Though citizen science programs have been broadly successful in diverse scientific fields, their adoption has lagged in some disciplines, including soil science and ecosystem ecology. Collaborations with citizen scientists may be viewed as a conundrum in these disciplines, which often require substantial labor and technical experience; citizen scientists could improve sampling capacity but may reduce sample quality or require training and oversight prior to and while performing specialized tasks. To demonstrate the feasibility of incorporating citizen scientists into soil biogeochemistry research, we conducted a proof-of-concept study in high-elevation meadows of the Sierra Nevada in California. A collaboration between university researchers and citizen scientists allowed us to assess spatial and diel patterns of soil greenhouse gas (GHG) fluxes with an intensity and frequency that would otherwise be beyond the capacity of a typical research laboratory. This collaboration with citizen scientists increased our sampling intensity by over 700% while only doubling the sampling error relative to that of full-time researchers. With training and support from project scientists, citizen scientists collected data that demonstrate spatial independence of carbon dioxide, methane, and nitrous oxide at scales between 1 m and 175 m. Additionally, we found a lack of temporal variation over a 24-h period for all three GHGs. Citizen scientists participating in this one-day event reported levels of satisfaction commensurate with longer-term, immersive campaigns. The place-based event also proved an effective tool for teaching intangible concepts of soil biogeochemistry and promoting local conservation. Despite perceived barriers to entry, this study demonstrates the mutual benefits of citizen science collaborations in soil science and ecosystem ecology, encouraging adoption by disciplines that have been slow to take advantage of such collaborations. Short-term, local citizen science events can provide meaningful experiences for area residents and teach global biogeochemical cycles in a place-based context.

Urbanization creates novel ecosystems comprised of species assemblages and environments with no natural analogue. Moreover, irrigation can alter plant function compared to non-irrigated systems. However, the capacity of irrigation to alter functional trait patterns across multiple species is unknown but may be important for the dynamics of urban ecosystems. We evaluated the hypothesis that urban irrigation influences plasticity in functional traits by measuring carbon-gain and water-use traits of 30 tree species planted in Southern California, USA spanning a coastal-to-desert gradient. Tree species respond to irrigation through increasing the carbon-gain trait relationship of leaf nitrogen per specific leaf area compared to their native habitat. Moreover, most species shift to a water-use strategy of greater water loss through stomata when planted in irrigated desert-like environments compared to coastal environments, implying that irrigated species capitalize on increased water availability to cool their leaves in extreme heat and high evaporative demand conditions. Therefore, irrigated urban environments increase the plasticity of trait responses compared to native ecosystems, allowing for novel response to climatic variation. Our results indicate that trees grown in water-resource-rich urban ecosystems can alter their functional traits plasticity beyond those measured in native ecosystems, which can lead to plant trait dynamics with no natural analogue.

Though citizen science programs have been broadly successful in diverse scientific fields, their adoption has lagged in some disciplines, including soil science and ecosystem ecology. Collaborations with citizen scientists may be viewed as a conundrum in these disciplines, which often require substantial labor and technical experience; citizen scientists could improve sampling capacity but may reduce sample quality or require training and oversight prior to and while performing specialized tasks. To demonstrate the feasibility of incorporating citizen scientists into soil biogeochemistry research, we conducted a proof-of-concept study in high-elevation meadows of the Sierra Nevada in California. A collaboration between university researchers and citizen scientists allowed us to assess spatial and diel patterns of soil greenhouse gas (GHG) fluxes with an intensity and frequency that would otherwise be beyond the capacity of a typical research laboratory. This collaboration with citizen scientists increased our sampling intensity by over 700% while only doubling the sampling error relative to that of full-time researchers. With training and support from project scientists, citizen scientists collected data that demonstrate spatial independence of carbon dioxide, methane, and nitrous oxide at scales between 1 m and 175 m. Additionally, we found a lack of temporal variation over a 24-h period for all three GHGs. Citizen scientists participating in this one-day event reported levels of satisfaction commensurate with longer-term, immersive campaigns. The place-based event also proved an effective tool for teaching intangible concepts of soil biogeochemistry and promoting local conservation. Despite perceived barriers to entry, this study demonstrates the mutual benefits of citizen science collaborations in soil science and ecosystem ecology, encouraging adoption by disciplines that have been slow to take advantage of such collaborations. Short-term, local citizen science events can provide meaningful experiences for area residents and teach global biogeochemical cycles in a place-based context.

Urban heat and air pollution, two environmental threats to urban residents, are studied via a community science project in Los Angeles, CA, USA. The data collected, for the first time, by community members, reveal the significance of both the large spatiotemporal variations of and the covariations between 2 m air temperature (2mT) and ozone (O₃) concentration within the (4 km) neighborhood scale. This neighborhood variation was not exhibited in either daily satellite observations or operational model predictions, which makes the assessment of community health risks a challenge. Overall, the 2mT is much better predicted than O₃ by the weather and research forecast model with atmospheric chemistry (WRF-Chem). For O₃, diurnal variation is better predicted by WRF-Chem than spatial variation (i.e., underestimated by 50%). However, both WRF-chem and the surface observation show the overall consistency in describing statistically significant covariations between O₃ and 2mT. In contrast, satellite-based land surface temperature at 1 km resolution is insufficient to capture air temperature variations at the neighborhood scale. Community engagement is augmented with interactive maps and apps that show the predictions in near real time and reveals the potential of green canopy to reduce air temperature and ozone; but different tree types and sizes may lead to different impacts on air temperature, which is not resolved by the WRF-Chem. These findings highlight the need for community science engagement to reveal otherwise impossible insights for models, observations, and real-time dissemination to understand, predict, and ultimately mitigate, urban neighborhood vulnerability to heat and air pollution.

To meet collective obligations towards biodiversity conservation and monitoring, it is essential that the world's governments and non-governmental organisations as well as the research community tap all possible sources of data and information, including new, fast-growing sources such as citizen science (CS), in which volunteers participate in some or all aspects of environmental assessments. Through compilation of a database on CS and community-based monitoring (CBM, a subset of CS) programs, we assess where contributions from CS and CBM are significant and where opportunities for growth exist. We use the Essential Biodiversity Variable framework to describe the range of biodiversity data needed to track progress towards global biodiversity targets, and we assess strengths and gaps in geographical and taxonomic coverage. Our results show that existing CS and CBM data particularly provide large-scale data on species distribution and population abundance, species traits such as phenology, and ecosystem function variables such as primary and secondary productivity. Only birds, Lepidoptera and plants are monitored at scale. Most CS schemes are found in Europe, North America, South Africa, India, and Australia. We then explore what can be learned from successful CS/CBM programs that would facilitate the scaling up of current efforts, how existing strengths in data coverage can be better exploited, and the strategies that could maximise the synergies between CS/CBM and other approaches for monitoring biodiversity, in particular from remote sensing. More and better targeted funding will be needed, if CS/CBM programs are to contribute further to international biodiversity monitoring.