Moss species and precipitation mediate experimental warming stimulation of growing season N2 fixation in subarctic tundra.

Climate change in high latitude regions leads to both higher temperatures and more precipitation but their combined effects on terrestrial ecosystem processes are poorly understood. In nitrogen (N) limited and often moss-dominated tundra and boreal ecosystems, moss-associated N2 fixation is an important process that provides new N. We tested whether high mean annual precipitation enhanced experimental warming effects on growing season N2 fixation in three common arctic-boreal moss species adapted to different moisture conditions and evaluated their N contribution to the landscape level. We measured in situ N2 fixation rates in Hylocomium splendens, Pleurozium schreberi and Sphagnum spp. from June to September in subarctic tundra in Sweden. We exposed mosses occurring along a natural precipitation gradient (mean annual precipitation: 571-1155 mm) to 8 years of experimental summer warming using open-top chambers before our measurements. We modelled species-specific seasonal N input to the ecosystem at the colony and landscape level. Higher mean annual precipitation clearly increased N2 fixation, especially during peak growing season and in feather mosses. For Sphagnum-associated N2 fixation, high mean annual precipitation reversed a small negative warming response. By contrast, in the dry-adapted feather moss species higher mean annual precipitation led to negative warming effects. Modelled total growing season N inputs for Sphagnum spp. colonies were two to three times that of feather mosses at an area basis. However, at the landscape level where feather mosses were more abundant, they contributed 50% more N than Sphagnum. The discrepancy between modelled estimates of species-specific N input via N2 fixation at the moss core versus ecosystem scale, exemplify how moss cover is essential for evaluating impact of altered N2 fixation. Importantly, combined effects of warming and higher mean annual precipitation may not lead to similar responses across moss species, which could affect moss fitness and their abilities to buffer environmental changes.

A systems-based analysis to rethink the European environmental risk assessment of regulated chemicals using pesticides as a pilot case.

A growing body of scientific literature stresses the need to advance current environmental risk assessment (ERA) methodologies and associated regulatory frameworks to better address the landscape-scale and long-term impact of pesticide use on biodiversity and the ecosystem. Moreover, more collaborative and integrative approaches are needed to meet sustainability goals. The One Health approach is increasingly applied by the European Food Safety Authority (EFSA) to support the transition towards safer, healthier and more sustainable food. To this end, EFSA commissioned the development of a roadmap for action to establish a European Partnership for next-generation, systems-based Environmental Risk Assessment (PERA). Here, we summarise the main conclusions and recommendations reported in the 2022 PERA Roadmap. This roadmap highlights that fragmentation of data, knowledge and expertise across regulatory sectors results in suboptimal processes and hinders the implementation of integrative ERA approaches needed to better protect the environment. To advance ERA, we revisited the underlying assumptions of the current ERA paradigm; that chemical risks are generally assessed and managed in isolation with a substance-by-substance, realistic worst-case and tiered approach. We suggest optimising the use of the vast amount of information and expertise available with pesticides as a pilot area. It is recommended to as soon as possible adopt a systems-based approach, i.e. within the current regulatory framework, to spark a step-wise transition towards an ERA framed at a system level of ecological and societal relevance. Tangible systems-based and integrative steps are available. For instance, the rich sources of existing data for prospective and retrospective ERA of pesticides could be used to reality-benchmark existing and new ERA methods. To achieve these goals, collaboration among stakeholders across scientific disciplines and regulatory sectors must be strengthened.

Body-size-dependent effects of landscape-level resource energetics on pollinator abundance in woodland remnants.

Land use change alters floral resource availability, thereby contributing to declines in important pollinators. However, the severity of land use impact varies by species, influenced by factors such as dispersal ability and resource specialization, both of which can correlate with body size. Here. we test whether floral resource availability in the surrounding landscape (the 'matrix') influences bee species' abundance in isolated remnant woodlands, and whether this effect varies with body size. We sampled quantitative flower-visitation networks within woodland remnants and quantified floral energy resources (nectar and pollen calories) available to each bee species both within the woodland and the matrix. Bee abundance in woodland increased with floral energy resources in the surrounding matrix, with strongest effects on larger-bodied species. Our findings suggest important but size-dependent effects of declining matrix floral resources on the persistence of bees in remnant woodlands, highlighting the need to incorporate landscape-level floral resources in conservation planning for pollinators in threatened natural habitats.

Landscape-Scale Biodiversity Impacts Analysis of Côte d'Ivoire's Cocoa Cultivation along Export Supply Chains.

Agricultural land use for export commodities leads to significant biodiversity impacts. A spatially detailed assessment of these impacts is crucial for implementing effective mitigation policies. Using cocoa cultivation and exports in Côte d'Ivoire as an example, we present a novel framework that combines earth observations, enhanced landscape-scale biodiversity models, and subnational export supply chain data sets to track the tele-connected potential biodiversity impacts of export groups and importing countries. We found that cocoa cultivation accounts for ∼44% of the biodiversity impacts in Côte d'Ivoire's cocoa cultivation areas, with >90% attributable to cocoa exports. The top 10 importing countries account for ∼84% of these impacts. Our method offers improved spatial detail compared to the existing approaches, facilitating the identification of biodiversity impact hotspots. Additionally, the biodiversity impacts of agroforestry cocoa are not always lower compared to full-sun cocoa, especially when agroforestry systems are established in regions of high biodiversity importance. Our transferable framework provides a comprehensive understanding of biodiversity footprint and promotes informed decision-making for sustainable agricultural production, processing, and trade. Our framework's application is currently constrained by the scarcity of detailed supply chain data sets; we underscore the urgent need for improved supply chain transparency to fully unlock the framework's potential.

The environmental impact assessment of China's ecological migration from a social-ecological perspective.

When accounting for the social-ecological impact of an ecological restoration program, both objective environmental contexts and people's subjective perceptions are required. While this kind of environmental impact assessment lacks a comprehensive perspective. We use the difference-in-differences model to evaluate the effect of the greenness of the landscape after ecological migration in the Qilian Mountains in China; and analysis of variance and fixed effects models are used to evaluate the effects of such ecological restoration programs on local people's perceptions. The results show that the ecological migration program in the Qilian Mountains has been successful at not only significantly improving remotely sensed greenness at the landscape scale, but also at enhancing immigrants' environmental perceptions. These findings demonstrate the environmental impacts of ecological migration from a social-ecological perspective, and can provide methodological implications for landscape planning to support a better understanding of ecological restoration programs in the drylands.

Improving strategic planning for nature: Panacea or pandora's box for the built and natural environment?

This paper assesses how strategic planning for nature can be improved for England's built and natural environment using mainstreaming and landscape-scale concepts. Whilst both concepts feature in academic literature, there has been limited attention on their role as catalytic agents for strategic planning. Addressing this gap, evidence is used from two stakeholder workshops involving 62 senior policy experts managing a range of operational and hypothetical strategic spatial planning challenges. The results reveal a significantly weakened strategic planning arena characterised by policy disintegration, short termism and uncertainty. Key findings highlight the fallacy of pursuing strategic planning for nature in isolation from wider policy integration fusing environmental, economic and social components from the outset. Current barriers to progress include institutional inertia, technocratic vocabularies and neoliberalist priorities exacerbated by a weak underlying theory. Conversely opportunities for mainstreaming processes may help knowledge generation and exchange within transdisciplinary partnerships, whilst landscape scale thinking can improve understanding of issues using natures inherent geometry transforming processes and outcomes. The paper recommends the adoption of strategic planning pathways using mainstreaming and landscape-scale approaches working in tandem. Whilst focused on the English context, our findings are transferable to other planning systems in the Global North, especially those championing neoliberal market led policies.

A spatiotemporally explicit modeling approach for more realistic exposure and risk assessment of off-field soil organisms.

Natural and seminatural habitats of soil living organisms in cultivated landscapes can be subject to unintended exposure by active substances of plant protection products (PPPs) used in adjacent fields. Spray-drift deposition and runoff are considered major exposure routes into such off-field areas. In this work, we develop a model (xOffFieldSoil) and associated scenarios to estimate exposure of off-field soil habitats. The modular model approach consists of components, each addressing a specific aspect of exposure processes, for example, PPP use, drift deposition, runoff generation and filtering, estimation of soil concentrations. The approach is spatiotemporally explicit and operates at scales ranging from local edge-of-field to large landscapes. The outcome can be aggregated and presented to the risk assessor in a way that addresses the dimensions and scales defined in specific protection goals (SPGs). The approach can be used to assess the effect of mitigation options, for example, field margins, in-field buffers, or drift-reducing technology. The presented provisional scenarios start with a schematic edge-of-field situation and extend to real-world landscapes of up to 5 km × 5 km. A case study was conducted for two active substances of different environmental fate characteristics. Results are presented as a collection of percentiles over time and space, as contour plots, and as maps. The results show that exposure patterns of off-field soil organisms are of a complex nature due to spatial and temporal variabilities combined with landscape structure and event-based processes. Our concepts and analysis demonstrate that more realistic exposure data can be meaningfully consolidated to serve in standard-tier risk assessments. The real-world landscape-scale scenarios indicate risk hot-spots that support the identification of efficient risk mitigation. As a next step, the spatiotemporally explicit exposure data can be directly coupled to ecological effect models (e.g., for earthworms or collembola) to conduct risk assessments at biological entity levels as required by SPGs. Integr Environ Assess Manag 2024;20:263-278. © 2023 Applied Analysis Solutions LLC and WSC Scientific GmbH and Bayer AG and The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Use of the term "landscape" in sustainable agriculture research: A literature review.

Finding consensus in definitions of commonly-used terms and concepts is a key requirement to enable cooperations between interdisciplinary scientists and practitioners in inter- or transdisciplinary projects. In research on sustainable agriculture, the term 'landscape' is emphasised in particular, being used in studies that range from biogeochemical to socio-economic topics. However, it is normally used in a rather unspecific manner. Moreover, different disciplines assign deviating meanings to this term, which impedes interdisciplinary understanding and synthesis. To close this gap, a systematic literature review from relevant disciplines was conducted to identify a common understanding of the term "landscape". Three general categories of landscape conceptualizations were identified. In a small subset of studies, "landscape" is defined by area size or by natural or anthropogenic borders. The majority of reviewed papers, though, define landscapes as sets of relationships between various elements. Selection of respective elements differed widely depending on research objects. Based on these findings, a new definition of landscape is proposed, which can be operationalized by interdisciplinary researchers to define a common study object and which allows for sufficient flexibility depending on specific research questions. It also avoids over-emphasis on specific spatio-temporal relations at the "landscape scale", which may be context-dependent. Agricultural landscape research demands for study-specific definitions which should be meticulously provided in the future.

Sustainable transformation of agriculture requires landscape experiments.

Transformation of agriculture to realise sustainable site-specific management requires comprehensive scientific support based on field experiments to capture the complex agroecological process, incite new policies and integrate them into farmers' decisions. However, current experimental approaches are limited in addressing the wide spectrum of sustainable agroecosystem and landscape characteristics and in supplying stakeholders with suitable solutions and measures. This review identifies major constraints in current field experimentation, such as a lack of consideration of multiple processes and scales and a limited ability to address interactions between them. It emphasizes the urgent need to establish a new category of landscape experimentation that empowers agricultural research on sustainable agricultural systems, aiming at elucidating interactions among various landscape structures and functions, encompassing both natural and anthropogenic features. It extensively discusses the key characteristics of landscape experiments and major opportunities to include them in the agricultural research agenda. In particular, simultaneously considering multiple factors, and thus processes at different scales and possible synergies or antagonisms among them would boost our understanding of heterogeneous agricultural landscapes. We also highlight that though various studies identified promising approaches with respect to experimental design and data analysis, further developments are still required to build a fully functional and integrated framework for landscape experimentation in agricultural settings.

Aquatic Risks at the Landscape Scale: A Case Study for Pyrethroid Use in Pome Fruit Orchards in Belgium.

Procedures for environmental risk assessment for pesticides are under continuous development and subject to debate, especially at higher tier levels. Spatiotemporal dynamics of both pesticide exposure and effects at the landscape scale are largely ignored, which is a major flaw of the current risk assessment system. Furthermore, concrete guidance on risk assessment at landscape scales in the regulatory context is lacking. In this regard, we present an integrated modular simulation model system that includes spatiotemporally explicit simulation of pesticide application, fate, and effects on aquatic organisms. As a case study, the landscape model was applied to the Rummen, a river catchment in Belgium with a high density of pome fruit orchards. The application of a pyrethroid to pome fruit and the corresponding drift deposition on surface water and fate dynamics were simulated. Risk to aquatic organisms was quantified using a toxicokinetic/toxicodynamic model for individual survival at different levels of spatial aggregation, ranging from the catchment scale to individual stream segments. Although the derivation of landscape-scale risk assessment end points from model outputs is straightforward, a dialogue within the community, building on concrete examples as provided by this case study, is urgently needed in order to decide on the appropriate end points and on the definition of representative landscape scenarios for use in risk assessment.

Quality matters: Stoichiometry of resources modulates spatial feedbacks in aquatic-terrestrial meta-ecosystems.

Species dispersal and resource spatial flows greatly affect the dynamics of connected ecosystems. So far, research on meta-ecosystems has mainly focused on the quantitative effect of subsidy flows. Yet, resource exchanges at heterotrophic-autotrophic (e.g. aquatic-terrestrial) ecotones display a stoichiometric asymmetry that likely matters for functioning. Here, we joined ecological stoichiometry and the meta-ecosystem framework to understand how subsidy stoichiometry mediates the response of the meta-ecosystem to subsidy flows. Our model results demonstrate that resource flows between ecosystems can induce a positive spatial feedback loop, leading to higher production at the meta-ecosystem scale by relaxing local ecosystem limitations ('spatial complementarity'). Furthermore, we show that spatial flows can also have an unexpected negative impact on production when accentuating the stoichiometric mismatch between local resources and basal species needs. This study paves the way for studies on the interdependency of ecosystems at the landscape extent.

A firebreak placement model for optimizing biodiversity protection at landscape scale.

A solution approach is proposed to optimize the selection of landscape cells for inclusion in firebreaks. It involves linking spatially explicit information on a landscape's ecological values, historical ignition patterns and fire spread behavior. A firebreak placement optimization model is formulated that captures the tradeoff between the direct loss of biodiversity due to the elimination of vegetation in areas designated for placement of firebreaks and the protection provided by the firebreaks from losses due to future forest fires. The optimal solution generated by the model reduced expected losses from wildfires on a biodiversity combined index due to wildfires by 30% relative to a landscape without any treatment. It also reduced expected losses by 16% compared to a randomly chosen solution. These results suggest that biodiversity loss resulting from the removal of vegetation in areas where firebreaks are placed can be offset by the reduction in biodiversity loss due to the firebreaks' protective function.

Evaluating and Explaining the Variability of Honey Bee Field Studies across Europe Using BEEHAVE.

To assess the effect of plant protection products on pollinator colonies, the higher tier of environmental risk assessment (ERA), for managed honey bee colonies and other pollinators, is in need of a mechanistic effect model. Such models are seen as a promising solution to the shortcomings, which empirical risk assessment can only overcome to a certain degree. A recent assessment of 40 models conducted by the European Food Safety Authority (EFSA) revealed that BEEHAVE is currently the only publicly available mechanistic honey bee model that has the potential to be accepted for ERA purposes. A concern in the use of this model is a lack of model validation against empirical data, spanning field studies conducted in different regions of Europe and covering the variability in colony and environmental conditions. We filled this gap with a BEEHAVE validation study against 66 control colonies of field studies conducted across Germany, Hungary, and the United Kingdom. Our study implements realistic initial colony size and landscape structure to consider foraging options. Overall, the temporal pattern of colony strength is predicted well. Some discrepancies between experimental data and prediction outcomes are explained by assumptions made for model parameterization. Complementary to the recent EFSA study using BEEHAVE, our validation covers a large variability in colony conditions and environmental impacts representing the Northern and Central European Regulatory Zones. Thus we believe that BEEHAVE can be used to serve the development of specific protection goals as well as the development of simulation scenarios for the European Regulatory Zone. Subsequently, the model can be applied as a standard tool for higher tier ERA of managed honey bees using the mechanistic ecotoxicological module for BEEHAVE, BEEHAVEecotox . Environ Toxicol Chem 2023;42:1839-1850. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Wind erosion induced low-density microplastics migration at landscape scale in a semi-arid region of northern China.

Microplastics (MPs) have been extensively investigated in terrestrial environments, while the occurrence and movement of MPs at the landscape scale in semi-arid regions with serious wind erosion are less well studied. Here, we sampled film mulching farmland and downwind nearby grassland surface soils in a semi-arid region of northern China to explore the distribution of MPs at different downwind distances and the potential environmental risk to the local landscapes. The results revealed that the MP abundances presented a decreasing trend with increasing downwind distance (Mann-Kendall test, P < 0.01). The MP size distributions at different distances showed similar sigmoid trends described by logistic models. MP fiber size (500-2000 µm) abundance in the farmland was higher than that of the grassland. By contrast, MP non-fiber size (<1000 µm) abundance of farmlands was less than that of the grassland. The abundances of fibers larger than 500 µm and non-fibers larger than 1000 µm in size decreased exponentially with increasing downwind distance. The size of transported MPs at the landscape scale was larger than that of long-distance dispersal. The migration of MPs from farmlands can pose a potential threat to the downwind landscape, leading the downwind grassland to be a potential MP emission source. This study presents the first insights into the MPs distribution among different downwind distances at the landscape scale. Future research is required to deploy aeolian sediment sampling devices and establish the connection between the field data and the MP emission models.

Balancing disturbance risk and ecosystem service provisioning in Swiss mountain forests: an increasing challenge under climate change.

Climate change severely affects mountain forests and their ecosystem services, e.g., by altering disturbance regimes. Increasing timber harvest (INC) via a close-to-nature forestry may offer a mitigation strategy to reduce disturbance predisposition. However, little is known about the efficiency of this strategy at the scale of forest enterprises and potential trade-offs with biodiversity and ecosystem services (BES). We applied a decision support system which accounts for disturbance predisposition and BES indicators to evaluate the effect of different harvest intensities and climate change scenarios on windthrow and bark beetle predisposition in a mountain forest enterprise in Switzerland. Simulations were carried out from 2010 to 2100 under historic climate and climate change scenarios (RCP4.5, RCP8.5). In terms of BES, biodiversity (structural and tree species diversity, deadwood amount) as well as timber production, recreation (visual attractiveness), carbon sequestration, and protection against gravitational hazards (rockfall, avalanche and landslides) were assessed. The INC strategy reduced disturbance predisposition to windthrow and bark beetles. However, the mitigation potential for bark beetle disturbance was relatively small (- 2.4%) compared to the opposite effect of climate change (+ 14% for RCP8.5). Besides, the INC strategy increased the share of broadleaved species and resulted in a synergy with recreation and timber production, and a trade-off with carbon sequestration and protection function. Our approach emphasized the disproportionally higher disturbance predisposition under the RCP8.5 climate change scenario, which may threaten currently unaffected mountain forests. Decision support systems accounting for climate change, disturbance predisposition, and BES can help coping with such complex planning situations. Supplementary Information: The online version contains supplementary material available at 10.1007/s10113-022-02015-w.

Heterogeneity in biological assemblages and exposure in chemical risk assessment: Exploring capabilities and challenges in methodology with two landscape-scale case studies.

Chemical exposure concentrations and the composition of ecological receptors (e.g., species) vary in space and time, resulting in landscape-scale (e.g. catchment) heterogeneity. Current regulatory, prospective chemical risk assessment frameworks do not directly address this heterogeneity because they assume that reasonably worst-case chemical exposure concentrations co-occur (spatially and temporally) with biological species that are the most sensitive to the chemical's toxicity. Whilst current approaches may parameterise fate models with site-specific data and aim to be protective, a more precise understanding of when and where chemical exposure and species sensitivity co-occur enables risk assessments to be better tailored and applied mitigation more efficient. We use two aquatic case studies covering different spatial and temporal resolution to explore how geo-referenced data and spatial tools might be used to account for landscape heterogeneity of chemical exposure and ecological assemblages in prospective risk assessment. Each case study followed a stepwise approach: i) estimate and establish spatial chemical exposure distributions using local environmental information and environmental fate models; ii) derive toxicity thresholds for different taxonomic groups and determine geo-referenced distributions of exposure-toxicity ratios (i.e., potential risk); iii) overlay risk data with the ecological status of biomonitoring sites to determine if relationships exist. We focus on demonstrating whether the integration of relevant data and potential approaches is feasible rather than making comprehensive and refined risk assessments of specific chemicals. The case studies indicate that geo-referenced predicted environmental concentration estimations can be achieved with available data, models and tools but establishing the distribution of species assemblages is reliant on the availability of a few sources of biomonitoring data and tools. Linking large sets of geo-referenced exposure and biomonitoring data is feasible but assessment of risk will often be limited by the availability of ecotoxicity data. The studies highlight the important influence that choices for aggregating data and for the selection of statistical metrics have on assessing and interpreting risk at different spatial scales and patterns of distribution within the landscape. Finally, we discuss approaches and development needs that could help to address environmental heterogeneity in chemical risk assessment.

Alpine Treeline Dynamics and the Special Exposure Effect in the Hengduan Mountains.

Alpine treeline is highly sensitive to climate change, but there remains a lack of research on the spatiotemporal heterogeneity of treeline and their relationships with climate change at the landscape scale. We extracted positions of alpine treeline from high-resolution Google Earth images from three periods (2000, 2010, and 2020) and analyzed the elevation patterns and dynamics of treeline positions in the Hengduan Mountains. Based on the treeline positions in 2020, a buffer zone of 300 m is established as the treeline transition zone, and the changing trend of the fraction vegetation cover (FVC) from 2000 to 2020 and its relationship with climate are also analyzed. Due to the special geographical and climatic environment, the treeline in the Hengduan Mountains area is high in the middle but lower in the surrounding areas. We found that over the past 20 years, the treeline position did not change significantly but that the FVC increased in 80.3% of the treeline areas. The increase in FVC was related to the decrease in precipitation in the growing season. The results also revealed a special exposure effect on the alpine treeline in the Hengduan Mountains. Because of the lower treeline, isotherm position caused by the monsoon climate, the treeline position on south-facing slopes is lower than that on slopes with other exposures. Our results confirmed that the pattern and dynamics of the alpine treeline are driven by the regional monsoon climate regime.

Spatiotemporal characteristics of NO2, PM2.5 and O3 in a coastal region of southeastern China and their removal by green spaces.

Understanding the spatio-temporal characteristics of air pollutants is essential to improving air quality. One aspect is the question of whether green spaces can reduce air pollutant concentrations. However, previous studies on this issue have reported mixed results. This study analyzed the spatio-temporal characteristics of NO2, PM2.5 and O3 in Fujian Province, Southeast China in 2015. In order to reduce uncertainties in the conclusions drawn, the effects landscape metrics describing green spaces have on air pollutants have been analyzed using Pearson correlation analysis at six different spatial scales for the four seasons, considering the influence of meteorological conditions. The results show that PM2.5 and O3 are major pollutants whose relative importance varies with the seasons. Significant differences in pollutant concentrations were observed in suburban and urban areas, highlighting the importance of ensuring a reasonable spatial distribution of monitoring stations. Moreover, significant correlations between air pollutants and green space landscape patterns during the four seasons were found, revealing increased air pollutant concentrations with increasing landscape fragmentation and reduced connectivity and aggregation. This probably indicates that interconnected green spaces have the potential to improve air quality. Utilizing green space function regulations can alleviate NO2 and PM2.5 pollution effectively, but it is still difficult to reduce O3 concentrations because green spaces are likely to not only serve as sinks for O3, but can also promote O3 formation.

Resolving the SLOSS dilemma for biodiversity conservation: a research agenda.

The legacy of the 'SL > SS principle', that a single or a few large habitat patches (SL) conserve more species than several small patches (SS), is evident in decisions to protect large patches while down-weighting small ones. However, empirical support for this principle is lacking, and most studies find either no difference or the opposite pattern (SS > SL). To resolve this dilemma, we propose a research agenda by asking, 'are there consistent, empirically demonstrated conditions leading to SL > SS?' We first review and summarize 'single large or several small' (SLOSS) theory and predictions. We found that most predictions of SL > SS assume that between-patch variation in extinction rate dominates the outcome of the extinction-colonization dynamic. This is predicted to occur when populations in separate patches are largely independent of each other due to low between-patch movements, and when species differ in minimum patch size requirements, leading to strong nestedness in species composition along the patch size gradient. However, even when between-patch variation in extinction rate dominates the outcome of the extinction-colonization dynamic, theory can predict SS > SL. This occurs if extinctions are caused by antagonistic species interactions or disturbances, leading to spreading-of-risk of landscape-scale extinction across SS. SS > SL is also predicted when variation in colonization dominates the outcome of the extinction-colonization dynamic, due to higher immigration rates for SS than SL, and larger species pools in proximity to SS than SL. Theory that considers change in species composition among patches also predicts SS > SL because of higher beta diversity across SS than SL. This results mainly from greater environmental heterogeneity in SS due to greater variation in micro-habitats within and across SS habitat patches ('across-habitat heterogeneity'), and/or more heterogeneous successional trajectories across SS than SL. Based on our review of the relevant theory, we develop the 'SLOSS cube hypothesis', where the combination of three variables - between-patch movement, the role of spreading-of-risk in landscape-scale population persistence, and across-habitat heterogeneity - predict the SLOSS outcome. We use the SLOSS cube hypothesis and existing SLOSS empirical evidence, to predict SL > SS only when all of the following are true: low between-patch movement, low importance of spreading-of-risk for landscape-scale population persistence, and low across-habitat heterogeneity. Testing this prediction will be challenging, as it will require many studies of species groups and regions where these conditions hold. Each such study would compare gamma diversity across multiple landscapes varying in number and sizes of patches. If the prediction is not generally supported across such tests, then the mechanisms leading to SL > SS are extremely rare in nature and the SL > SS principle should be abandoned.

First landscape-scale survey of the background level of COVID-19 face mask litter: Exploring the potential for citizen science data collection during a 'pollution pilgrimage' of walking a 250-km roadside transect.

The COVID-19 pandemic has generated a global problem through the cavalier or deliberate disposal of personal protective equipment (PPE) by the general public. This has raised concerns that the billions of discarded face masks pose a threat to wildlife through entanglement or, when broken down, through ingestion of derived microplastics. Previous quantitative surveys of the magnitude of such litter have focused on areas where people congregate, such as tourist beaches and large cities. The present survey is the first to provide data on the background level of face mask litter through a landscape of variable land-use. A 250-km transect along an historic road between Montreal and Quebec City (Canada) was surveyed during a walking pilgrimage, revealing an overall density of 0.0001 ± 0.00006 face masks m-2. Average densities were significantly higher in areas of human occupation compared to agricultural and forested rural land. However, there was no significant correlation between population size of communities and the number of face masks encountered, nor in litter extent and proximity to municipalities. This may be due to the confounding influence of inter-community differences in scheduled street cleaning operations. Seventy-six percent of face masks were of the disposable surgical variety, with the remaining 24% being reusable cloth masks. This, and the fact that only 10% of the former and none of the latter exhibited broken ear straps, insinuates that the litter could be due to accidental loss rather than inappropriate discarding by individuals en route. Scaling-up these findings in relation to the global road network generates a preliminary background estimate for roadside litter of >17 million face masks. The present study endorses the call made by others to engage citizen scientists in surveying PPE litter, in particular, the thousands who each year walk the medieval pilgrimage routes through the landscape of Europe.