Distributed Modeling Approach Research Articles

Comparing spatial distribution modelling of fisheries data with single-area or spatially-explicit integrated population models, a case study of toothfish in the Ross Sea region

Most models used for assessing the status of fish stocks and providing quantitative advice for fisheries management are not spatially explicit despite the well-known spatial heterogeneity of fish populations. Statistical spatial distribution modelling, which can derive spatially-resolved biomass from catch rates, is a method increasingly used to infer trends in population biomass, particularly where integrated population models are not available. Although the spatial distribution modelling tool VAST was developed to analyze survey data, such methods have also been used with fisheries-dependent catch and effort data, particularly when survey data are not available. We developed a statistical spatial distribution model for Antarctic toothfish (Dissostichus mawsoni) in the Ross Sea region of the Southern Ocean using the VAST (Vector Autoregressive Spatio-Temporal model) approach. We based the VAST model on catch-rate (catch per unit effort) data from the long-line fishery and compared the biomass time series obtained to that of existing single-area and spatially-explicit integrated population models which have also been developed for this population. The time series obtained from the statistical spatial distribution modelling approach was highly variable between years, inconsistent with constraints imposed on population dynamics by biological parameters, and substantially different from biomass trends obtained from the integrated models. Although it has been used successfully in other analyses, in this instance, the spatial distribution modelling could not overcome fine-scale spatial and vessel-based variability in fishery catch rates to estimate the underlying abundance of toothfish at the scale of the Ross Sea region measurable with the more-informed integrated models.

Integrative taxonomy delimits species within the Duranta sprucei complex

Species boundaries in the Duranta sprucei complex have been a taxonomic challenge, displaying complex patterns of variation in vegetative morphology. This complex includes plants distributed in the Neotropical Andes from Bolivia to Colombia and the mountains of Central America. Previous authors delimited taxa morphologically, and different criteria have been reflected in the recognition of a variable number of taxa. Lineage divergence forms a temporal process whence populations may diverge morphologically and/or ecologically, and this contingent property of taxa should provide the criteria necessary for species delimitation. To clarify the taxonomy of the Duranta sprucei complex, an integrative methodology based on a modified Population Aggregation Analysis and a Species Distribution Modelling approach was employed. Morphology was used to discriminate species with different predicted distributions that share environmental parameters. As a result, the complex is here circumscribed to include four previously recognized species, D. benthamii, D. costaricensis, D. penlandii and D. sprucei, one former variety elevated to the rank of species, D. espinosae, and a new species, D. dickinsonii, endemic to the Peruvian Yungas. One new synonym and a new combination are also herein presented.

Modeling the Red-shanked Douc (Pygathrix nemaeus) distribution in Vietnam using Maxent

The Red-shanked Douc (Pygathrix nemaeus) is the only douc species recorded in all three countries of Indochina. It is classified as Endangered by IUCN, and is believed to have experienced a major drop of more than 50% of its population over the last 40 years. The known distribution of main P. nemaeus populations in Vietnam ranges from Pu Mat National Park, Nghe An Province in the North to the Kon Ha Nung, Gia Lai Province in the South. In this study, we used Maxent, a species distribution modeling approach that is shown to a have high predictive power even with low number of occurrence records, to predict the current distribution of the Red-shanked Douc in Vietnam based on published records. The results show that P. nemaeus inhabits a region from Nghe An to Kon Tum Province, with areas from Ha Tinh, Quang Binh, Quang Tri, Thua Thien – Hue, Da Nang – Quang Nam Provinces exhibiting the highest potential. With all model parameters already listed here, studies in the future may incorporate more occurrence records to develop better models, or other environmental variables to assess the influence of different factors on the species distribution. The results also suggest that species distribution modeling, coupled with a carefully checked and filtered occurrence dataset, as well as species-specific model fine-tuning and evaluating, can help address many conservation issues in Vietnam.
 
 

Arctic Sensitivity? Suitable Habitat for Benthic Taxa Is Surprisingly Robust to Climate Change

Arctic marine ecosystems are often assumed to be highly vulnerable to ongoing climate change, and are expected to undergo significant shifts in structure and function. Community shifts in benthic fauna are likely to result from changes in key physico-chemical drivers, such as ocean warming, but there is little ecological data on most Arctic species to support any specific predictions as to how vulnerable they are, or how future communities may be structured. We used a species distribution modelling approach (MaxEnt) to project changes over the 21st century in suitable habitat area for different species of benthic fauna by combining presence observations from the OBIS database with environmental data from a coupled climate-ocean model (SINMOD). Projected mean % habitat losses over taxonomic groups were small (0-11%), and no significant differences were found between Arctic, boreal, or Arcto-boreal groups, or between calcifying and non-calcifying groups. However, suitable habitat area for 14 of 78 taxa were projected a change by over 20%, and several of these taxa are characteristic and/or habitat-forming fauna on some Arctic shelves, suggesting a potential for significant ecosystem impacts. These results highlight the weakness of general statements regarding vulnerability of taxa on biogeographic or presumed physiological grounds, and suggest that more basic biological data on Arctic taxa are needed for improved projections of ecosystem responses to climate change.Importantly, however, 14 of 78 taxa exhibited a predicted increase or decrease in suitable habitat of over 20%, and several of these taxa are characteristic and/or habitat-forming fauna on some Arctic shelves, suggesting a potential for significant ecosystem impacts. These results highlight the weakness of general statements regarding vulnerability of taxa on biogeographic or presumed physiological grounds, and suggest that more basic biological data on Arctic taxa are needed for improved projections of ecosystem responses to climate change.

Evaluating precipitation datasets for large-scale distributed hydrological modelling

We are experiencing a proliferation of satellite derived precipitation datasets. Advantages and limitations of their promising application in hydrological modelling application have been broadly investigated. However, most studies have analysed only the performance of one or few datasets, were limited to selected small-scale case studies or used lumped models when investigating large-scale basins.In this study, we compared the performance of 18 different precipitation datasets when used as main forcing in a grid-based distributed hydrological model to assess streamflow in medium to large-scale river basins. These datasets are classified as Uncorrected Satellites (Class 1), Corrected Satellites (Class 2) and Reanalysis – Gauges based datasets (Class 3). To provide a broad-based analysis, 8 large-scale river basins (Amazon, Brahmaputra, Congo, Danube, Godavari, Mississippi, Rhine and Volga) having different sizes, hydrometeorological characteristics, and human influence were selected. The distributed hydrological model was recalibrated for each precipitation dataset individually.We found that there is not a unique best performing precipitation dataset for all basins and that results are very sensitive to the basin characteristics. However, a few datasets persistently outperform the others: SM2RAIN-ASCAT for Class 1, CHIRPS V2.0, MSWEP V2.1, and CMORPH-CRTV1.0 for Class 2, GPCC and WFEDEI GPCC for Class 3. Surprisingly, precipitation datasets showing the highest model accuracy at basin outlets do not show the same high performance in internal locations, supporting the use of distributed modelling approach rather than lumped.

Connectivity or isolation? Identifying reintroduction sites for multiple conservation objectives for wisents in Poland

AbstractLarge herbivores and carnivores today often only occupy small fractions of their former ranges, and restoring them is a conservation priority. Reintroductions may serve two critical goals in this context: (1) to expand and connect existing populations, or (2) to increase the number of separate populations as insurance in case individual populations are lost, for example, to disease. We developed an approach to identify reintroduction sites for both purposes, using an applied example of European bison or wisent (Bison bonasus) in Poland. Using a large occurrence dataset from all extant herds in Poland, we mapped suitable wisent habitats throughout Poland using a species distribution modelling approach. We identified 47 patches of suitable habitat, together covering 20,710 km2, and used graph theory tools to identify the top candidate reintroduction sites for (1) connecting existing herds into larger metapopulations or (2) establishing ‘reservoir’ herds that could serve as a backup in case of mass die‐offs. The most well‐connected habitat patches ranged between 203 and 728 km2 and occurred mainly in north‐western and south‐eastern Poland, in close vicinity to other free‐ranging herds. In contrast, candidate sites for reservoir herds were smaller (204–410 km2) and occurred mainly in central Poland. Our approach provides a possible blueprint for wisent reintroductions in Poland. More broadly, our work also highlights how jointly planning for multiple conservation goals for wide‐ranging species that depend on reintroductions or translocations can be achieved at the regional scale.

Identifying main interactions in marine predator–prey networks of the Bay of Biscay

AbstractIdentifying the role that environmental factors and biotic interactions play in species distribution can be essential to better understand and predict how ecosystems will respond to changing environmental conditions. This study aimed at disentangling the assemblage of the pelagic predator–prey community by identifying interspecific associations and their main drivers. For this purpose, we applied the joint species distribution modelling approach, JSDM, to the co-occurrence patterns of both prey and top predator communities obtained from JUVENA surveys during 2013–2016 in the Bay of Biscay. Results showed that the co-occurrence patterns of top predators and prey were driven by a combination of environmental and biotic factors, which highlighted the importance of considering both components to fully understand the community structure. In addition, results also revealed that many biotic interactions, such as schooling in prey (e.g. anchovy–sardine), local enhancement/facilitation in predators (e.g. Cory’s shearwater–fin whale), and predation between predator–prey species (e.g. northern gannet–horse mackerel), were led by positive associations, although predator avoidance behaviour was also suggested between negatively associated species (e.g. striped dolphin–blue whiting). The identification of interspecific associations can therefore provide insights on the functioning of predators–prey network and help advance towards an ecosystem-based management.

Testing effects of Pleistocene climate change on the altitudinal and horizontal distributions of frogs from the Colombian Andes: a species distribution modeling approach

Recent climatic models suggest the late Pleistocene was colder and had different precipitation regimes from the present. If this climatic shift occurred more rapidly than species could adapt, species likely shifted their ranges as populations moved in concert with suitable environmental conditions. We examined changes in altitudinal and horizontal distribution in response to past climate change of amphibian species from different elevational zones and habitat requirements in the Eastern Cordillera of the Colombian Andes. We used environmental information and species occurrence data to model the distribution of 14 amphibian species (seven highland and seven lowland) which we projected to the Last Glacial Maximum (LGM) using two past climatic reconstructions. For these 14 species, we studied the predicted elevational and areal shifts. In agreement with palynological-derived models for Andean flora, we predicted that the elevation of montane amphibians shifted downwards increasing their total altitudinal range. We did not detect any evidence of compression related to drier lowlands. In some cases, the wider distribution areas of high-elevation amphibians during the LGM overlapped with contemporary distributions implying that these areas are present-day refugia for some species. Lowland species showed little or no elevational changes across time, but their areal distributions changed depending on habitat requirements. Four lowland frog species occurring in present-day xeric environments showed substantial range expansion across the lowlands during the LGM, while two species occurring in humid habitats likely expanded their ranges since the LGM. Since the LGM ended, ranges of mid‐ to high-elevation species shrank and shifted to higher elevation. Lowland species in xeric or open habitats have also experienced shrinking ranges, with some evidence that they have been moving upwards. Thus, low- and high-elevation species may be at risk under predicted anthropogenic climate change. Our results generate spatial hypotheses about amphibian responses to climate change that can be tested with phylogeographic data.

Estimation of drug effect in radiographic progression for rheumatoid arthritis and psoriatic arthritis.

To demonstrate the treatment effect on structural damage in rheumatoid arthritis (RA) and psoriatic arthritis (PsA), radiographic images of hands and feet are scored according to Sharp scoring systems in randomized clinical trials. However, the quantification of such an effect is challenging because the overall mean progression is lack of clinical interpretation. This article attempts to shed a light on the statistical challenges resulted from its scoring methods and heterogeneity of the study population and proposes a mixture distribution model approach to fit radiographic progression data. With such a model, the drug effect is fully captured by the mean progression of those patients who would progress in the study period under the control treatment. The resulting regression model also lends a tool in examining prognostic factors for radiographic progression. Simulations have been carried out to evaluate the precision of the parameter estimation procedure. Using the data examples from RA and PsA, we will show that the mixture distribution approach provides a better goodness of fit and leads to a casual inference of the study drug, hence a clinically meaningful interpretation.

Mapping wader biodiversity along the East Asian—Australasian flyway

Background and goalThe study is conducted to facilitate conservation of migratory wader species along the East Asian-Australasian Flyway, particularly to 1) Identify hotspots of wader species richness along the flyway and effectively map how these might change between breeding, non-breeding and migratory phases; 2) Determine if the existing network of protected areas (PA) is sufficient to effectively conserve wader biodiversity hotspots along the EAAF; 3) Assess how species distribution models can provide complementary distribution estimates to existing BirdLife range maps.MethodsWe use a species distribution modelling (SDM) approach (MaxEnt) to develop temporally explicit individual range maps of 57 migratory wader species across their annual cycle, including breeding, non-breeding and migratory phases, which in turn provide the first biodiversity hotspot map of migratory waders along the EAAF for each of these phases. We assess the protected area coverage during each migration period, and analyse the dominant environmental drivers of distributions for each period. Additionally, we compare model hotspots to those existing range maps of the same species obtained from the BirdLife Internationals’ database.ResultsOur model results indicate an overall higher and a spatially different species richness pattern compared to that derived from a wader biodiversity hotspot map based on BirdLife range maps. Field observation records from the eBird database for our 57 study species confirm many of the hotspots revealed by model outputs (especially within the Yellow Sea coastal region), suggesting that current richness of the EAAF may have been underestimated and certain hotspots overlooked. Less than 10% of the terrestrial zones area (inland and coastal) which support waders are protected and, only 5% of areas with the highest 10% species richness is protected.Main conclusionsThe study results suggest the need for new areas for migratory wader research and conservation priorities including Yellow Sea region and Russian far-East. It also suggests a need to increase the coverage and percentage of current PA network to achieve Aichi Target 11 for Flyway countries, including giving stronger consideration to the temporal dynamics of wader migration.

A model based on Gauss Distribution for predicting window behavior in building

Modeling of window behavior is a key component for building performance simulation, due to the significant impact of opening/closing windows on indoor environment and energy consumption. The predictions of existing models cannot well reflect actual window behavior, the prediction accuracy still needs to be improved. The Gauss distribution model is a new machine-learning technique which has achieved successful applications in many fields because of its special advantages (i.e. simple structure, strong operability and flexible nonparametric inference ability) compared to existing models. This paper presents results from a study using the Gauss distribution model to predict window behavior in office building. The data used in this study were from a real building located in Beijing, China, and covered two transitional seasons (from October 1 to November 15, 2014 and from March 15 to May 16, 2015), when natural ventilation was fully applied. When modeling, three types of input variables, i.e., indoor temperature, outdoor temperature and their combination were used. This work validates the importance of selecting suitable input variables when developing Gauss distribution model. This study also compared the prediction performance between the Gauss distribution modeling approach and the Logistic regression modeling approach, which is the most popular method used to model occupant window behavior in buildings. The results showed that Gauss distribution models could provide higher prediction accuracy, with 9.5% higher than Logistic regression model when using suitable inputs. This paper provided a novel modeling method that can be used to predict window states more accurately in office buildings.

Modelling habitat and spatial distribution of the edible insectHenicus whellani Chop (Orthoptera: Stenopelmatidae) in south-eastern districts of Zimbabwe

Edible insects present unique opportunities for food and nutrition security in many African communities. However, the characteristics of habitats and spatial distribution of edible insects is not known and yet it is important for understanding their ecology, planning harvesting and conservation activities in the wild. The edible ground cricket (Henicus whellani) Chopard (Orthoptera: Stenopelmatidae) is an edible insect consumed in south eastern Zimbabwe with protein content >50% on dry matter basis but harvesting is largely random and opportunistic. The aim of this study was to apply the Maximum Entropy (MaxEnt) presence-only species distribution modelling approach to understand the factors influencing distribution ofH. whellani and map the potential areas for harvesting and conservation of the species. Geographical locations of sites whereH. whellani is currently present were obtained from field reports from communities. Seven geographical factors which are mean annual temperature, temperature seasonality, mean annual precipitation, seasonality of precipitation, soil type, elevation, vegetation density and land cover were used to run the model. The model showed a high prediction accuracy forH. whellani (AUC=0.86) indicating that the model can be used with confidence to predict distribution and potential habitats in S.E Zimbabwe. Results showed that soil type (46.7%) and vegetation density (17.5%) are the most important factors determining the distribution ofH. whellani. The hotspots forH. whellani were identified and closely followed specific soil and vegetation gradients in the area. The model considered temperature (3.9%) and elevation (0.6%) as the least important factors inH. whellani distribution. The produced distributed maps can be used for planning efficient harvesting and conservation of this nutritious edible insect in Zimbabwe.

The sufficiency of existed protected areas in conserving the habitat of proboscis monkey (Nasalis larvatus)

Wardatutthoyyibah, Pudyatmoko S, Subrata SA, Imron MA. 2019. The sufficiency of existed protected areas in conserving the habitat of proboscis monkey (Nasalis larvatus). Biodiversitas 20: 1-10. Proboscis monkey (Nasalis larvatus) is an endemic species on the island of Borneo. Their population size progressively decreased because they are very sensitive to any habitat destruction and human activity. The population of proboscis monkey in 2008 was estimated at only approximately 25,000 in total, of which only 5,000 within the conservation areas. However so, the continuation of habitat degradation is hardly prevented in non-protected areas. To solve the problem, the Indonesian government commits to increase the population of the proboscis monkey, particularly outside the protected areas. To support this goal, the distribution data of N. larvatus for conservation planning has become necessary. This study aims to build predictive models of the N. larvatus in Kalimantan and to measure how big the overlap between the habitat and the land use activity (protected areas, concession areas, plantation, and agriculture areas). The study used the Species Distribution Modelling (SDM) approach and Maximum Entropy (MaxEnt) software. We collected recent data from N. larvatus and a number of environmental variables. The result shows that only 5% of the total of Kalimantan area is suitable for their habitat. The overlap between N. larvatus distribution, land use, and land cover map reveals that only 9% of the distribution lies in protected areas, while 37% lies in concession areas and 27% lies in agriculture and plantations areas. We discuss the spatial distribution of the model and current situation of the land use policy in Kalimantan to provide scientific guidance for the Indonesian government to make a master plan for conserving endangered species N. larvatus.

Multi-Model Approach to Quantify Future Sediment and Pollutant Loads and Ecosystem Change in Selenga River System

The Selenga River, which originates in Mongolia, contributes about 50% of the total inflow into Lake Baikal. Hydroclimatic development and abrupt landscape evolution due to mining, industrial, and agricultural activities within the Selenga drainage basin affect the pollutant influx and transport along the course of the river and its tributaries and influence the riverine ecosystem, including fish habitats. This paper presents a process-based distributed modeling approach for the assessment of water, sediment, and contaminants dynamics and its environmental consequences at river basin scale by integrating various tools at multiple spatial scales. Different water quantity and quality processes were considered and modelled, e.g., the hydrology in the river basin, the erosion and sediment transport and budget, and fish migration. A set of regression models and a climate-driven hydrological model (ECOMAG) were applied to create projections of possible changes to the sediment and pollutants transport regime of the Selenga River and its delta that may occur in response to the projected variations of climate of the XXI century. Climate change may reduce the mean flow in the Selenga River at Kabansk by an average of 3–5% in the 2020s–2030s and 4–25% in the 2080s–2090s, depending on climate projections. The future increase in temperatures with permafrost thaw and the expansion of agricultural and mining activities along with urbanizaiton processes may induce up to 6% increase in the particulate modes and 3%, in the dissolved modes of some metals in the river system. Water runoff decline will dramatically decrease suspended sediment retention in the delta. Depending on the climate change scenario, in the 2080–2099, the suspended sediment load will change in the delta by –0.8% (retention) or by +1% (increase), which is much less than the recent observed average of sediment retention rates –33%. The reduction of runoff will induce a decrease in the migration distance of Baikal omul (Coregonus migratorius)) in the XXI century from 185 to 320 km, with a tendency to an increase towards the end of the century.

Meshfree analysis of high-frequency field-effect transistors: distributed modeling approach

Time-domain analysis of high-frequency field-effect transistors is presented using the meshfree radial point interpolation method. The distributed modeling approach is followed in the linear and nonlinear regimes. The corresponding matrix Telegrapher’s equation and terminal conditions are discretized using the weighted average method. Conditionally and unconditionally stable schemes are studied. For linear and conditionally stable nonlinear analysis, the leap-frog and Crank–Nicolson methods are used. To provide unconditional stability in the nonlinear regime, a hybrid backward/forward scheme is exploited.

Managing birds of conservation concern on sandy shores: How much room for future conservation actions is there?

Resource limitations often prevent the active management required to maintain habitat quality in protected areas. Because restrictions in access or allowable public activities are the sole conservation measure in these locations, an important question to consider is whether species of conservation concern truly benefit from parcels that are shielded from human disturbance. Here, we assess the conservation benefit of protecting birds from human recreation on over 204 km of sandy beaches by (a) estimating the total area of beach‐nesting bird habitat that has been created by conservation protections; (b) quantifying the change in nesting habitat extent should further conservation protections be implemented; and (c) providing data to inform future protected area expansion. We use a maximum entropy species distribution modeling approach to estimate the extent and quality of suitable habitat for four beach‐nesting bird species of conservation concern under the existing management regime and compare it to scenarios in which the entire study area is either unprotected of fully protected from human disturbance. Managing humans has dramatic conservation returns for least terns and piping plovers, creating extensive nesting habitat that otherwise would not exist. There is considerable scope for conservation gains, potentially tripling the extent of nesting areas. Expanding conservation footprints for American oystercatchers and black skimmers is predicted to enhance the quality of existing nesting areas. The work demonstrates the utility of modeling changes in habitat suitability to inform protected area expansion on ocean beaches and coastal dunes.

Analysis of dual‐gate high electron mobility transistor using an unconditionally stable time domain method

A dual-gate aluminium gallium arsenide (GaAs)/GaAs pseudomorphic high electron mobility transistor is analysed based on the distributed modelling approach, wherein the transistor is considered as an active multi-conductor transmission line. Discretisation of the governing matrix Telegrapher's equation is carried out using the implicit Crank–Nicolson-finite-difference time-domain (CN-FDTD) method. The results obtained from the proposed method are compared with the results of the conventional leap-frog (LF) FDTD scheme. It is observed that the unconditionally stable CN method is in good agreement with the LF method even by increasing the time step size by the factor of 5000, leading to a dramatic decrease in the central processing unit time.

Increase in CO2 concentration could alter the response of Hedera helix to climate change.

Increasing CO 2 concentration ([CO 2]) is likely to affect future species distributions, in interaction with other climate change drivers. However, current modeling approaches still seldom consider interactions between climatic factors and the importance of these interactions therefore remains mostly unexplored. Here, we combined dendrochronological and modeling approaches to study the interactive effects of increasing [CO 2] and temperature on the distribution of one of the main European liana species, Hedera helix. We combined a classical continent‐wide species distribution modeling approach with a case study using H. helix and Quercus cerris tree rings, where we explored the long‐term influence of a variety of climate drivers, including increasing [CO 2], and their interactions, on secondary growth. Finally, we explored how our findings could influence the model predictions. Climate‐only model predictions showed a small decrease in habitat suitability for H. helix in Europe; however, this was accompanied by a strong shift in the distribution toward the north and east. Our growth ring data suggested that H. helix can benefit from high [CO 2] under warm conditions, more than its tree hosts, which showed a weaker response to [CO 2] coupled with higher cavitation risk under high temperature. Increasing [CO 2] might therefore offset the negative effects of high temperatures on H. helix, and we illustrate how this might translate into maintenance of H. helix in warmer areas. Our results highlight the need to consider carbon fertilization and interactions between climate variables in ecological modeling. Combining dendrochronological analyses with spatial distribution modeling may provide opportunities to refine predictions of how climate change will affect species distributions.

Potential impact of climate change on the distribution of six invasive alien plants in Nepal

The biological invasions have been increasing at multiple spatial scales and the management of invasive alien species is becoming more challenging due to confounding effects of climate change on the distribution of those species. Identification of climatically suitable areas for invasive alien species and their range under future climate change scenarios are essential for long-term management planning of these species. Using occurrence data of six of the most problematic invasive alien plants (IAPs) of Nepal (Ageratum houstonianum Mill., Chromolaena odorata (L.) R.M. King & H. Rob., Hyptis suaveolens (L.) Poit., Lantana camara L., Mikania micrantha Kunth, and Parthenium hysterophorus L.), we have predicted their climatically suitable areas across the country under the current and two future climate change scenarios (RCP 4.5 scenarios for 2050 and 2070). We have developed an ensemble of eight different species distribution modelling approaches to predict the location of climatically suitable areas. Under the current climatic condition, P. hysterophorus had the highest suitable area (18% of the total country’s area) while it was the lowest for M. micrantha (12%). A predicted increase in the currently suitable areas ranges from 3% (M. micrantha) to 70% (A. houstonianum) with the mean value for all six species being 29% under the future climate change scenario for 2050. For four species (A. houstonianum, C. odorata, H. suaveolens and L. camara), additional areas at elevations higher than the current distribution will provide suitable habitat under the projected future climate. In conclusion, all six IAPs assessed are likely to invade additional areas in future due to climate change and these scenarios need to be considered while planning for IAPs management as well as climate change adaptation.

Dynamics of water fluxes and storages in an Alpine karst catchment under current and potential future climate conditions

Abstract. Karst aquifers are difficult to manage due to their unique hydrogeological characteristics. Future climate projections suggest a strong change in temperature and precipitation regimes in European karst regions over the next decades. Alpine karst systems can be especially vulnerable under changing hydro-meteorological conditions since snowmelt in mountainous environments is an important controlling process for aquifer recharge and is highly sensitive to varying climatic conditions. Our paper presents the first study to investigate potential impacts of climate change on mountainous karst systems by using a combined lumped and distributed modeling approach with consideration of subsurface karst drainage structures. The study site is characterized by high-permeability (karstified) limestone formations and low-permeability (non-karst) sedimentary Flysch. The model simulation under current conditions demonstrates that a large proportion of precipitation infiltrates into the karst aquifer as autogenic recharge. Moreover, the result shows that surface snow storage is dominant from November to April, while subsurface water storage in the karst aquifer dominates from May to October. The climate scenario runs demonstrate that varied climate conditions significantly affect the spatiotemporal distribution of water fluxes and storages: (1) the total catchment discharge decreases under all evaluated future climate conditions. (2) The spatiotemporal discharge pattern is strongly controlled by temperature variations, which can shift the seasonal snowmelt pattern, with snow storage in the cold season (December to April) decreasing significantly under all change scenarios. (3) Increased karst aquifer recharge in winter and spring, and decreased recharge in summer and autumn, partly offset each other. (4) Impacts on the karst springs are distinct; the lowest permanent spring presents a “robust” discharge behavior, while the highest overflow outlet is highly sensitive to changing climate. This analysis effectively demonstrates that the impacts on subsurface flow dynamics are regulated by the characteristic dual flow and spatially heterogeneous distributed drainage structure of the karst aquifer. Overall, our study highlights the fast groundwater dynamics in mountainous karst catchments, which make them highly vulnerable to future changing climate conditions. Additionally, this work presents a novel holistic modeling approach, which can be transferred to similar karst systems for studying the impact of climate change on local karst water resources with consideration of their individual hydrogeological complexity and hydraulic heterogeneity.