Constraints and limits to adaptation are critical to understanding the extent to which human and natural systems can successfully adapt to climate change. We conduct a systematic review of 1,682 academic studies on human adaptation responses to identify patterns in constraints and limits to adaptation for different regions, sectors, hazards, adaptation response types, and actors. Using definitions of constraints and limits provided by the Intergovernmental Panel on Climate Change (IPCC), we find that most literature identifies constraints to adaptation but that there is limited literature focused on limits to adaptation. Central and South America and Small Islands generally report greater constraints and both hard and soft limits to adaptation. Technological, infrastructural, and ecosystem-based adaptation suggest more evidence of constraints and hard limits than other types of responses. Individuals and households face economic and socio-cultural constraints which also inhibit behavioral adaptation responses and may lead to limits. Finance, governance, institutional, and policy constraints are most prevalent globally. These findings provide early signposts for boundaries of human adaptation and are of high relevance for guiding proactive adaptation financing and governance from local to global scales.

Future climate warming may increase water temperature, stratification, and the occurrence of cyanobacteria blooms in drinking water reservoirs. Herein, past relationships between air temperature, water temperature, thermal stratification, and cyanobacteria prevalence are quantified in six Connecticut, U.S.A., reservoirs. Lake‐specific empirical models were developed and used to project historical (1971–2000) and future (mid‐century, 2041–2070) water temperature and thermal stratification in the study lakes. Projections are driven with downscaled air temperature projections from three general circulation models (i.e., HadGEM2‐CC365, CCSM4, and GFDL‐ESM 2M) under Representative Concentration Pathway 8.5. Results suggest that reservoirs in Connecticut are warming relatively quickly over time and that surface, average, and bottom water temperatures may continue to increase by 0.44°C, 0.30°C, and 0.16°C per decade, respectively. Future projections of thermal stratification indicate that significant increases may occur in July–September and that stratification is likely to begin 2–4 weeks earlier and last 2–4 weeks longer by mid‐century. High‐risk cyanobacteria blooms, defined as those exceeding 70,000 cells ml⁻¹, historically occurred in three of the study reservoirs and are correlated with the occurrence of high surface water temperatures, cool bottom water temperatures, and high total Relative Thermal Resistance to Mixing (RTRM). Days per year with extreme high water temperatures and total RTRM are projected to increase significantly in the future. This shift may favor increased dominance of certain cyanobacteria species that tend to grow best in these extreme conditions, especially in reservoirs where cyanobacteria blooms are already a concern.

Participatory approaches to science and decision making, including stakeholder engagement, are increasingly common for managing complex socio-ecological challenges in working landscapes. However, critical questions about stakeholder engagement in this space remain. These include normative, political, and ethical questions concerning who participates, who benefits and loses, what good can be accomplished, and for what, whom, and by who. First, opportunities for addressing justice, equity, diversity, and inclusion interests through engagement, while implied in key conceptual frameworks, remain underexplored in scholarly work and collaborative practice alike. A second line of inquiry relates to research–practice gaps. While both the practice of doing engagement work and scholarly research on the efficacy of engagement is on the rise, there is little concerted interplay among ‘on-the-ground’ practitioners and scholarly researchers. This means scientific research often misses or ignores insight grounded in practical and experiential knowledge, while practitioners are disconnected from potentially useful scientific research on stakeholder engagement. A third set of questions concerns gaps in empirical understanding of the efficacy of engagement processes and includes inquiry into how different engagement contexts and process features affect a range of behavioral, cognitive, and decision-making outcomes. Because of these gaps, a cohesive and actionable research agenda for stakeholder engagement research and practice in working landscapes remains elusive. In this review article, we present a co-produced research agenda for stakeholder engagement in working landscapes. The co-production process involved professionally facilitated and iterative dialogue among a diverse and international group of over 160 scholars and practitioners through a yearlong virtual workshop series. The resulting research agenda is organized under six cross-cutting themes: (1) Justice, Equity, Diversity, and Inclusion; (2) Ethics; (3) Research and Practice; (4) Context; (5) Process; and (6) Outcomes and Measurement. This research agenda identifies critical research needs and opportunities relevant for researchers, practitioners, and policymakers alike. We argue that addressing these research opportunities is necessary to advance knowledge and practice of stakeholder engagement and to support more just and effective engagement processes in working landscapes.

The U.S. EPA's Water Quality Exchange (WQX) allows state environmental agencies, the EPA, other federal agencies, universities, private citizens, and other organizations to provide water quality, biological, and physical data (Read & Winslow, 2017). The Water Quality Portal (WQP) is a data warehouse that facilitates access to data stored in large water quality databases, including WQX, in a common format. WQP has become an essential resource with tools to facilitate both data publishing (WQX Web API, 2018; WQX Web User Guide, 2020) and data retrieval (De Cicco et al., 2022; Hodson & Horsburgh, 2023). However, given the variety of data originators and methods, using the data in analysis often requires cleaning to ensure it meets required quality standards and wrangling to get it in a more analytic-ready format. Although there are many examples where this data cleaning or wrangling has been performed (Bousquin, 2021; Evans & Malcom, 2021; Manning & Kominoski, 2020; Ross & Pavelsky, 2019; Shen & Domisch, 2020), standardized tools to perform this task will make it less time-intensive, more standardized, and more reproducible. More standardized data cleansing and wrangling allows easier integration of outputs into other tools in the water quality data pipeline, e.g., for integration into hydrologic analysis (Chegini et al., 2021), dashboards for visualization (Beck & Best, 2021) or decision support tools (Booth & Murphy, 2011).