Regional Scale Research Articles

Predicting and Mapping the Phosphorus Adsorption Maximum and Phosphorus Adsorption Affinity Constant at Regional Scale

ABSTRACTInsight into the variation of the soil phosphorus (P) adsorption maximum (Qmax) and the P adsorption affinity constant (KL) is crucial for accurately assessing the dynamics of P availability, P uptake and P leaching in agricultural systems at regional scale. Data on the variation in soil P adsorption characteristics, derived from traditional batch experiments, combined with data on soil properties affecting them, such as pH, clay and organic matter content, can be used to assess the influence of soil properties on P adsorption characteristics. However, current studies are limited to explaining the variation in Qmax using linear models, focusing on either noncalcareous or calcareous soils. This study aims to (1) identify the soil properties governing both Qmax and KL for a combination of noncalcareous and calcareous soils, including nonlinear and interaction effects; and (2) create spatial maps depicting the variations in both soil P adsorption characteristics at the regional scale (two typical Chinese counties). We leveraged 83 data points of both Qmax and KL from 16 publications with main soil properties affecting P adsorption, that is, pH and the content of soil organic matter (SOM), clay and oxalate extractable Fe and Al (FeOX and AlOX), to develop predictive models for soil P adsorption. General linear regression (GLM) and extreme gradient boosting (XGB) models were used to unravel the relationships between soil properties and P adsorption characteristics. The XGB model outperformed GLM model, explaining more than 80% of the variations in both Qmax and KL in noncalcareous and calcareous soils, while the GLM model explained 52% for Qmax and only 21% for KL. Key drivers influencing Qmax were found to be FeOX, AlOX and pH, while clay and pH played significant roles in explaining the variability in KL. When applying these models at the county level using county‐level inventory data, noncalcareous soils generally exhibited higher P sorption capacity and binding energy than calcareous soils. To enhance the accuracy of soil P sorption predictions and guide sustainable P fertiliser use, regional mapping of FeOX and AlOX content is essential.

Multi-criteria decision analysis for monitoring and evaluating soil erosion risk in forest fire-affected areas.

Wildfires lead to socio-economic and environmental impacts. These impacts include hydrological instability, which can cause severe damage, especially where infrastructures are present. Post-rehabilitation measures can be useful in reducing or preventing erosion or hydrogeological risks. Decision-makers are called on to prioritize post-fire intervention areas and allocate public funds for this purpose. This work focuses on the assessment of erosion and hydrological risk potential in forested slope areas affected by wildfire using a Multi-Criteria Decision Analysis (MCDA) approach integrated with a GIS environment on a regional scale. Expert perception was considered using the pairwise comparison method as part of the Analytical Hierarchy Process (AHP). This allows expert stakeholders to rank relevant criteria, providing a quantitative metric (weight) for qualitative data. Two MCDA methods are used and compared: Weighted Linear Combination (WLC) and Ordered Weighted Averaging (OWA). Fire frequency, slope (gradient and length), and proximity to infrastructures were found to be the most important factors by the stakeholders. The WLC method provides evidence classified into high and moderate suitability class areas characterized by high values for fire frequency or slope gradient. Conversely, the OWA method, ranging from low to high risks, makes it possible to adapt the method and obtain a range of suitability maps. Novelties of the MCDA-GIS combined methodology adopted in this work are its application on a regional scale and the combination of vulnerability and driving-force factors (namely presence of grey infrastructures, fire frequency). The MCDA-GIS methodology can be suitable for public administrations in that it allows for mapping a regional area more quickly and thus facilitates sector planning.

The impact of the AMO on wintertime surface wind speed reversal in Northeast Asia

Abstract Decadal variations in seasonal mean surface wind speed (SWS) and their underlying causes remain elusive. Here, we utilize wind data from in situ stations to demonstrate that the stilling reversed around 2002 and that wintertime wind speed in Northeast Asia has rebounded. We illustrate that decadal-scale variations of SWS are closely linked to the phase shift of the Atlantic Multidecadal Oscillation (AMO). Specifically, an AMO positive phase generates a wave train characterized by a cyclonic anomaly over Northeast Asia, which leads to the strengthened westerly wind, enhanced meridional temperature gradient, and increased transient eddy activities in Northeast Asia. These findings hold vital implications for considering changes in the AMO to gain a comprehensive understanding of SWS variations at the regional scale.

Evaluating and Improving the Connectivity of China's Protected Area Networks for Facilitating Species Range Shifts under Climate Change

Contemporary climate change is causing spatial redistributions of many species, potentially undermining the effectiveness of existing protected areas (PAs). This raises concerns about whether current PAs are connected enough to capture climate-induced range shifts and how to expand PAs to support this ecological process. Hence, we conducted a national-scale assessment of climate connectivity for the terrestrial PAs across mainland China. We found that most PAs are structurally connected to cool ones through low human impact (LHI) areas along temperature gradients. The connected PA networks could enable species to migrate and avoid an average climate warming of 2.9°C under moderate emission scenario. Nevertheless, less than half (46.2%) of the PAs have achieved successful climate connectivity. To facilitate climate-induced range shifts, we identified priority areas for conservation based on their importance in supporting connections between PAs. Our study provides spatially explicit assessments of the connectivity of PA networks for range shifts and emphasizes the necessity to consider climate connectivity in the planning of PAs at regional scales.

Twenty-five years on: Widespread kelp forest decline revealed in a potential climatic refugium.

Kelp forests are key temperate ecosystems that experience the combined effects of global and local stressors throughout their distribution range. Niche modelling projections identified NW Spain, a region influenced by an intense upwelling system, as one such potential refugium. However, the recent discovery that fish overgrazing has eradicated kelp forests from certain reefs calls into question the validity of these projections. To determine the actual persistence of kelp forests (Laminaria ochroleuca and Laminaria hyperborea) on a regional scale, we resurveyed 50 sites in 2023 where kelp forests had been recorded up to 25 years earlier. Kelp had either disappeared or been reduced to a few scattered individuals at two-thirds (58%) of the sites. Furthermore, where kelp forests persist, L. ochroleuca is now the dominant canopy-forming kelp, while L. hyperborea has only been recorded at two sites. Kelp forest persistence was negatively correlated with summer sea surface temperature and wave exposure. Altogether, our results indicate that kelp forest decline is widespread in NW Spain, challenging the view of this region as a climate refugium and underscoring the difficulty of accurately predicting the trajectory of such complex and fragile ecosystems. Furthermore, in line with the recommendations of the OSPAR Convention, this study lays the foundation for a long-term monitoring network along a region where kelp forests are undergoing rapid change.

Projected Effects of Climate Change on Meteorological Droughts over China: A Study Based on High-Resolution NEX-GDDP Data

Abstract While historical observations reveal increases in meteorological drought frequency across China during 1960–2021, future drought characteristics at the regional scale are uncertain. We evaluate historic and twenty-first-century-projected dryness changes using the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) 0.25° resolution dataset for representative concentration pathways (RCPs) 4.5 and 8.5. The 20-model NEX-GDDP ensemble mean precipitation and derived potential evapotranspiration, which is calculated by utilizing the Thornthwaite approach, are consistent with gridded station data over China from 1961 to 2005. Results show that the projections of occurrence frequency of moderate drought based on the standardized precipitation evapotranspiration index (SPEI) increase remarkably under the RCP4.5 scenario, and a significant increasing frequency is seen for severe drought under the RCP8.5 scenario, while few droughts of extreme dryness occur during the twenty-first century under both emission scenarios. More moderate drought projections are found over northwestern, northern, and southeastern regions under the RCP4.5 scenario, but all of China will face severe droughts for RCP8.5. The areas affected by moderate droughts begin to extend rapidly around 2030s at both national and regional scales for the RCP4.5 scenario, and the substantial increases in drying area extension for RCP8.5 appear around the 2050s. Particularly, the severe drought areas are found to grow much more sharply after the 2070s under the RCP8.5 scenario, implying that the occurrences of severe droughts over China are more sensitive to greenhouse gas emissions. Significance Statement Both temperature and rainfall are closely associated with drought variability; therefore, this study examines the changes in frequency and intensity of projected droughts across China based on the standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI). Severe droughts are projected to increase over most of the regions according to SPEI. The substantial increases in moderate and severe droughts are seen over all of China under the RCP4.5 and RCP8.5 scenarios, respectively. At the temporal scale, most of the areas are projected to experience more severe droughts by the end of twenty-first century, while the areas of moderate droughts are projected to exhibit fluctuating variations during the twenty-first century. These results indicate more future droughts, which may increase the vulnerability of more areas of China from exposure to the consequences of global warming.

Estimation of All-Sky Gridded Diurnal Near-Surface Air Temperatures at Regional Scale From FY-4B Measurements

Estimation of All-Sky Gridded Diurnal Near-Surface Air Temperatures at Regional Scale From FY-4B Measurements

Local structural-functional coupling with counterfactual explanations for epilepsy prediction.

The structural-functional brain connections coupling (SC-FC coupling) describes the relationship between white matter structural connections (SC) and the corresponding functional activation or functional connections (FC). It has been widely used to identify brain disorders. However, the existing research on SC-FC coupling focuses on global and regional scales, and few studies have investigated the impact of brain disorders on this relationship from the perspective of multi-brain region cooperation (i.e., local scale). Here, we propose the local SC-FC coupling pattern for brain disorders prediction. Compared with previous methods, the proposed patterns quantify the relationship between SC and FC in terms of subgraphs rather than whole connections or single brain regions. Specifically, we first construct structural and functional connections using diffusion tensor imaging (DTI) and resting-state functional magnetic resonance imaging (rs-fMRI) data, subsequently organizing them into a multimodal brain network. Then, we extract subgraphs from these multimodal brain networks and select them based on their frequencies to generate local SC-FC coupling patterns. Finally, we employ these patterns to identify brain disorders while refining abnormal patterns to generate counterfactual explanations. Results on a real epilepsy dataset suggest that the proposed method not only outperforms existing methods in accuracy but also provides insights into the local SC-FC coupling pattern and their changes in brain disorders. Code available at https://github.com/UAIBC-Brain/Local-SC-FC-coupling-pattern.

Sources of PM2.5 exposure and health benefits of clean air actions in Shanghai.

Estimating PM2.5 exposure and its health impacts in cities involves large uncertainty due to the limitations of model resolutions. Consequently, attributing the sources of PM2.5-related health impacts at the city level remains challenging. We characterize the health impacts associated with chronic PM2.5 exposure and anthropogenic emissions in Shanghai using a chemical transport model (GEOS-Chem) and its adjoint. By incorporating high-resolution satellited-derived PM2.5 estimates into the calculation, we investigate the response of PM2.5 exposure and its related health impacts in Shanghai to changes in anthropogenic emissions from each individual region, species, sector, and month. We estimate that a 10% decrease in anthropogenic emissions throughout China avoids over 752 (506-1,044) PM2.5-related premature deaths in Shanghai, with changes in local emissions potentially saving 241 (161-334) lives. Ammonia (NH3) emissions are identified as the marginal dominant contributor to the health impacts due to the NH3-limited PM2.5 formation within the city, thus controlling NH3 emissions at both the local and regional scales are effective at reducing the population's exposure to PM2.5. A negative response of the PM2.5 exposure to local nitrogen oxides (NOx) emission changes is detected in winter. Even so, controlling NOx emissions is still justified since the negative impacts decrease as anthropogenic emissions decline and NOx emission reductions benefit the public health on average. The anthropogenic emission changes due to Clean Air Actions helped avoid 3,132 (2,108-4,346) PM2.5-related premature deaths in 2019 relative to 2013, most of which are associated with emission reductions in the agricultural and industrial sectors.

The Influence of Tropical Cyclones on Mixed-Population Flood Frequency Analysis

Abstract Floods induced by tropical cyclones (TCs) and their frequency analysis have received much attention at the regional scale, but little is known about the role of TCs in the mixed flood frequency analysis at the global scale, which is the key for hazard management. Here, we investigated the influence of TCs on the upper tail of flood frequency estimates using discharge observations at 3883 stations influenced by TCs alongside global discharge simulations from the second phase of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2a). Our results show that TC-induced floods in inland areas are not always found along the TC path but can be located about 1000 km ahead, which is linked to TC-induced predecessor rain events. Extreme floods associated with TCs are generally larger in coastal areas compared to those in inland areas, whereas TC-induced floods in some inland areas tend to be more extreme relative to their local flood magnitude. The flood peaks generated by TCs and other mechanisms compose a mixed population flood series. However, the largest flood peaks in coastal areas are usually affected by TCs. These large TC-induced flood peaks play an important role in making the upper tail of the flood frequency curve heavier. In regions affected by TCs, the flood magnitude with an n-yr return period is greater when estimated from TC-induced floods only. Therefore, regions (especially inland regions) should thoroughly consider the extremity of TC-induced flooding when improving hydraulic infrastructures to ensure a more conservative design, thereby enhancing the safety of these hydraulic projects. Significance Statement Tropical cyclones (TCs) are responsible for extreme floods in coastal and inland areas influenced by TCs, which may play an important role in the flood frequency analysis and flood risk management. In this study, we investigated how TCs affect the upper tail of flood frequency estimates at the global scale. We find that extreme floods associated with TCs are generally higher in coastal areas, whereas TC-induced floods in some inland areas tend to be more extreme relative to their regional flood magnitude. These anomalously large TC-induced flood peaks control the upper tail of the flood frequency curve in coastal and inland areas and make the upper tail heavier. Globally, the flood magnitude once in n years is generally greater, estimated from only TC-induced flood peaks than that estimated from all flood peaks. Therefore, regions (especially inland regions) should thoroughly consider the extremity of TC-induced flooding when improving hydraulic infrastructures to ensure a more conservative design, thereby enhancing the safety of these hydraulic projects.

Automatic landslide prioritization at regional scale through PS-InSAR cluster analysis and socio-economic impacts

The present study is part of an initiative to revise the PAI landslide inventories for post-seismic reconstruction in the Central Apennines (Italy), affected by the 2016-2017 seismic sequence. We introduce an innovative automated workflow for classifying and prioritizing landslide-prone areas using multi-sensor Persistent Scatterers (PS). This approach aims to support post-seismic reconstruction efforts by government institutions through a comprehensive and up-to-date ranking of landslides. The methodology integrates post-seismic multi-sensor interferometric datasets, advanced clustering techniques, and socio-economic factors to establish a standard procedure for monitoring hazardous areas and prioritizing resource allocation. Key findings demonstrate the efficacy of the method in identifying critical regions that require immediate intervention, thereby enhancing the effectiveness of field inspections and territorial planning activities. Our multi-sensor analysis reveals that approximately 6% of landslides are not detectable by interferometric technique, 45% show stability with no detected deformation via PS data, and 19% are accurately mapped with deformation confined within their boundaries. Notably,30% of analyzed landslides exhibit displacement beyond their mapped perimeters, indicating potential expansion or underestimation of their extent. The integration of data from multiple sources provides a more robust understanding of potential risks across the study area, promoting a structured approach to hazard management that ensures interventions are both scientifically grounded and economically justified.

Strategic analysis of avian conservation within key areas and key species - A case study of Baiyangdian, China.

Global climate change and extensive human activities are causing rapid transformations in natural ecosystems, leading to the rapid loss of suitable habitats for wildlife, which urgently requires measures to protect global biodiversity. In the past decade, China has invested heavily in ecological restoration, but current projects often do not prioritize biodiversity conservation. Therefore, developing systematic conservation strategies and using quantitative methods to identify conservation key areas and key species within a regional scale is of great importance for current ecological restoration. In this study, we focused on avian species, using an Ensemble Species Distribution Model to identify bird distribution hotspots and accordingly proposed conservation key areas in Baiyangdian. Additionally, the AHP-EWM-TOPSIS method and ENMTools were utilized to select flagship bird species with strong umbrella effects and to determine conservation key species. The results indicate that the Fuhe wetland, southwest of ZaoZaDian, central and northern of ShaoCheDian, northwest of Beitian Village and Datian Village, northern of XiaoBaiYangDian, and the Xiaoyihe wetland should be designated as the birdconservation key areas. The key birds should include Aythya baeri, Ardea alba, Phasianus colchicus, Falco tinnunculus, Upupa epops and Paradoxornis heudei, with higher priority given to A. baeri, A. alba, P. colchicus and F. tinnunculus. This study aims to provide a systematic framework for identifying conservation key areas and key species, facilitating the efficient use of public funding by local governments, and providing scientific guidance for conserving the bird diversity of Baiyangdian.

Biodiversity accounting on farms: Relating diversity of bird assemblages to ecosystem condition.

Natural capital accounting can help farmers and producers meet global demands to disclose supply chain impacts on biodiversity and to reverse biodiversity declines in farmland. To date, methods have been limited in their ability to reliably represent biodiversity, especially fauna, and are typically prepared at the regional scale, not at the farm scale - the scale at which many decisions that impact habitats for species are made. We surveyed birds at 1155 sites across 50 farms (total area=135,890ha) in south-eastern Australia to relate site-level species richness of groups of birds to spatially discrete ecosystem condition states that are based on the structure and composition of vegetation and to develop a framework for farm-scale biodiversity accounting. Site-level species richness of bird groups was strongly related to ecosystem states. Spatially explicit models enabled calculation of the proportion of a farm that provides high-quality habitat for each bird group. This metric represents farm-level diversity and can be used to quantify a farm's impact on biodiversity and contribution to biodiversity conservation. This approach could be applied to agriculture regions within Australia and could be replicated in agricultural landscapes around the world where it is possible to establish applicable state and transition models with a reliable 'best-on-offer' or 'reference' condition state. Farm-scale accounts that incorporate biodiversity provide a robust tool for strategic farm management, rigorous environmental reporting, greater traceability through supply chains, and improved access to global sustainability markets.

Spatial distribution and isotopic signatures of N and C in mosses across Europe.

The accumulation of nitrogen (N) in moss tissue has proven to be a reliable marker of increasing N deposition. However, this measurement does not offer additional data about the origin of pollution. In this respect, the analysis of the N isotopic ratios might be a helpful tool in providing supplementary information about the nature of the nitrogenous species in biomonitoring surveys. Furthermore, isotopic signatures have been extensively used in the study of N and carbon (C) biogeochemical cycles. The main purpose of this study was to determine N and C elemental contents and their stable isotopes in mosses to investigate atmospheric pollution patterns across Europe. We aimed at identifying the main N polluted areas and evaluating the potential use of isotopic signatures in the attribution of pollution sources at a regional scale. With these objectives in mind, >1300 samples from 15 countries from Europe, all of them participants of the ICP-Vegetation programme 2005-2006, were analyzed for their C and N contents and δ15N and δ13C. The results were compared to those derived from EMEP model, which provided modeled deposition and emission data, as well as to the predominant land uses at the sampling sites (based on CORINE Land Cover). This evaluation suggests that additional measurements of stable C and N isotopes in mosses could be a valuable tool in European environmental surveys. Such measurements not only provide useful information for identifying probable pollution sources but also enable the quantification of their contributions, serving as biological indicators of significant environmental processes. This study presents the first quantitative assessment of major atmospheric nitrogen (N) sources based on stable isotope analysis on a European scale, establishing a framework for evaluating historical changes in N across the region.

Decision analysis of Integrated Pest Management: A case study on invasive sea lamprey in the Great Lakes Basin.

Integrated Pest Management (IPM) provides a powerful framework for addressing threats to human well-being caused by nuisance species including invasives. We examined the hypothesis that adaptive management could erode barriers to IPM implementation by developing a decision-analytic adaptive management framework for invasive sea lamprey (Petromyzon marinus) IPM in the Laurentian Great Lakes of North America. The framework addressed objectives associated with coordinating multiple sea lamprey control actions at the regional scale and objectives associated with internal validity of control actions. We reduced the scope of possible management actions by orders of magnitude to the set of 6432 alternatives expected to be both socially acceptable and technically feasible. Using utility theory, we identified the management actions that optimized expected utility for all possible objective weighting schemes that considered tradeoffs between maximizing learning about control tactic efficacy and minimizing cost to the IPM program. Sensitivity analyses revealed that assumptions about the social acceptability of deploying electric weirs to control invasive sea lamprey influenced selection of the optimal control action, suggesting that resolving this source of uncertainty through iterative application of the framework may lead to improved sea lamprey control outcomes. Overall, we found that adaptive management enabled learning processes useful for overcoming barriers to IPM of invasive sea lamprey. It formalized learning about sea lamprey control tactic efficacy as an objective of the IPM institution, questioned previously held assumptions about what constitutes a viable control strategy, and enabled a management experiment with temporal and spatial replication.

Scale effects of supplementary nature reserves on biodiversity conservation in China's southern hilly region.

The Southern Hilly Region (SHR) of China plays a critical role in maintaining national ecological security and supporting global biodiversity. However, intensified human activities, such as urbanization and excessive land exploitation, have led to significant ecological degradation, posing threats to both local and global biodiversity. The current nature reserve system in SHR no longer meets the demands for local biodiversity conservation. To address these challenges, this study proposes a strategic framework aimed at enhancing biodiversity conservation in the SHR by establishing Supplementary Nature Reserves (SNRs). Using the Systematic Conservation Planning method, we identified 80 additional SNRs based on existing reserves, focusing on watersheds as the unit of analysis. We evaluated their conservation effectiveness at regional, watershed, and sub-watershed scales. The results indicate that while SNRs significantly improved habitat quality and reduced human impacts at local and smaller scales, their effectiveness varied across spatial scales. The study underscores the importance of multi-scale conservation planning and the need to integrate local and regional strategies to optimize biodiversity protection. These findings provide a foundation for policymakers to develop more targeted and effective conservation measures, ensuring the long-term sustainability of biodiversity in the SHR.

Global drought-flood abrupt alternation: Spatiotemporal patterns, drivers, and projections

<p>The spatiotemporal patterns and driving factors of drought-flood abrupt alternations (DFAA) have been investigated across several regional and watershed scales; however, comprehensive examination at the global scale is lacking. Here, we employed the long period drought-flood abrupt change index (LDFAI), derived from an ensemble of 40 output datasets from eight Coupled Model Intercomparison Project phase 6 (CMIP6) models, to assess the spatiotemporal patterns, drivers, and future projections of global DFAA. The results indicate that DFAA are influenced by various anthropogenic forcings, and greenhouse gas emissions exert the most significant impact. The changes in the intensity of global DFAA (1950–2014), attributed to natural forcing (NAT), anthropogenic aerosols (AER), and greenhouse gas (GHG) forcing, accounted for 5.65%, 14.57%, and 33.55%, respectively. The rates of change of the DFAA intensity under shared socioeconomic pathways (SSPs) from 2014 to <styled-content style-type="number">2100</styled-content> were estimated to be 21.73% (SSP1-2.6), 45.37% (SSP2-4.5), 63.1% (SSP3-7.0), and 69.51% (SSP5-8.5). This means that under high radiative forcing, the regional rivalry and fossil-fuel development models will lead to a significant increase in DFAA. These findings can aid in the development of global adaptive policies related to DFAA.</p>

Indirect Effects and Context Dependency in Stream Fish Invasions

ABSTRACTAimInvasion ecology is replete with a body of well‐supported yet contradictory evidence for numerous invasion hypotheses, likely as a result of context dependency. Context dependency in invasion studies can arise in two ways: (1) apparent, when results differ between studies solely due to methodical differences, or (2) mechanistic, when results truly differ due to ecological processes. One form of apparent context dependency occurs when causally linked factors associated with invasion success (hereafter, invasion drivers) either mask or enhance each other's effect on invasion success. Mechanistic context dependency can occur when regional scale processes modify the influence of local scale invasion processes. Together, apparent and mechanistic context dependency likely give rise to conflicting support between invasion hypotheses via confounding effects of causally related invasion drivers and region‐specific invasion processes.Location2339 stream segments in two ecoregions of the United States.MethodsUsing local scale stream fish community data for two distinct ecoregions, we constructed identical path models to estimate the direct and indirect effects of invasion drivers on nonnative richness. We chose one variable to index invasion drivers from each of the following categories: propagule pressure, natural abiotic, anthropogenic abiotic and biotic factors.ResultsWe found evidence of apparent context dependency through the presence of indirect effects, in which the effects of propagule pressure and biotic factors on nonnative richness were modulated by abiotic factors. The indirect effects of invasion drivers differed between both regions, providing evidence of mechanistic context dependency.Main ConclusionsApparent and mechanistic context dependency can lead to conflicting evidence between studies of invasion hypotheses. Accounting for indirect effects of invasion drivers is important in gaining a more general understanding of the invasion process. Furthermore, because indirect effects varied regionally, it is important to understand the large‐scale processes that contextualise local invasion processes.

Shallow landslide susceptibility map at a regional scale (Asturias, NW Spain). A heuristic-driven approach

ABSTRACT The study area (Asturias, NW Spain) is a mountainous region extending over 10,000 km2, where shallow landslides triggered after heavy rainfall episodes are very frequent and pose a major threat and hazard to infrastructure and human populations, causing frequenteconomic losses and damage. In this regard, Shallow Landslide Susceptibility Mapping (SLSM) represents a very powerful tool for managers and agencies dealing with landslide hazards and land planning. Here we produced an SLSM based on basic geological/geomorphological maps and a heuristic approach. The regional-scale model built here has a cell resolution of 50 m and combines bedrock geology, and surface deposits mapped at a1:25k scale together with a digital slope model. The resulting map was compared with two local inventories of landslides, giving a goodness of fit of 80 and 77.5%. To better understand the results, the erroneous data have been reviewed individually and the causes of error were analysed.

Reset or renaissance? An exploratory comparison of pre- and post-pandemic regional short-term rental markets in Australia

ABSTRACT Following nearly a decade of unabated growth in the digitally disruptive short-term rental (STR) sector, the onset of the COVID-19 pandemic in 2020 caused a relatively abrupt two-year industry contraction characterised by substantial reductions in participating properties and booking activities. Given the sudden opportunity to rethink how STR markets fit alongside more traditional accommodation arrangements, this unanticipated Black Swan event catalysed much debate about the role that STRs play, and how they are regulated and managed. As the STR market rebounds toward a ‘new normal’, a timely opportunity exists to understand and theorise how and where the industry evolves. In this paper, we apply regression modelling and descriptive statistics to compare STR property utilisation across four regional markets in Australia both before and after the pandemic. We observe a sharp reduction yet strong intensification in available properties after the COVID-19 pandemic, with 27% fewer properties that were booked 26% more often across the nation. This was led by a significant geographical shift from capital cities to high-amenity, tourist-focused regions. Our findings suggest that this pivot is driven by spatial market segmentation, in which urban STRs are operated professionally, whereas regional markets are distinguished by their amenity value, both at the regional and property scales. Combined, the results of this study point to a more professionalised STR hosting landscape in which properties are more intensively used. Any potential policy reform should consider this evolution in the STR accommodation sector.