Local Scale Research Articles

Nestbox use indicates declining arboreal mammals in an Australian savanna may be limited by tree hollow availability

In the tropical savannas of northern Australia, many native mammal species are experiencing rapid and ongoing declines due to multiple interacting threats. These mostly arboreal and semi-arboreal mammals are reliant on tree hollows for shelter, which may be contributing to their decline. We monitored 198 nestboxes over three years across a 100-km transect on Cobourg Peninsula, where a diverse arboreal mammal community still occurs. Most nestboxes (67%) were used by at least one of five mammal species, all of which are declining and four are threatened. Hollow density (proxied by eucalypt stand density) varied across sites, with the number of eucalypts (>20 cm DBH) ranging between 20 and 140 per hectare and averaging 74 ± 28 (SD) per hectare. Correspondingly, the likelihood and frequency of nestbox use by arboreal mammals increased with declining local tree hollow density, indicating that hollows are a critical limiting resource at the local scale for arboreal mammals in this region. Frequent, local disturbances e.g., fire and introduced species, contribute to threatening processes. Therefore, reversing the decline of arboreal mammals in Australia’s tropical savannas requires multiple management interventions, including conserving hollow-bearing trees as ecosystem assets.

Peri-urban Mediterranean plant communities are shaped by chronic anthropogenic disturbances

Peri-urban plant communities perform key ecological functions. However, the integrity of peri-urban vegetation is threatened by the continuous expansion of built-up areas and anthropogenic activities, which result in low-intensity, but continuous and pervasive chronic anthropogenic disturbances (CADs). Despite the growing attention to the ecological role of peri-urban vegetation patches, the assessment of the relationship between CADs and typical Mediterranean plant communities at the local scale is still lacking. In this work, both the compositional and functional responses to typical CADs of five vegetation types were assessed in 48 plots, located around the city of Genoa (Italy). The main anthropogenic and environmental drivers of species composition were identified through a Non-Metric Multidimensional Scaling, and selected variables were used to fit a partial Redundancy Analysis. Differences in the number of alien species in relation to total CAD intensity were assessed with a Kruskal-Wallis test. Regarding functional composition, the community weighted mean values (CWMs) of five functional traits were computed for each plot. Generalized linear models were then fitted to assess the relationship between the CWMs and CADs intensity. Our results showed that the specific composition of peri-urban plant communities of Genoa is shaped by interacting environmental and anthropogenic factors. Considering composition, CADs promote the increase of alien species’ number. Moreover, the increased intensity of CADs altered the functional composition, with increasing specific leaf area, leaf nitrogen content and seed bank longevity. Overall, the effect of typical Mediterranean CADs is more pronounced on the functional composition than on the taxonomic composition of peri-urban plant communities. This work highlights the relevance at the local scale of the typical CADs of the Mediterranean area in influencing the different vegetation types that characterise a peri-urban zone.

Unveiling the Impact of Urbanization on Net Primary Productivity: Insights from the Yangtze River Delta Urban Agglomeration

Urbanization has significantly altered the carbon cycle of the terrestrial environment, particularly in relation to net primary productivity (NPP). Gaining a more comprehensive comprehension of how NPP is affected by urbanization is crucial for obtaining fresh perspectives on sustainable urban landscape design and decision making. While there is a significant body of research examining the geographical and temporal patterns of NPP supply capacity, there are only a few studies that have investigated the spatial relationships between NPP and urbanization, particularly at the grid scale. This research investigated the temporal and geographical features and patterns of NPP and their impact mechanisms. In order to estimate NPP and the level of urbanization in the Yangtze River Delta Urban Agglomeration (YRDUA), we used a combination of different models and datasets. To evaluate the geographical correlations and dependence between NPP and urbanization, we utilized local bivariate autocorrelation methods and spatial regression models to describe and visualize these relationships. The findings revealed that there was a consistent negative relationship between NPP and urbanization on a global scale from 1990 to 2020. However, when examining the local scale, the geographical correlations could be classified into four distinct categories: areas with both low NPP and low urbanization, areas with high NPP and high urbanization, areas with low NPP and high urbanization, and areas with high NPP and low urbanization. Our analysis showed that spatial regression models are more suitable for quantifying the spatial relationship between NPP and urbanization due to their ability to include the impacts of spatial Moran’s I techniques. Due to the growing urbanization, the highest NPP value was recorded in 2005, followed by 2000, 2020, and 2010. Conversely, the smallest association was observed in 2015. Examining the geographical connection between NPP and urbanization offers theoretical and practical insights for urban planning that prioritizes human needs and promotes sustainable development. It also aids in the development of reasonable methods for organizing ecological functional systems.

Where the not-so-wild things are in cities? The influence of social-ecological factors in urban trees at multiple scales

Green infrastructure plays an essential role in cities due to the ecosystem services it provides. However, these elements are shaped by social and ecological factors that influence their distribution and diversity, affecting ecological functions and human well-being. Here, we analyzed neighborhood tree distribution - trees in pocket parks, squares and along streets – in Lisbon (Portugal) and modelled tree abundance and taxonomic and functional diversity, at the parish and local scales, considering a comprehensive list of social and ecological factors. For the functional analyses, we included functional traits linked to dispersal, resilience to important perturbations in coastal Mediterranean cities, and ecosystem services delivery. Our results show not only that trees are unevenly distributed across the city, but that there is a strong influence of social factors on all biological indices considered. At the parish and local scales, abundance and diversity responded to different factors, with abundance being linked to both social and ecological variables. Although the influence of social factors on urban trees can be expected, by modelling their influence we can quantify how much humans modify urban landscapes at a structural and functional level. These associations can underlie potential biodiversity filters and should be analyzed over time to inform decisions that support long-term ecological resilience, maximize trait functional expression, and increase equity in ecosystem services delivery.

Setting up a CFD model to evaluate the impact of green infrastructures on local air quality

AbstractGreen infrastructures have been pointed out as innovative solutions to deal with current and future challenges related to air pollution and climate change. Although the potential of green infrastructures, such as green walls and green roofs, to mitigate air pollution has been documented, evidence at a local scale is still limited. This work aims to increase knowledge about the potentialities of green infrastructures in improving local air quality, focusing on particulate matter, nitrogen dioxide and ozone pollutants, and by using a local-scale computational fluid dynamics model. The ENVI-met model was applied to a particular hour of a summer day over a built-up environment centred on a main avenue in the city of Lisbon (Portugal). The dimensions of the computational domain are 618 m × 594 m × 143 m, and it contains 184 buildings, with the tallest building being 56 m. In addition to the baseline simulation, modelling was also done considering the application of green walls and green roofs to specific buildings located near the main avenue, together with a green corridor. The overall results show no disturbances exerted by green walls on the turbulent flow dynamics and on the air quality levels when compared to the baseline scenario (without green walls). The integrated scenario, which includes green walls, green roofs and a green corridor, will lead to potential local benefits of green infrastructures on O3 concentrations, followed by variable impacts on NO2 and particulate matter concentrations.

Manifold regularized deep canonical variate analysis with interpretable attribute guidance for three-phase flow process monitoring

Oil–gas–water three-phase flow has multiple flow states, exhibiting dynamic, nonlinear, and instantaneous behaviors. Monitoring and analysis of flow state are crucial for ensuring safe operation of industrial processes. However, the absence of a universal definition for three-phase flow states, owing to the complex flow characteristics and structures, leads to that labeling three-phase flow states by categories is impractical. For comprehensive monitoring and analysis, the flow states should be described from both global (e.g., the dominant phase) and local (e.g., the interphase structure) aspects. Given the aforementioned challenges, the work aims to address the accurate identification of typical three-phase flow states and to meticulously monitor and analyze the continuous evolutionary process of three-phase flow. To achieve it, the manifold regularized deep canonical variate analysis with attribute guidance (Ag-MRDCVA) is proposed, which not only introduces an innovative monitoring paradigm that designs state attributes for process description but also facilitates knowledge transfer from typical flow states to transition states. For enhancing the model’s feature embedding capabilities, an attribute guidance module is introduced to increase supervision information at both class and attribute levels. Then, convolutional neural network (CNN) backbones are developed with a dual objective of global serial correlation and local manifold regularization, which capture spatiotemporal information at both global and local scales, facilitating effective attribute encoding and characterization of flow states. Finally, the attribute evolution heat map and a monitoring metric (MM) collectively offer a compelling and comprehensive analysis of the three-phase flow process. Extensive experiments demonstrate that Ag-MRDCVA surpasses existing methods, showcasing its ability to minutely monitor the process while providing reasonable explanations.

RADReef: A global Holocene Reef Rate of Accretion Dataset

Reef cores are a powerful tool for investigating temporal changes in reef communities. Radiometric dating facilitates the determination of vertical accretion rates, which has allowed for examination of local-regional controlling factors, such as subsidence and sea level changes. Coral reefs must grow at sufficient rates to keep up with sea level rise, or risk ‘drowning.’ As sea level is expected to rise significantly in the next 100 years and beyond, it is important to understand whether reefs will be able to survive. Historical records of reef accretion rates extracted from cores provide valuable insights into extrinsic controlling factors of reef growth and are instrumental in helping predict if future reefs can accrete at rates needed to overcome predicted sea level changes. While extensive research exists at local and regional scales, limited attention has been given to identifying global patterns and drivers. To address this, we present “RADReef”: A global dataset of dated Holocene reef cores. RADReef serves as a foundation for further research on past, present and future reef accretion.

Evaluating seawater intrusion forecast uncertainty under climate change in the Pajaro Valley, California

Climate change and climate variability impacts such as rising sea levels have the potential to exacerbate seawater intrusion and the strain on coastal freshwater resources in already stressed groundwater basins such as those in the Pajaro Valley groundwater basin, California. Regional hydrologic models are often coupled with climate projections to forecast future hydrologic conditions and inform adaptive resources management strategies. However, there is high uncertainty in the future projections of water resources due to uncertainties from downscaling global general circulation models (GCMs) to local scale climate change projections, future land use changes, and the inherent uncertainty of developed hydrologic models. Future climate projections and the magnitude of their influence on modeled hydrologic drivers are highly variable. Therefore, to develop a forecast model, an ensemble of different projections can be used to capture a wider range of basin responses and the associated uncertainties in the modeled forecasts. Understanding the reliability and uncertainty of forecasts is important for developing climate adaptation strategies such as developing protective thresholds, particularly at the basin scale where the impacts are felt, and adaptation is implemented. To demonstrate this, an uncertainty analysis of groundwater level and seawater intrusion forecasts for the Pajaro Valley groundwater basin was performed using an ensemble of three future climate projections with the Pajaro Valley Integrated Hydrologic Model (PVIHM) and the first-order second moment (FOSM) method. FOSM uncertainty analysis of hydrologic forecasts across a multi-GCM climate ensemble provides an upper and lower bound of potential impacts of climate change on sustainability targets related to mitigating seawater intrusion. The groundwater level forecasts’ narrow range of variability can help policymakers in adaptation planning by constraining possible outcomes to a focused range for risk-management decisions. However, less than one-third of groundwater level forecasts met the current protection thresholds to prevent chronic lowering of groundwater. Therefore, sustainability targets may need to be reassessed. Relative to groundwater level changes, the seawater intrusion forecasts had larger uncertainty due to the GCM climate projections and the simulated hydrologic response that were compounded by the propagation of scaling and bias from the GCMs and model simplifications in simulating the coastal boundary.

A multi-source proxies approach to identifying local processes in lower Permian black shale impacting on the sedimentary environment of eastern Palaeo-Tethys Ocean

Foreland basin tectonics along the eastern Palaeo-Tethys Ocean produced a complex and dynamic pattern of sediment delivery to adjacent basins. Environmental processes at the local scale significantly disrupt regional ones, making the analysis of sedimentary evolution difficult. This study investigated the Lower Permian Liangshan Formation black shale formed in such geological setting, rich in cherts with exceptionally high silica and fluctuating major and trace element concentrations, detected using XRD, XRF, and ICP-MS techniques. Different types of silica, including detrital quartz, recrystallised radiolaria, microcrystalline quartz, and quartz veins, were identified using SEM and SEM-CL imaging. Geochemical characterisation and enrichment pattern analyses indicated that the structural setting was characterised by proximity to the oceanic island arc, continental island arc, and passive margin, and the major zone of sediment accumulation was a semi-restricted back-arc basin under the subduction zone. The processes controlling sediment accumulation included hydrothermal activity, upwelling, biogenic silica, and terrestrial inputs. Although upwelling interfered with the mobility and migration of hydrothermal elements, it introduced abundant nutrients, and together with hydrothermal fluids, it contributed to the subsequent boom in siliceous organisms. Terrigenous inputs induced by land uplift significantly diluted the components from other sources. This multi-source proxies approach not only enables researchers to disentangle local from regional processes but also sheds light on how these diverse environmental forces interact within intricate earth systems, which enhance our comprehension of geologic history and inform ongoing studies focused on climate change mitigation strategies.

Evaluation of streamflow predictions from LSTM models in water- and energy-limited regions in the United States

The application of Long Short-Term Memory (LSTM) models for streamflow predictions has been an area of rapid development, supported by advancements in computing technology, increasing availability of spatiotemporal data, and availability of historical data that allows for training data-driven LSTM models. Several studies have focused on improving the performance of LSTM models; however, few studies have assessed the applicability of these LSTM models across different hydroclimate regions. This study investigated the single-basin trained local (one model for each basin), multi-basin trained regional (one model for one region), and grand (one model for several regions) models for predicting daily streamflow in water-limited Great Basin (18 basins) and energy-limited New England (27 basins) regions in the United States using the CAMELS (Catchment Attributes and Meteorology for Large-sample Studies) data set. The results show a general pattern of higher accuracy in daily streamflow predictions from the regional model when compared to local or grand models for most basins in the New England region. For the Great Basin region, local models provided smaller errors for most basins and substantially lower for those basins with relatively larger errors from the regional and grand models. The evaluation of one-layer and three-layer LSTM network architectures trained with 1-day lag information indicates that the addition of model complexity by increasing the number of layers may not necessarily increase the model skill for improving streamflow predictions. Findings from our study highlight the strengths and limitations of LSTM models across contrasting hydroclimate regions in the United States, which could be useful for local and regional scale decisions using standalone or potential integration of data-driven LSTM models with physics-based hydrological models.

Design and application of coastal erosion indicators using satellite and drone data for a regional monitoring program

Coastal erosion is a complex issue that affects landforms at various spatio-temporal scales, with concerns rising due to the impending threats of climate change. Given the increasing availability of coastal shoreline data, we identify a gap in present coastal management methods: the need for a simple and cost-effective mechanism to track and compare shoreline trends, to inform high-level reporting, down to local management scales. This study introduces simplified, automated erosion indicators, demonstrated for 20 morphologically diverse beach sites across the temperate coast of Victoria, Australia. The methods utilise coastal drone surveys (2018–2023; 560 surveys) and satellite-derived shorelines (Digital Earth Australia Coastlines, 1988 to 2021). Two tools are introduced: (1) the Erosion Warning Indicator, for high-level reporting, reducing multiple aspects of shoreline change (long-term vs. short-term; widespread vs. hotspot) to a simplified scoring system allowing overall site assessment and comparison across sites; and (2) the Erosion Hotspot Detector, to aid local managers to automatically identify and analyse emerging erosion areas. Results for a 2-year period (2021-22) indicate one site with a high erosion warning level, and four sites with a moderate level. Tracking the indicator over time (2018–2022) identifies two sites with persistently high erosion warning levels (Apollo Bay and Marengo). Importantly, the indicators also highlight areas where recent erosion trends differ from longer-term patterns (e.g., Inverloch), allowing re-evaluation of short-term expenditure on management interventions, without impacting longer-term adaptation pathways. The erosion indicators presented here hold value for coastal managers in many parts of the world. If comparable approaches are introduced and shared at scale, we will collectively be better equipped and informed to respond to future challenges to our coastlines.

Tidally driven porewater exchange and diel cycles control CO2 fluxes in mangroves on local and global scales

Mangrove soils are highly enriched in organic carbon. Tidal pumping drives seawater and oxygen into mangrove soils during flood tide and releases carbon-rich porewater during ebb tides. Here, we resolve semi-diurnal (flood/ebb tides), diel (day/night) and weekly (neap/spring tides) drivers of porewater-derived CO2 fluxes in two mangroves and update global estimates of CO2 emissions building on earlier observations from other sites. Tidal pumping controlled pCO2 variability within the two mangrove creeks. The highest values of pCO2 (2,585–6,856 µatm) and 222Rn (2,315–6,159 dpm m−3) and lowest values of pH (6.8–7.1) and dissolved oxygen (1.7–3.7 mg L−1) at low tides were due to enhanced porewater export. 222Rn and pCO2 in mangrove porewater were 4–15 and 38–41 times greater than surface waters, respectively. pCO2 increased by 50 ± 30 % from high to low tide, 9 ± 22 % from day to night and 57 ± 5 % from neap to spring tide with clear changes in hourly, diel, and weekly time scales. Combining our new estimates with literature data, global porewater-derived (16 sites) and water-atmosphere (52 sites) CO2 fluxes in mangroves would upscale to 45 ± 12 and 41 ± 10 Tg C y−1, respectively. These fluxes represent 25 % of net primary production and are twice as high as the sediment carbon burial rates in global mangroves. Overall, our local observations and global compilation suggest that porewater-derived CO2 exchange is a major but often unaccounted source of CO2 in mangroves. The porewater-derived CO2 can be emitted to the atmosphere or laterally exported to the ocean and should be included in carbon budgets to solve global imbalances.

Planning for Deer-Hunting Management at the Local and Regional Scales: Reconciling Economic, Social and Ecological Functions

Game species with home ranges exceeding the area of the management units may entail conflicts over hunting rights and cause damage to crops and forest stands in surrounding areas. This is currently the case in the Mendro Mountain Range (Portugal), inhabited by free-ranging red (Cervus elaphus) and fallow deer (Dama dama) populations. This study’s primary goal was to uncover the processes underlying these tensions and identify solutions to overcome them, thus reconciling the economic, social, and ecological functions of hunting. We analyzed data from three different sources of information regarding the surveyed management units: biophysical and anthropical spatial data collected using a GIS; typology, whether fenced, area and game bag results, data provided by a public institute; crop and forest damage locations reported by game managers. Approximately half of the surveyed open management units reported damage. We found no relationship between damage and game bag results, regardless of the typology and habitat quality index. To address this disconnection between the negative and positive values associated with deer locally, we proposed habitat management solutions. It is of chief importance to keep valuable crops apart from deer’s refuge cover, such as bushy areas, to minimize damage in management units where deer hunting is a subsidiary activity. Conversely, in management units where deer hunting is of significant economic importance, the food and refuge cover should be closely interspersed to increase the management unit’s carrying capacity. To improve the efficacy of measures such as this at a regional scale, as in the Mendro Mountain Range, we recommend implementing a so-called Global Management Plan. In Portuguese law, this governance instrument applies to the entire biologic unit where the deer populations occur, thus implying arrangements between the involved stakeholders and multiple other concerned institutions.

Estimating risk to prevent damage: predicting and preventing coypu (Myocastor coypus) damage to transport infrastructure.

A major impact of invasive Myocastor coypus in their introduction range is the collapse of riverbanks and nearby infrastructure, such as railway lines, due to the species' burrowing activities. Because widespread implementation of preventive measures along watercourses is unfeasible, identifying susceptible areas is key to guide targeted management actions. This study used species-habitat models to: (i) identify local environmental features of the railway line/watercourse intersections (RLWIs) that make them particularly susceptible to coypu damage, and (ii) predict species occurrence probability over a wide lowland-hilly area of northern Italy (Lombardy) to identify priority areas for monitoring. Local-scale models identified that the RLWIs most susceptible to burrowing were those surrounded by arable land with interspersed hedgerows locally characterized by high herbaceous vegetation and clay soil. In urbanized areas and areas of intensive agriculture, coypu dens were generally located significantly closer to the railway, increasing the risk of collapse. A landscape-scale species distribution model showed that lowland areas along major rivers and lake shores, and also agricultural areas with a dense minor hydrographic network, particularly in the southeast of the study area, are more likely to be occupied by coypu. Local-scale models showed that specific environmental characteristics increase the risk of burrowing near RLWIs. The landscape-scale model allowed us to predict which areas require thorough monitoring of RLWIs to search for such local characteristics to implement preventive management measures. The proposed model-based framework can be applied to any geographical context to predict and prevent coypu damage. © 2024 Society of Chemical Industry.

A comprehensive multi-fidelity surrogate framework based on Gaussian process for datasets with heterogeneous responses

In recent decades, the multi-fidelity (MF) surrogate framework has seen widespread application across various scenarios. This framework significantly enhances the efficiency of surrogate modeling by integrating data of varying fidelity levels. However, research on the MF surrogate has predominantly focused on regression settings, aiming at approximating continuous responses, with limited attention to classification problems involving discrete responses. Moreover, no existing studies have addressed a heterogeneous MF dataset, where the data types (continuous or discrete) vary between different fidelities. This paper introduces a comprehensive MF surrogate framework based on Gaussian process, designed to handle a wide range of MF dataset types. Our framework employs a hierarchical Kriging scheme and Bayesian inference, adaptable to any MF dataset type. Given the challenges posed by discrete data in analytical inference, we incorporate the Laplace approximation for the latent function associated with discrete data in our framework. Additionally, we introduce a local scaling factor specifically for low-correlation classification problems in MF settings. The superiority of our method over conventional ones is demonstrated through both synthetic and engineering examples. Notably, in an engineering example featuring a heterogeneous MF dataset, our proposed MF surrogate model achieves an error reduction exceeding 50%.

Multi-scale effects of behavioral movement deterrents on invasive carp metapopulations

Behavioral deterrents of among-pool movement represent a promising tool for controlling invasive fish populations. To date, much of the research in this area has been focused on the direct effectiveness of different methods of deterrence. However, the effect of these structures on populations in spatially complex habitats is unknown. We combine a metacommunity model with movement data of two invasive species (bighead carp and silver carp) in a large river to assess local and river-wide scale population outcomes of deterrent locations. We calculated (1) which potential deterrent locations are most effective at reducing the growth at the invasion front (2) the river-scale population effects at each location, and (3) what, if any, are the risks imposed by altering the current spatial dynamics. We found that the effects on the population dynamics at the invasion front varied with the location of deterrents, ranging from near zero to effects equal to the reduction in an individual’s movement across the deterrent. The river-scale population growth rate was slightly increased by all potential deterrent placements because the deterrents tended to concentrate more of the river-scale population into pools with the highest recruitment rates. The short-term, transient dynamics followed a strictly decreasing pattern after deterrent placement suggesting no additional short-term risk. These results suggest that deterrents can be an effective and low-risk intervention for the control of invasive carp, although the population level effect will depend on the interaction of the traits and behavior of the species with the physical character and spatial structure of the habitat.

Crayfish communities converge over succession in beaver pond metacommunities

Abstract Metacommunity theory predicts that the relative importance of regional and local processes structuring communities will change over ecological succession. Determining effects of these processes on taxonomic and evolutionary diversity in spatially structured freshwater habitats of different successional stages may greatly improve understanding of the maintenance of diversity across temporal and spatial scales. In this study, we evaluated crayfish diversity at local and regional scales in pond metacommunities undergoing secondary succession from beaver (Castor canadensis) disturbance. Following theoretical predictions from metacommunity ecology of the increasing importance of local processes over succession, we hypothesised a decline in crayfish local and β diversity over succession from stronger local structuring as the older ponds may provide less suitable habitat than streams. Crayfish species and phylogenetic diversity were evaluated in beaver pond metacommunities and reference headwater streams located in three catchment regions. DNA sequences from the mitochondrial cytochrome oxidase I gene were used to assign crayfish to species for community and phylogenetic diversity tests. Local and β diversity were contrasted across beaver ponds ranging in age from 24 to 70 years and as a function of metacommunity processes. Counter to predictions, local species diversity among streams and the successional stages of ponds categorised by age class (24–39 years; 42–57 years; 60–70 years) did not differ, but community and phylogenetic convergence occurred in the oldest pond ecosystems. Crayfish community composition differed between the youngest and oldest ponds, resulting from higher abundance in the youngest ponds and community convergence in the oldest ponds. The association between community composition and the environment was strongest in streams and decoupled with pond age. In contrast, the correlation between intraspecific haplotype composition and the environment increased over succession. Among the three metacommunities, the regional crayfish species diversity arose from a combination of the temporal and environmental drivers from beaver‐constructed ecosystems and dispersal limitation within catchments. This study represents the first investigation of the taxonomic and phylogenetic diversity response to the successional stages of beaver pond metacommunities. The detection of differential crayfish composition and haplotype sorting to pond age suggests a role for local structuring and further indicates that future studies should acknowledge succession in shaping species diversity at local and regional scales. Dispersal limitation within catchment regions probably contributes to the evolution of crayfish species diversity in metacommunities and the overall maintenance of biodiversity. The results support a transition in community and freshwater ecology from a recent emphasis on spatial processes towards the integration of temporal drivers to better identify regulators of taxonomic and phylogenetic diversity across scales.

Dam the river: Ontological exclusion in global and Brazilian Integrated Water Resources Management

Integrated Water Resource Management (IWRM) has been widely adopted as a norm that promises to increase equality and sustainability of water governance through participatory decision-making. After decades of policy implementation, however, inequalities in outcomes and large-scale water-related disasters raise questions about the ability of IWRM to deliver on its promises. This article explores these questions by putting the history of IWRM at the global scale in conversation with the national scale of water governance in Brazil and the local scale of the Rio Doce, the site of the largest single environmental disaster in Brazilian history. This conversation highlights truncated practices of inclusion in which participation of diverse actors is possible only within an account of water as a resource system. Mobilizing recent debates about the Ontological Turn in social sciences and humanities, we argue that the appeal to inclusion in IWRM masks ontological exclusion in which participation is dependent on an ontology of water as a resource system. The case of the Rio Doce shows how promises of equality and sustainability through inclusion fail in the light of rendering local ontologies invisible or illegitimate for governance. In framing IWRM as a site of ontological inequality, groundwork is laid for a renewed promise of participation.

Broad, strong, and soft: Using geospatial analysis to understand folk-linguistic terminology

Abstract This study uses a modified online version of the “draw-a-map” task and Garrett, Williams, and Evans’ (2005b) “keywords” methodology to explore the geospatial distribution of different accent and dialect labels and descriptors in Greater Manchester, UK. Specifically, we consider the distribution of the three most frequent labels related to “accentedness”: Broad, Strong, and Soft, as provided by 349 Greater Manchester residents. This analysis finds that these descriptors were clustered in separate areas of Greater Manchester, suggesting that they were being used to describe perceptually distinct varieties of English. In order to uncover the nuances in these folk-linguistic terms, we consider how they correlate with other concepts emerging from the dataset, finding that they are being used to differentiate between varieties with contrasting social associations. By combining innovative approaches, this study demonstrates how the subtleties of folk-linguistic modes of awareness can be uncovered through in-depth analysis of the terminology employed to describe linguistic variation on a very local scale. In so doing, it paves the way for further development of draw-a-map techniques that will enable similarly nuanced analysis in different regions, thus pushing the sub-discipline forward.

Influence of habitat features on the colonisation of native and non-indigenous species

Marine artificial structures provide substrates on which organisms can settle and grow. These structures facilitate establishment and spread of non-indigenous species, in part due to their distinct physical features (substrate material, movement, orientation) compared to natural habitat analogues such as rocky shores, and because following construction, they have abundant resources (space) for species to colonise. Despite the perceived importance of these habitat features, few studies have directly compared distributions of native and non-indigenous species or considered how functional identity and associated environmental preferences drive associations. We undertook a meta-analysis to investigate whether colonisation of native and non-indigenous species varies between artificial structures with features most closely resembling natural habitats (natural substrates, fixed structures, surfaces oriented upwards) and those least resembling natural habitats (artificial materials, floating structures, downfacing or vertical surfaces), or whether functional identity is the primary driver of differences. Analyses were done at global and more local (SE Australia) scales to investigate if patterns held regardless of scale. Our results suggest that functional group (i.e., algae, ascidians. barnacles, bryozoans, polychaetes) rather than species classification (i.e., native or non-indigenous) are the main drivers of differences in communities between different types of artificial structures. Specifically, there were differences in the abundance of ascidians, barnacles, and polychaetes between (1) upfacing and downfacing/vertical surfaces, and (2) floating and fixed substrates. When differences were detected, taxa were most abundant on features least resembling natural habitats. Results varied between global and SE Australian analyses, potentially due to reduced variability across studies in the SE Australian dataset. Thus, the functional group and associated preferences of the highest threat NIS in the area should be considered in design strategies (e.g., ecological engineering) to limit their establishment on newly built infrastructure.