineering, and math (STEM) fields. To date, most existing research with ESL students in higher education is qualitative. Drawing from this important body of work, we investigate the impact of a social-belonging intervention on anticipated changes in belonging, STEM GPA, and proportion of STEM credits obtained in students’ first semester and first year of college. Using data from more than 12,000 STEM-interested students at 19 universities, results revealed that the intervention increased ESL students’ anticipated sense of belonging and three of the four academic outcomes. Moreover, anticipated changes in belonging mediated the intervention’s effects on these academic outcomes. Robustness checks revealed that ESL effects persisted even when controlling for other identities correlated with ESL status. Overall, results suggest that anticipated belonging is an understudied barrier to creating a multilingual and diverse STEM workforce. 

Broad-access institutions play a democratizing role in American society, opening doors to many who might not otherwise pursue college. Yet these institutions struggle with persistence and completion. Do feelings of nonbelonging play a role, particularly for students from groups historically disadvantaged in higher education? Is belonging relevant to students’ persistence—even when they form the numerical majority, as at many broad-access institutions? We evaluated a randomized intervention aimed at bolstering first-year students’ sense of belonging at a broad-access university ( N = 1,063). The intervention increased the likelihood that racial-ethnic minority and first-generation students maintained continuous enrollment over the next two academic years relative to multiple control groups. This two-year gain in persistence was mediated by greater feelings of social and academic fit one-year post-intervention. Results suggest that efforts to address belonging concerns at broad-access, majority-minority institutions can improve core academic outcomes for historically disadvantaged students at institutions designed to increase college accessibility.