The effects of longitudinal fragmentation on riverine beta diversity are modulated by fragmentation intensity

The loss of longitudinal connectivity affects river systems globally, being one of the leading causes of the freshwater biodiversity crisis. Barriers alter the dispersal of aquatic organisms and limit the exchange of species between local communities, disrupting metacommunity dynamics. However, the interplay between connectivity losses due to dams and other drivers of metacommunity structure, such as the configuration of the river network, needs to be explored. In this paper, we analyzed the response of fish communities to the network position and the fragmentation induced by dams while controlling for human pressures and environmental gradients. We studied three large European catchments covering a fragmentation gradient: Upper Danube (Austrian section), Ebro (Spain), and Odra/Oder (Poland). We quantified fragmentation through reach-scaled connectivity indices that account for the position of barriers along the dendritic network and the dispersal capacity of the organisms. We used generalized linear models to explain species richness and Local Contributions to Beta Diversity (LCBD) and multilinear regressions on the distance matrix to describe Beta Diversity and its Replacement and Richness Difference components. Results show that species richness was not affected by fragmentation. Network centrality metrics were relevant drivers of beta diversity for catchments with lower fragmentation (Ebro, Odra), and fragmentation indices were strong beta diversity predictors for the catchment with higher fragmentation (Danube). We conclude that in highly fragmented catchments, the effects of network centrality/isolation on biodiversity could be masked by the effects of dam fragmentation. In such catchments, metapopulation and metacommunity dynamics can be strongly altered by barriers, and the restoration of longitudinal connectivity (i.e. the natural centrality/isolation gradient) is urgent to prevent local extinctions.

Assessing hydrological connectivity for natural-artificial catchment with a new framework integrating graph theory and network analysis

Anthropogenic activities alter the underlying surface conditions and arrangements of landscape features in a drainage basin, interfering with the pollutant (e.g., dissolved nitrogen, phosphorus) transport network configuration and altering the hydrological response. Assessing the impact of anthropogenic activities on hydrological connectivity for natural-artificial catchment is critical to understand the hydrological-driven ecosystem processes, services and biodiversity. However, quantifying this impact at catchment scale remains challenging. In this study, a new framework was proposed to quantify the impact of anthropogenic activities on hydrological connectivity combined with graph theory and network analysis. This framework was exemplified in a natural-artificial catchment of the Yangtze River basin of China. Based on remote sensing and field-investigated data, three transport networks were constructed, including natural transport network (N1), ditch-road transport network (N2), and terrace-dominated transport network (N3), which reflected the different human intervention. The results showed that human intervention improved the connectivity of the nodes and enhanced the complexity of the catchment transport network structure. Anthropogenic activities significantly decreased the hydrological structural connectivity of the catchment. In particular, compared with the N1 network, the critical nodes for hydrological connectivity which were judged by connectivity indexes were reduced by 92.94% and 95.29% in the N2 and N3 network, respectively. Furthermore, the ditch-road construction had a greater impact than terraces in decreasing hydrological structural connectivity at catchment scale. This framework has proven effective in quantifying the hydrological connectivity analysis under different human intervention at the catchment scale and facilitates the improvement of catchment management strategies.

Marine aquaculture as a source of propagules of invasive fouling species

Non-indigenous species tend to colonize aquaculture installations, especially when they are near international ports. In addition to the local environmental hazard that colonizing non-indigenous species pose, they can also take advantage of local transport opportunities to spread elsewhere. In this study, we examined the risk of the spread of eight invasive fouling species that are found in mussel farms in southern Brazil. We used ensemble niche models based on worldwide occurrences of these species, and environmental variables (ocean temperature and salinity) to predict suitable areas for each species with three algorithms (Maxent, Random Forest, and Support Vector Machine). As a proxy for propagule pressure, we used the tonnage transported by container ships from Santa Catarina (the main mariculture region) that travel to other Brazilian ports. We found that ports in the tropical states of Pernambuco, Ceará, and Bahia received the largest tonnage, although far from Santa Catarina and in a different ecoregion. The ascidians Aplidium accarense and Didemnum perlucidum are known from Bahia, with a high risk of invasion in the other states. The bryozoan Watersipora subtorquata also has a high risk of establishment in Pernambuco, while the ascidian Botrylloides giganteus has a medium risk in Bahia. Paraná, a state in the same ecoregion as Santa Catarina is likely to be invaded by all species. A second state in this region, Rio Grande do Sul, is vulnerable to A. accarense, the barnacle Megabalanus coccopoma, and the mussel Mytilus galloprovincialis. Climate change is changing species latitudinal distributions and most species will gain rather than lose area in near future (by 2050). As an ideal habitat for fouling organisms and invasive species, aquaculture farms can increase propagule pressure and thus the probability that species will expand their distributions, especially if they are close to ports. Therefore, an integrated approach of the risks of both aquaculture and nautical transport equipment present in a region is necessary to better inform decision-making procedures aiming at the expansion or establishment of new aquaculture farms. The risk maps provided will allow authorities and regional stakeholders to prioritize areas of concern for mitigating the present and future spread of fouling species.

Connectivity indices of m-polar fuzzy network model, with an application to a product manufacturing problem

Connectivity is among the most essential concerns in graph theory and its applications. We consider this issue in a framework that stems from the combination of m-polar fuzzy set theory with graphs. We introduce two measurements of connectedness of m-polar fuzzy graphs that we call their connectivity and average connectivity indices. Examples are given, and the theoretical performance of these concepts is investigated. Particularly, we are concerned with the effect of deleting a vertex or an edge from an m-polar fuzzy graph, on its connectivity and average connectivity indices. We also establish bounding expressions for the connectivity index in complete m-polar fuzzy graphs, complete bipartite m-polar fuzzy graphs, and wheel m-polar fuzzy graphs. Moreover, we introduce some special types of vertices called m-polar fuzzy connectivity reducing vertices, m-polar fuzzy connectivity enhancing vertices, and m-polar fuzzy connectivity neutral vertices. Our theoretical contribution is applied to a product manufacturing problem that takes advantage of multi-polar uncertain information. The justification for our application is systematized using an algorithm. Finally, we compare the proposed method to existing methodologies to demonstrate its feasibility and applicability.

On the significance of edges for connectivity in uncertain random graphs

In practical applications of graph theory, indeterminacy factors always appear in graphs. Uncertain random graph was proposed via chance theory, in which some edges exist with degrees in probability measure and others exist with degrees in uncertain measure. This paper discusses the contributions of edges for connectivity of an uncertain random graph and proposes concepts about significance of edges, according to which edges are classified. In addition, this paper presents algorithms for calculating connectivity index and significance of edges of an uncertain random graph. Examples are given to illustrate algorithms and methods.

Hydrological connectivity dynamics of tidal flat systems impacted by severe reclamation in the Yellow River Delta

River deltas contain complex self-organizing channel networks that continuously exchange fluxes of water, matter, energy, and information with their surroundings. The connectivity of these exchange processes plays a crucial role in controlling the evolution and dynamic stability of river deltas. However, connectivity patterns related to tidal channel networks have rarely been studied, especially in the Yellow River Delta (YRD), which is impacted by severe reclamation. Here, we evaluated the potential hydrological connectivity dynamics between the tidal channel network and its surroundings using an index of connectivity (IC) in the whole YRD and its three sub-regions: erosion zone, oil field zone and deposition zone. The results suggested that different areas had different spatial connectivity potential. The mean value of the IC related to the channel networks showed little difference for any zones. However, the total connectivity response area (CRA; set of connectivity response units) varied with the study scale. A decreasing trend was found on the delta scale and a relatively stable trend was found in the deposition zone. In terms of dynamic connectivity, the tidal flat system did not show a continuous trend over time. Our results indicated that the YRD is such a dynamic complex that a relatively stable connectivity pattern is unlikely to be achieved over time. Therefore, future ecological restoration based on hydrological connectivity needs to consider more related influencing factors and their temporal and spatial dynamics.

A model to evaluate spatiotemporal variations of hydrological connectivity on a basin-scale complex river network with intensive human activity

In recent decades, rivers have been among the most gravely disturbed ecosystems due to intense anthropogenic impacts. Accurate spatial evaluation of river network connectivity is necessary for providing an improved empirical basis for management, conservation, and restoration initiatives. In this study, we focused on the stream continuity-oriented hydrological connectivity of the river network ecosystem. An evaluation model was established using spatiotemporal hydrological data, temporal data on dam development, and a new stream continuity-oriented connectivity index (SCI). The Pearl River basin was selected as the study area to demonstrate the model application using data since 1960. The model showed that the SCI values had significantly and steadily decreasing characteristics in the entire basin from 1960 to 2018, with a total decrease during this period of 26% throughout the river network. The connectivity of the river network declined as the number of dams increased, and dams built on main trunks had a larger impact on the connectivity than those on tributaries. These model results can help government regulators identify the worst connected areas of the river network and take effective measures to reduce the impact of human interferences. Thus, the model can provide practical guidance and support to the conservation, management, and restoration of the river ecosystem.

Evaluating dynamic hydrological connectivity of a floodplain wetland in North Bihar, India using geostatistical methods

Spatio-temporal connectivity patterns of a wetland as a function of the land use/land cover (LULC) of its catchment have been analysed in a GIS environment. An innovative method has been implemented for mapping 'dynamic hydrological connectivity' for a water-stressed wetland of Kosi-Ganga interfluve area in the middle Ganga Plains, India for pre- and post-monsoon seasons over a time-span of 29 years (1989 to 2017). It was accomplished by using the time-series NDVI (Normalized Difference Vegetation Index) data and the connectivity response unit (CRU) approach by applying geostatistical methods namely the Getis-Ord Gi* and Mann-Kendall trend test statistics. The study area is principally a rain-fed wetland located in flat terrain (average slope of ~2°) under intensive agriculture and receives water as overland flows. The agriculture dominated LULC in this region is controlling the wetland-catchment connectivity scenarios and the overall connectivity potential of the catchment is higher in the pre-monsoon compared to the post-monsoon season. High and low connectivity potentials of different areas of the catchment with respect to the wetland have been classified into three types: persistent, intensifying, and diminishing. The areas with 'persistent' high or low connectivity potentials have been attributed to the topographic factors which are static in nature, such as the proximity to the wetland and the presence of other geomorphic features. The 'intensifying' and 'diminishing' clusters have been linked to changing LULC patterns. The proposed method holds significant implications for the restoration of wetland-catchment connectivity and can be applied in any flatland terrain where hydrological connectivity is strongly influenced by the surface impedance induced by LULC.