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Surface water network structure, landscape resistance to movement and flooding vital for maintaining ecological connectivity across Australia’s largest river basin

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Context: Landscape-scale research quantifying ecological connectivity is required to maintain the viability of populations in dynamic environments increasingly impacted by anthropogenic modification and environmental change. Objective: To evaluate how surface water network structure, landscape resistance to movement, and flooding affect the connectivity of amphibian habitats within the Murray–Darling Basin (MDB), a highly modified but ecologically significant region of south-eastern Australia. Methods: We evaluated potential connectivity network graphs based on circuit theory, Euclidean and least-cost path distances for two amphibian species with different dispersal abilities, and used graph theory metrics to compare regional- and patch-scale connectivity across a range of flooding scenarios. Results: Circuit theory graphs were more connected than Euclidean and least-cost equivalents in floodplain environments, and less connected in highly modified or semi-arid regions. Habitat networks were highly fragmented for both species, with flooding playing a crucial role in facilitating landscape-scale connectivity. Both formally and informally protected habitats were more likely to form important connectivity “hubs” or “stepping stones” compared to non-protected habitats, and increased in importance with flooding. Conclusions: Surface water network structure and the quality of the intervening landscape matrix combine to affect the connectivity of MDB amphibian habitats in ways which vary spatially and in response to flooding. Our findings highlight the importance of utilising organism-relevant connectivity models which incorporate landscape resistance to movement, and accounting for dynamic landscape-scale processes such as flooding when quantifying connectivity to inform the conservation of dynamic and highly modified environments.
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... Over-harvesting, distribution shrinkage, and ongoing habitat destruction and degradation have resulted in a severe population decline, which was estimated to be more than 50% in the last 15 years (Lau et al., 2004). Moreover, considerable time lags in observable population fluctuations have often been associated with habitat isolation and connectivity reductions, and extensively distributed amphibian species may decrease undetected before reaching a considerable magnitude (Bishop-Taylor et al., 2015). Owing to the limited availability of resources for protecting the continuously growing list of threatened species, it is particularly relevant that conservation strategies take into account how climate change would affect suitable habitats and connectivity for species and accordingly prioritize corridors (McRae and Beier, 2007). ...
... Amphibians do not rely on the 'perceptual environment knowledge' to disperse but instead largely make use of random-walk dispersal strategies in response to features encountered in their paths (Pittman et al., 2014). In Circuitscape, the algorithms based on the electrical circuit theory provide an ideal tool to model the broadest possible evaluation of connectivity for amphibians, which are not dependent on species-specific dispersal abilities (Bishop-Taylor et al., 2015;McRae et al., 2008). To trace the most parsimonious path between core patches with the highest suitability, best chances for the connection of isolated patches are provided (Fig. 4). ...
... This may be due to a funneling effect in which climate-driven habitat shifts can reduce multiple movement pathways, resulting in an increased role for the remaining pathways (Dilts et al., 2016). The Circuitscape models allow the dispersal to end between core patches because of high resistance or too long distances (Bishop-Taylor et al., 2015;Brambilla et al., 2017;McRae et al., 2008). As the populations of spiny-bellied frog are isolated in mountain habitats (Fei et al., 2009;Lau et al., 2004;Yan et al., 2013), the dynamic connectivity modified by changing climate is vital for providing opportunities for dispersal across the highly fragmented habitat networks, and a decrease in connectivity could be a key issue, especially in marginal or contracting populations (Figs. 4 & S8-S11). ...
Article
Amphibians are particularly vulnerable to climate changes that are expected to cause habitat fragmentation and loss and, ultimately, local extirpations. However, little is known about how the interaction between climate change and fragmentation may impede the ability of amphibians to adapt to climate change. Here, we used the iconic mountain frog Quasipaa boulengeri as an indicator species to extrapolate climate-driven shifts in its habitat availability and connectivity in central and southern China according to the minimum and maximum representative concentration pathways. The models projected an average habitat loss of 36%–71% and the in situ and ex situ climate-change refugia to be 29%–64% and 5%–18% of the present-day suitable habitats, respectively. An increase in habitat fragmentation was reflected in a 51% decrease in core patch size, a 9% increase in the mean least-cost path (LCP) length, and a 19% increase in the cost-weighted distance. These climate-driven shifts varied spatially around the Sichuan Basin, with those in the southeast of the Basin being the most pronounced habitat and connectivity losses and those along the Basin being relatively optimistic. The effectiveness of refugia may only be maintained through a narrow passageway along the southern Sichuan Basin because of the presence of LCPs over time. Our results emphasize the need to understand how climate change and connectivity will jointly affect the distribution of mountain amphibians and to accordingly adopt conservation strategies. Further, our findings highlight the importance of identifying and preserving climate-change refugia and habitat connectivity for species persistence and conservation planning.
... In this approach, the landscape is represented as a set of discrete habitat patches, or nodes, connected by links that represent the ability of an organism to disperse between nodes (Calabrese & Fagan, 2004). We defined links based on least-cost paths as a measure of effective distance between nodes and used cost-distance surfaces to account for landscape resistance to movement (Bishop-Taylor et al., 2015;Dilts et al., 2016). We defined resistance values based on the assumption that forest species, especially specialist species, will face greater dispersal difficulty as they move through land-cover types with characteristics increasingly disparate from those of the forested areas where they reside, similar to Saura et al. (2011). ...
... Least-cost distances were calculated between the centroids of habitat patches, similar to Theobald et al. (2012), and reflect the minimum cost accumulated along the shortest path between two habitat nodes (Bishop-Taylor et al., 2015;van Etten, 2017). Using habitat patch centroids reduced computation time and allowed us to simulate species movement between and within habitat patches as a continuous process rather than assuming within-patch homogenization or an abrupt end to species movement at a patch edge (Dickson et al., 2017). ...
... Our connectivity analysis relied on least-cost path resistance distances based on the assumption that forest species will face greater dispersal difficulty as they move through landcover types increasingly disparate from their preferred habitat, as described in Saura et al. (2011). Yet, the use of leastcost paths relies on two simplifying assumptions: that a single optimal path between habitats conveys the movement potential of that segment of the landscape and that an organism has complete knowledge of the landscape and can select a movement path accordingly (Pinto & Keitt, 2009;Bishop-Taylor et al., 2015). Future analyses could use circuit theory (e.g., Circuitscape, McRae et al., 2013) as a measure of effective distance between patches or between patch edges instead of patch centers. ...
Article
Maintaining and enhancing landscape connectivity reduces biodiversity declines due to habitat fragmentation. Uncertainty remains, however, about the effectiveness of conservation for enhancing connectivity for multiple species on dynamic landscapes, especially over long time horizons. Focusing on central North Carolina, we forecast connectivity under four common conservation strategies‐ acquiring the lowest cost land, acquiring land clustered around already established conservation areas, acquiring land with high geodiversity characteristics, and acquiring land opportunistically‐ on a dynamic landscape incorporating forest growth and succession, disturbance, and management from 2020 to 2100. We used graph theoretic metrics to quantify landscape connectivity across these four strategies, evaluating connectivity for four ecologically relevant species guilds, representing endpoints along a spectrum of vagility and habitat specificity: long‐ vs. short‐distance dispersal ability and habitat specialists vs. generalists. Our results indicate that landscape connectivity will improve for specialist species under any conservation strategy employed, although these increases were highly variable across strategies. For generalist species, connectivity improvements were negligible. Overall, clustering the development of new protected areas around land already designated for conservation yielded the largest improvements in connectivity, with increases of several orders of magnitude beyond current landscape connectivity for both long‐ and short‐distance dispersing specialist species. Conserving the lowest cost land showed the smallest contributions to connectivity. Our approach provides insight into the connectivity contributions of a suite of conservation alternatives prior to on‐the‐ground implementation, and therefore can inform connectivity planning to maximize conservation benefit. This article is protected by copyright. All rights reserved
... The first set of studies investigates the temporal dynamics of connectivity without testing their effects on biodiversity. In these studies, the impact of the temporal dynamics of connectivity on biodiversity is assumed, based on the hypothesis that landscape graphs used for connectivity assessment accurately represent the presence and the dispersal movements of the species concerned (see for instance Bishop-Taylor et al. 2015;Liu et al. 2017;Huang et al. 2020). The second set of study goes further thanks to empirical testing (Metzger et al. 2009;Bommarco et al. 2014;Huber et al. 2017;Raatikainen et al. 2018;Horváth et al. 2019)-and sometimes, to validation (Metzger et al. 2009;Bommarco et al. 2014;Raatikainen et al. 2018;Horváth et al. 2019)-of the impact of temporal dynamics of connectivity on biodiversity patterns. ...
... By contrast, several studies tested for significant differences in local or global connectivity between time steps in the time series. These differences were assessed by comparing the standard error (Rayfield et al. 2008;Raatikainen et al. 2018) or the 95% confidence interval (Bishop- Taylor et al. 2015) around mean connectivity values. Statistical tests could be also used though already done yet. ...
... They assessed the robustness of the aquatic landscape by studying the curve of global connectivity with an increasing proportion of sequentially removed aquatic habitat patches. Other authors go further, reporting a visual examination of the temporal changes in spatial connectivity accounting for changes in nodes and/or and edges at both global(Bishop-Taylor et al. 2015;Saura et al. 2019) and local(Metzger et al. 2009;Raatikainen et al. 2018) scales. For example,Bishop- Taylor et al. (2015) considered global spatial connectivity of surface water habitats under eight flooding scenarios ranging from no flood to a 100-year average recurrence interval in an aquatic landscape. ...
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ContextLandscape connectivity plays a key role in determining the persistence of species inhabiting fragmented habitat patches. In dynamic landscapes, most studies measure connectivity at multiple time steps, but pay less attention to explicitly quantifying its temporal dynamics to gain insights into its role in biodiversity patterns, thereby enabling more effective operational outcomes.Objectives This article aimed at making an overview of the existing methods for the assessment of the temporal dynamics of connectivity. By analysing their differences and possible applications, we aimed to highlight knowledge gap and future research directions.Methods We conducted a systematic review of literature dealing with the assessment of the temporal dynamics of connectivity and obtained 32 studies.ResultsWe presented two main approaches based on graph theory and compared them from conceptual and operational perspectives. The first widely used approach, accounting only for the spatial dispersal of organisms, quantifies temporal changes in spatial connectivity. Based on two or multiple time steps in the time series, this approach enables assessment of the sense and magnitude of the temporal changes in spatial connectivity. The second recently developed approach quantifies spatio-temporal connectivity, thus accounting for both spatial and temporal dispersal. So far, this holistic assessment of spatio-temporal connectivity only covers two time steps.Conclusion Existing methods for the assessment of the temporal dynamics of connectivity provide indicators to advance our understanding of biodiversity patterns, and to be able to implement measures to conserve and restore connectivity. We propose future directions to develop these methods.
... For example, researchers developed maps of surface water and flooding extent dynamics (SWD) using statistically representative measures of accuracy based on the entire Landsat archive across one of the largest agricultural dryland basins in the world . They then used the SWD maps together with time series of vegetation dynamics to quantify space time patterns of vegetation response to flooding (Broich et al., 2018;Shendryk et al., 2016), to assess drivers of flooding dynamics across space and time (Heimhuber et al., 2016(Heimhuber et al., , 2017, and to identify surface water habitats that play central roles as biodiversity hubs for water dependent biota (Bishop-Taylor et al., 2015, 2017. This type of work, while technically possible at global scales, will prove less insightful due to generalizations that will need to be made even if enough budget is available for their global development. ...
Article
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Unprecedented amounts of analysis‐ready Earth Observation (EO) data, combined with increasing computational power and new algorithms, offer novel opportunities for analysing ecosystem dynamics across large geographic extents, and to support conservation planning and action. Much research effort has gone into developing global EO‐based land‐cover and land‐use datasets, including tree cover, crop types, and surface water dynamics. Yet there are inherent trade‐offs between regional and global EO products pertaining to class legends, availability of training/validation data, and accuracy. Acknowledging and understanding these trade‐offs is paramount for both developing EO products and for answering science questions relevant for ecology or conservation studies based on these data. Here we provide context on the development of global EO‐based land‐cover and land‐use datasets, and outline advantages and disadvantages of both regional and global datasets. We argue that both types of EO‐derived land‐cover datasets can be preferable, with regional data providing the context‐specificity that is often required for policy making and implementation (e.g., land‐use and management, conservation planning, payment schemes for ecosystem services), making use of regional knowledge, particularly important when moving from land cover to actors. Ensuring that global and regional land‐cover and land‐use products derived based on EO data are compatible and nested, both in terms of class legends and accuracy assessment, should be a key consideration when developing such data. Open access high‐quality training and validation data derived as part of such efforts are of utmost importance. Likewise, global efforts to generate sets of essential variables for climate change, biodiversity, or eventually land use, which often require land‐cover maps as inputs, should consider regionalized, hierarchical approaches to not sacrifice regional context. Global change impacts manifest in regions, and so must the policy and planning responses to these challenges. EO data should embrace that regions matter, perhaps more than ever, in an age of global data availability and processing.
... In reality, landscape connectivity is affected by both the landscape and the particular species (Baranyi, Saura, Podani, & Jordan, 2011). Appropriate landscape connectivity is widely acknowledged as a critical element for the genetic persistence of the species, as it facilitates the movement of individual animals among the habitat patches (Bishop-Taylor, Tulbure, & Broich, 2015;Estes et al., 2012;Loro, Ortega, Arce, & Geneletti, 2015). In contrast, a decrease in connectivity caused by landscape fragmentation and habitat loss has been attributed to various biodiversity crises in many parts of the world (Austin, 1996;Fu, Liu, Cui, & Zhang, 2009). ...
Article
The landscape connectivity of natural habitats serves an important role in the migration and survival of animals. In southwestern China, the rapid decline of the Asian elephant (Elephas maximus) population has been attributed to habitat loss and fragmentation due to recent land-use changes. Despite efforts to protect the Asian elephants' habitats, an analysis on the cross-scale landscape connectivity within and among these habitats has rarely been documented. In this study, we focused in Xishuangbanna, China and first identified the key patches for the Asian elephant in Xishuangbanna, China. We then evaluated the landscape connectivity and compared scenarios for eight dispersal distances of the resource patches. Levels of importance for each individual patch were evaluated by calculating the probability of connectivity (dPC) and betweenness centrality (dBC). Results showed that habitats with high suitability occupied 29% of the studied area. The distribution of patch importance levels wasdetermined separately by dPC and dBC, and these two indices corresponded with each other via the con-nector fraction of dPC (dPC connector) index. The final total area of the priority patches was 2478 km 2 , or approximately 76% of the suitable habitat area. Our study indicated that the cross-scale landscape connectivity analysis is an effective approach to characterize the key patches, and the priority patches for Asian elephants can be selected by using both dBC and dPC in Xishuangbanna.
... Ecology and conservation often target landscape networks with different properties, operating at various scales (e.g., representing insect movement within a forest patch, Della Rocca et al. 2017; amphibian movements in freshwater ecosystems, Bishop-Taylor et al. 2015; protected areas, such as the Natura 2000 network in European Union, Mazaris et al. 2013; or the global protected area network, Santini et al. 2016). Obviously, there are many differences in the structural elements, the organization levels and the scaling properties of such networks. ...
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ContextLandscape connectivity quantification is essential to achieve effective conservation of wildlife. Graph theory is a common mathematical framework for representing habitat patch networks and evaluating their connectivity.Objectives While several graph-related indices have been used for this purpose, there is still need to evaluate landscape connectivity from different perspectives.Methods Based on classic network indices, we developed five novel landscape connectivity indices that incorporated attributes related to the quality of the patches, the connections among them, the dispersal probabilities and the overall habitat availability. To evaluate their performance, we applied them on three ecological networks developed for three species with different traits, at different scales, and compared them with widely used landscape connectivity indices.ResultsThe developed indices identified, in all the three networks, critical patches that were well-connected with others, and also aggregated valuable features which could affect network quality. Some critical patches and specific network connectivity properties could be overlooked if not considering the additional dimensions of information that these advanced indices incorporate.Conclusions We showed that the developed indices exhibited flexibility and wide applicability, offering novel insights on the evaluation of node contribution to the overall network connectivity. By integrating spatial patterns and processes, the solutions provided by the new indices could serve as an effective tool towards supporting landscape conservation planning.
... Graph theory approaches, which model pairwise relationships between nodes (lakes or streams) connected to each other by edges (streams), provide ways to overcome computational challenges because they have minimal data requirements while still providing accurate estimates of connections between waterbodies (Calabrese and Fagan 2004). However, because these metrics can be computationally difficult, studies that have applied graph theory to lakes are often restricted to a few watersheds (Bishop-Taylor et al. 2015;Saunders et al. 2016). ...
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Identifying lake networks and knowing the degree of surface‐water connectivity among lakes can help scientists better understand and predict the movement of abiotic materials and biota within networks. Quantifying broad‐scale networks that include lake and stream connections is difficult computationally. Starting from the medium resolution National Hydrography Dataset's lakes, streams, and rivers, we applied a graph theory approach to identify lake networks, a set of lakes connected by streams both upstream and downstream. The LAGOS‐US NETWORKS v1 module contains four data tables, one of which includes derived surface‐water connectivity metrics for lakes (n = 86,511 lakes ≥ 1 ha in surface area) and networks (n = 898) within the conterminous United States, including dams. The NETWORKS module also includes a flow table as well as a bidirectional and a unidirectional distance table that provide the stream course distances between every connected lake. Finally, this module includes a detailed User Guide.
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Graph theory (GT) is extensively applied in the ecological network analysis. This review study aimed to examine GT in the field of ecological network analysis based on the following questions: In what areas are the articles focused?, what indexes or graph-based indicators have been thus far utilized in ecological network analysis?, and what aspects of ecological network analysis have been less considered in terms of the use of the GT indicators? To address these questions, a systematic literature review was conducted and the results showed that most of the articles in this field had been fulfilled in China, the United States, and France. This theory could have implications for more research on plants and mammals. In addition, 118 indicators were identified in the field of GT in the ecological network analysis. Among these indicators, the probability of connectivity (PC) and an integral index of connectivity (IIC) had been consistently exploited in most articles. Moreover, the results revealed the increasing trend of introducing the new indicators of GT to ecological network analysis, suggesting the applicability of GT in this context. Despite the importance of ecological network resilience, it has been less reflected from the GT perspective while it can be useful and efficient in analyzing the sustainability of ecological networks within this framework. The current trend of exploiting the GT indicators delineates three future lines of development, viz. (1) the GT use more widely in ecological network analysis, (2) emerging new and more precise indexes, and (3) new concerns mainly examining ecological network resilience.
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