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Coastal areas are at the centre of human–nature relationship, shaped by recreation, tourism and aesthetic values. However, socioeconomic drivers of biodiversity change in coastal areas have received less attention. Soft sediment seafloors support diverse species communities and contribute to ecosystem functionality. One of the main threats is dredging, which sweeps resident organisms. Dredgings are commonly done to deepen waterways, but also for the purposes of private housing. The ecological impacts of these small‐sized dredgings are not well known over broad environmental and geographical gradients. We developed a simple approach for spatial integration of ecological and socioeconomic system, to describe how recreational land use change contributes to the loss of marine biodiversity. It shows how human behaviour, such as preference for a location of second home, can be derived from spatial data and coupled with ecological change. We characterize typical locations of second homes based on accessibility, aesthetics and environment, and with the information identified suitable areas for new second homes. We also quantified typical areas of dredging, based on the depth and substrate of the sea floor, and the extent of the reed beds, influencing the access to properties. We then simulate an annual increase of new second homes and expected land‐use change, namely dredging of shores. Finally, we quantified the realized and projected loss of marine biodiversity from dredged sites, based on species distribution models, relying on extensive ecological data collected from over 170,000 underwater sites. We found that small‐sized dredging can be detrimental to coastal biodiversity, as dredging targets shallow, photic bays and lagoons, with diverse algal and aquatic plant communities, with limited recovery potential. Dredgings also had broad impacts on benthic faunal habitats, which maintain ecosystem processes and functions. Our results reveal a significant ecological change driven by recreational land use. Reversing the trend of biodiversity loss requires a holistic understanding of socioecological systems. Our results highlight the need for integrating land–sea interactions into conservation policies and reforming current land‐use regulation for the benefit of marine biodiversity. Read the free Plain Language Summary for this article on the Journal blog. Read the free Plain Language Summary for this article on the Journal blog.

Background Due to the myriad of benefits of children’s outdoor play and time, there is increasing concern over its decline. This systematic review synthesized evidence on the correlates of outdoor play and outdoor time among children aged 3-12 years. Methods A total of 12 electronic databases in five different languages (Chinese, English, Korean, Spanish, Portuguese) were searched between October 28, 2019 and July 27, 2020. Covidence software was used for screening and Microsoft Excel with a predesigned coding form was used for data extraction. Evidence was synthesized and correlates were categorized using the socioecological model framework. Results Based on 107 studies representing 188,498 participants and 422 childcare centers from 29 countries, 85 studies examined potential correlates of outdoor play while 23 studies examined that of outdoor time (one examined both). The duration of outdoor play and outdoor time ranged between 60 and 165 min/d and 42-240 min/d, respectively. Out of 287 (outdoor play) and 61 (outdoor time) potential correlates examined, 111 correlates for outdoor play and 33 correlates for outdoor time were identified as significant correlates. Thirty-three variables were identified as key/common correlates of outdoor play/time, including eight correlates at the individual level (e.g., sex/gender, race/ethnicity, physical activity), 10 correlates at the parental level (e.g., parental attitude/support/behavior, parenting practice), nine at the microsystem level (e.g., proximal home/social environment such as residence type, peer influence), three at the macrosystem/community level (e.g., availability of space children can play), and three at the physical ecology/pressure for macrosystem change level (e.g., seasonality, rurality). No key correlates were found at the institutional level. Conclusions Individual, parental, and proximal physical (home) and social environments appear to play a role in children’s outdoor play and time. Ecological factors (i.e., seasonality, rurality) also appear to be related to outdoor play/time. Evidence was either inconsistent or lacking at institutional and macrosystem/community levels. Standardizing terminology and measures of outdoor play/time is warranted. Future work should investigate the interactions and processes of multiple variables across different levels of socioecological modelling to better understand the mechanisms through which outdoor play/time opportunities can be optimized for children while paying special attention to varying conditions in which children are born, live, and play.

Post-traumatic stress disorder (PTSD) occurs because of a variety of stressful situations and can be alleviated by a combination of support factors across different socio-ecological levels. The study investigates the impact of support at different socio-ecological levels on risk factors for PTSD in military families. A survey of 366 Slovenian service members and their spouses or intimate partners was conducted. We ran a basic regression model of risk factors for PTSD and later 6 two-stage hierarchical regression analyses to determine how the effect of risk factors on PTSD changes when support factors are added. On the micro level: 1) work environment support lessens the negative impact of general health and depression on PTSD; 2) spousal/intimate partner support is beneficial for women; and 3) family support offsets the negative impact of work on PTSD. On the meso and macro levels, community and military support ease the negative impact of the direct work environment, while macro national support significantly contributes to reducing PTSD.

Certified organic farming is a suite of regulated practices that can support social, economic, and ecological sustainability in agriculture. Despite the standardization and regulation of certifying bodies, practices adopted by organic farmers vary with potential heterogeneous effects on environmental outcomes. While it is accepted that beliefs can enable or constrain the adoption of farming practices, it remains unclear if variation in organic farmer beliefs mediates observed heterogeneity in practices and the ecology of farms. Communities of soil microorganisms that induce plant resistance and regulate insect herbivores offer a lens to explore the relationship between beliefs and practice adoption. Variation in insect herbivores across organic farms is common but none have studied the role of farmer beliefs in regulating pests through the soil microbiome. Herein, we hypothesized that variation in adoption of microbiome-supportive practices by organic farmers is driven by heterogeneity in their microbiome beliefs. We also investigate the importance of demographic variables and farm characteristics, compared to farmer beliefs, for adoption of practices that support the microbiome. To test our hypothesis, we surveyed the microbiome beliefs, farming practices, and motivations of 85 organic farmers in New York State, USA. We used affinity propagation to cluster farmers by their beliefs, and statistical models to evaluate variation in farming practice adoption and farmer motivations. Our survey received a 30.5% response rate, most organic farmers (≈96%) believed the soil microbiome was important for supporting plant defenses and reducing pests, and <16% believed their farming practices were unimportant for promoting beneficial microbiomes. Seven clusters of farmers were identified that varied in their microbiome beliefs. Among the clusters ≈42% of farmers believed on-farm management and external factors (e.g., climate change) were important for promoting the microbiome. These farmers used fewer pesticides and synthetic mulches, more pre-planting practices (e.g., solarization), and were more motivated to adopt new practices to support the microbiome than their peers. The most important factors motivating adoption were reductions in pests, increased yields, and biodiversity benefits. Beliefs, demographics, and farm characteristics (e.g., time in organic management) were correlated with similar suites of farming practices, but only beliefs predicted farmer motivations. Our study suggests beliefs are key to understanding farmer motivations and promoting organic farming system sustainability via the pest-suppressive microbiome. More broadly, we suggest the need for socio-ecological approaches that account for farmer beliefs when studying the adoption of conservation practices in agroecosystems.

River ecosystems world-wide are affected by altered flow regimes, and advanced science and practice of environmental flows have been developed to understand and reduce these impacts. But most environmental flows approaches ignore flow intermittency, which is a natural feature of 30% of the global river network length. Ignoring flow intermittency when setting environmental flows in naturally intermittent rivers might lead to deleterious ecological effects.We review evidence of the ecological effects of flow intermittency and provide guidance to incorporate intermittency (non-flow events) into existing methods judged as suitable for application in temporary waterways.To better integrate non-flow events into hydrological methods, we propose a suite of new indicators to be used in the range of variability approach. These indicators reflect dry periods and the unpredictable nature of temporary waterways. We develop a predictability index for protecting those species adapted to temporary conditions.For hydraulic-habitat models, we find that mesohabitat methods are particularly effective for describing complex habitat dynamics during dry phases. We present an example of the European eel to show the relationship between discharge and non-flow days and wet area, habitat suitability and connectivity.We find that existing holistic approaches may be applied to temporary waterways without significant structural alteration to their stepwise frameworks, but new component methods are needed to address flow-related aspects across both flow and non-flow periods of the flow regime.Synthesis and applications. Setting environmental flow requirements for temporary waterways requires modification and enhancement of existing approaches and methodologies, most notably the explicit consideration of non-flow events and greater integration of specific geomorphic, hydrogeologic and hydraulic elements. Temporary waterways are among the freshwater ecosystems most vulnerable to alterations in flow regimes, and they are also under great pressure. The methodological modifications recommended in this paper will aid water managers in protecting key components of temporary flow regimes, thereby preserving their unique ecology and associated services.

The ecosystem service concept has emphasized the role of people within socio-ecological systems (SESs). In this paper, we review and discuss alternative ways of representing people, their behaviour and decision-making processes in SES models using an agent-based modelling (ABM) approach. We also explore how ABM can be empirically grounded using information from social survey. The capacity for ABM to be generalized beyond case studies represents a crucial next step in modelling SESs, although this comes with considerable intellectual challenges. We propose the notion of human functional types, as an analogy of plant functional types, to support the expansion (scaling) of ABM to larger areas. The expansion of scope also implies the need to represent institutional agents in SES models in order to account for alternative governance structures and policy feedbacks. Further development in the coupling of human-environment systems would contribute considerably to better application and use of the ecosystem service concept.

Expanding the footprint of natural fire has been proposed as one potential solution to increase the pace of forest restoration programs in fire‐adapted landscapes of the western USA. However, studies that examine the long‐term socio‐ecological trade‐offs of expanding natural fire to reduce wildfire risk and create fire resilient landscapes are lacking. We used the model Envision to examine the outcomes that might result from increased area burned by what we call “restoration” wildfire in a landscape where the ecological benefits of wildfire are known, but the need to suppress high‐risk fires that threaten human values is also evident. Our study area, in the eastern Cascades of Oregon, USA, includes the Deschutes National Forest where large tracts of mixed conifer forest structure are outside the historical range of variation and characterized by multi‐layer, closed‐canopy stands. We found that simulation of one restoration wildfire per year in addition to high‐risk wildfires in the regular fire season and over the course of 50 yr resulted in a 23% increase in total area burned, but the same probability of fire‐on‐fire interactions. This translated into 0.3% of the national forest burned by restoration wildfire per year and had a small impact in area burned by high‐risk fires albeit more likely in extreme fire years. Smoke production doubled in the restoration scenario relative to the scenario without restoration wildfire, but still resulted in minimal smoke production in most years. Restoration fires burned with low‐ to mixed‐severity and led to a steady reduction in canopy cover and increase in resilient forest structure in dry‐forest types. Habitat for the federally protected northern spotted owl declined with the inclusion of restoration fire, while habitat for species that use recently burned forest stands (e.g., black‐backed woodpecker) increased. Our results suggest that restoration wildfire can improve forest resilience and contribute to restoration efforts in fire‐adapted forests, but there are trade‐offs (wildlife habitat, smoke, area burned in fire‐sensitive forest types), and the level of restoration fire use we simulated is unlikely to have a significant impact on the occurrence of high‐severity wildfires.

The idea that human impacts on natural systems might trigger large‐scale, social–ecological ‘crises’ or ‘breakdowns’ is attracting increasing scientific, societal and political attention, but the risks of such crises remain hard to assess or ameliorate. Social–ecological systems have complex dynamics, with bifurcations, nonlinearities and tipping points all emerging from the interaction of multiple human and natural processes. Computational modelling is a key tool in understanding these processes and their effects on system resilience. However, models that operate over large geographical extents often rely on assumptions such as economic equilibrium and optimisation in social–economic systems, and mean‐field or trend‐based behaviour in ecological systems, which limit the simulation of crisis dynamics. Alternative forms of modelling focus on simulating local‐scale processes that underpin the dynamics of social–ecological systems. Recent improvements in data resources and computational tools mean that such modelling is now technically feasible across large geographical extents. We consider the contributions that the different types of model can make to simulating social–ecological crises. While no models are able to predict exact outcomes in complex social–ecological systems, we suggest that one new approach with substantial promise is hybrid modelling that uses existing model architectures to isolate and understand key processes, revealing risks and associated uncertainties of crises emerging. We outline convergent and efficient functional descriptions of social and ecological systems that can be used to develop such models, data resources that can support them, and possible ‘high‐level’ processes that they can represent. A free Plain Language Summary can be found within the Supporting Information of this article A free Plain Language Summary can be found within the Supporting Information of this article.

Background Active school travel (AST) is influenced by multiple factors including built and social environments, households and individual variables. A holistic theory such as Mitra’s Behavioural Model of School Transportation (BMST) is vital to comprehensively understand these complex interrelationships. This study aimed to assess direct and indirect associations between children’s AST and environmental, household and child factors based on the BMST using structural equation modelling (SEM). Methods Data were drawn from Neighbourhoods for Active Kids (NfAK), a cross-sectional study of 1102 children aged 8–13 years (school years 5–8) and their parents from nine intermediate and 10 primary schools in Auckland, New Zealand between February 2015 and December 2016. Data were collected using an online participatory mapping survey (softGIS) with children, a computer-assisted telephone interviewing survey (CATI) with parents, and ArcGIS for built environment attributes. Based on the BMST a conceptual model of children’s school travel behaviour was specified for SEM analyses (‘hypothesised SEM’), and model modification was made to improve the model (‘modified SEM’). SEM analyses using Mplus were performed to test the hypothesised/modified SEM and to assess direct and indirect relationships among variables. Results The overall fit of the modified SEM was acceptable ( N  = 542; Root mean square error of approximation = 0.04, Comparative fit index = 0.94, Tucker-Lewis index = 0.92). AST was positively associated with child independent mobility, child-perceived neighbourhood safety, and parent-perceived importance of social interaction and neighbourhood social environment. Distance to school, and parental perceptions of convenience and concerns about traffic safety were negatively associated with AST. Parental fears of stranger danger were indirectly related to AST through those of traffic safety. Distance to school and child independent mobility mediated relationships between AST and child school year and sex. Conclusions Increasing children’s AST requires action on multiple fronts including communities that support independent mobility by providing child friendly social and built environments, safety from traffic, and policies that promote local schools and safe vehicle-free zones around school.

Context Understanding the roles of different drivers in land use and land cover change (LULCC) is a critical research challenge. However, as LULCC is the result of complex, socio-ecological processes and is highly context dependent, achieving such understanding is difficult. This is particularly true for causal modelling approaches that are critical for effective policy formulation. Causal machine learning (ML) methods could help address this challenge, but are as yet poorly understood or applied by the LULCC community. Objectives To provide an accessible introduction to the state of the art for causal ML methods, their limitations, and their potential applications understanding LULCC. Methods We conducted two workshops where we identified the most promising ML methods for increasing understanding of LULCC dynamics. Results We provide a brief overview of the challenges to causal modelling of LULCC, including a simple example, and the most relevant causal ML approaches for addressing these challenges, as well as their limitations. Conclusions Causal ML methods hold considerable promise for improving causal modelling of LULCC. However, the complexity of LULCC dynamics mean that such methods must be combined with domain understanding and qualitative insights for effective policy design.