Surface-water dynamics and land use influence landscape connectivity across a major dryland region

Improving on mapping long-term surface water with a novel framework based on the Landsat imagery series

Surface water plays a crucial role in the ecological environment and societal development. Remote sensing detection serves as a significant approach to understand the temporal and spatial change in surface water series (SWS) and to directly construct long-term SWS. Limited by various factors such as cloud, cloud shadow, and problematic satellite sensor monitoring, the existent surface water mapping datasets might be short and incomplete due to losing raw information on certain dates. Improved algorithms are desired to increase the completeness and quality of SWS datasets. The present study proposes an automated framework to detect SWS, based on the Google Earth Engine and Landsat satellite imagery. This framework incorporates implementing a raw image filtering algorithm to increase available images, thereby expanding the completeness. It improves OTSU thresholding by replacing anomaly thresholds with the median value, thus enhancing the accuracy of SWS datasets. Gaps caused by Landsat7 ETM + SLC-off are respired with the random forest algorithm and morphological operations. The results show that this novel framework effectively expands the long-term series of SWS for three surface water bodies with distinct geomorphological patterns. The evaluation of confusion matrices suggests the good performance of extracting surface water, with the overall accuracy ranging from 0.96 to 0.97, and user's accuracy between 0.96 and 0.98, producer's accuracy ranging from 0.83 to 0.89, and Matthews correlation coefficient ranging from 0.87 to 0.9 for several spectral water indices (NDWI, MNDWI, ANNDWI, and AWEI). Compared with the Global Reservoirs Surface Area Dynamics (GRSAD) dataset, our constructed datasets promote greater completeness of SWS datasets by 27.01%-91.89% for the selected water bodies. The proposed framework for detecting SWS shows good potential in enlarging and completing long-term global-scale SWS datasets, capable of supporting assessments of surface-water-related environmental management and disaster prevention.

Forecasting the influence of conservation strategies on landscape connectivity

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. We forecasted landscape connectivity from 2020 to 2100 under four common conservation land-acquisition strategies: acquiring the lowest cost land, acquiring land clustered around already established conservation areas, acquiring land with high geodiversity characteristics, and acquiring land opportunistically. We used graph theoretic metrics to quantify landscape connectivity across these four strategies, evaluating connectivity for four ecologically relevant species guilds that represent endpoints along a spectrum of vagility and habitat specificity: long- versus short-distance dispersal ability and habitat specialists versus generalists. We applied our method to central North Carolina and incorporated landscape dynamics, including forest growth, succession, disturbance, and management. Landscape connectivity improved for specialist species under all conservation strategies employed, although 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; increases were several orders of magnitude beyond current landscape connectivity for long- and short-distance dispersing specialist species. Conserving the lowest cost land contributed the least 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.

Modelling Dynamic Hydrological Connectivity in the Zoigê Area (China) Based on Multi-Temporal Surface Water Observation

The sustainability of wetlands is threatened by the past and present land use practices. Hydrological connectivity is one of the most important aspects to consider for wetland rehabilitation planning purposes. Circuit theory and connectivity indices can be used to model and assess hydrological connectivity. The aim of this study was to assess spatiotemporal variation in the hydrological connectivity of the Zoigê area from 2000–2019 using both methods. The study area contains a Ramsar wetland of international importance, namely the Sichuan Ruoergai Wetland National Nature Reserve. We used a global surface water observation product as the major input for both methods, and then analyzed the temporal and spatial characteristics, in terms of important components and patches. We found that the overall connectivity has increased slightly in the last 20 years, while the probability of connection between patches of surface water has increased significantly. Important components and patches represent steppingstone habitat for the dispersal of organisms in the landscape. The main determinants of hydrological connectivity are mostly human oriented, predominantly a decrease in large livestock population size and population increase.

Measuring Dynamic Changes in the Spatial Pattern and Connectivity of Surface Waters Based on Landscape and Graph Metrics: A Case Study of Henan Province in Central China

An understanding of the scientific layout of surface water space is crucial for the sustainable development of human society and the ecological environment. The objective of this study was to use land-use/land-cover data to identify the spatiotemporal dynamic change processes and the influencing factors over the past three decades in Henan Province, central China. Multidisciplinary theories (landscape ecology and graph theory) and methods (GIS spatial analysis and SPSS correlation analysis) were used to quantify the dynamic changes in surface water pattern and connectivity. Our results revealed that the water area decreased significantly during the periods of 1990–2000 and 2010–2018 due to a decrease in tidal flats and linear waters, but increased significantly in 2000–2010 due to an increase in patchy waters. Human construction activities, socioeconomic development and topography were the key factors driving the dynamics of water pattern and connectivity. The use of graph metrics (node degree, betweenness centrality, and delta probability of connectivity) in combination with landscape metrics (Euclidean nearest-neighbor distance) can help establish the parameters of threshold distance between connected habitats, identify hubs and stepping stones, and determine the relatively important water patches that require priority protection or development.

Assessing the Impact of Urban Expansion on Surrounding Forested Landscape Connectivity across Space and Time

Landscape connectivity is important for all organisms as it directly affects population dynamics. Yet, rapid urbanization has caused serious landscape fragmentation, which is the primary contributor of species extinctions worldwide. Previous studies have mostly used spatial snap-shots to evaluate the impact of urban expansion on landscape connectivity. However, the interactions among habitats over time in dynamic landscapes have been largely ignored. Here, we demonstrated that overlooking temporal connectivity can lead to the overestimation of the impact of urban expansion. How much greater the overestimation is depends on the amount of net habitat loss. Moreover, we showed that landscape connectivity may have a delayed response to urban expansion. Our analysis shifts the way to understand the ecological consequences of urban expansion. Our framework can guide sustainable urban development and can be inspiring to conservation practices under other contexts (e.g., climate change).

Circuitscape in Julia: Empowering Dynamic Approaches to Connectivity Assessment

The conservation field is experiencing a rapid increase in the amount, variety, and quality of spatial data that can help us understand species movement and landscape connectivity patterns. As interest grows in more dynamic representations of movement potential, modelers are often limited by the capacity of their analytic tools to handle these datasets. Technology developments in software and high-performance computing are rapidly emerging in many fields, but uptake within conservation may lag, as our tools or our choice of computing language can constrain our ability to keep pace. We recently updated Circuitscape, a widely used connectivity analysis tool developed by Brad McRae and Viral Shah, by implementing it in Julia, a high-performance computing language. In this initial re-code (Circuitscape 5.0) and later updates, we improved computational efficiency and parallelism, achieving major speed improvements, and enabling assessments across larger extents or with higher resolution data. Here, we reflect on the benefits to conservation of strengthening collaborations with computer scientists, and extract examples from a collection of 572 Circuitscape applications to illustrate how through a decade of repeated investment in the software, applications have been many, varied, and increasingly dynamic. Beyond empowering continued innovations in dynamic connectivity, we expect that faster run times will play an important role in facilitating co-production of connectivity assessments with stakeholders, increasing the likelihood that connectivity science will be incorporated in land use decisions.

The impact assessment of hydro-biological connectivity changes on the estuary wetland through the ecological restoration project in the Yellow River Delta, China

Yellow River Delta (YRD) is one of the youngest delta with complex hydrological and biological connectivity in the world, where offers habitats to the famous waterfowls in the Eastern Asia. Meanwhile, one specific ecological restoration project named as the "Wuwanmu" and followed by the "Shiwanmu" within the National Nature Reserve of the Yellow River Delta (NNRYRD) complicated the hydrological and biological connectivity. How to quantitatively evaluate the extent of coastal wetland affected by the project will be a difficult problem. Hence the authors presented three innovative models of the Marine Connectivity Change Index (MCCI), the Coupling Index of Hydro-biological Connectivity (CIHBC), and the Assessment Index of Suitability on Bird Habitats (AISBH). After the project, the habitat of Phragmites australis has been restored effectively with the increased area of 24.59%, while the habitat of Suaeda salsa as the native species lost largely with decreased area of 84.62%. And the tidal channel having been cut off by the project resulted in isolating the buildup restoration area from seawater, and reshaping completely the plant habitat environment. So the hydrological and biological connectivity has been changed largely with the 47.79% decreased MCCI area and the 16.3% decreased zero-valued CIHBC area. However the AISBH non-zero-valued area increased 10.7%, and with the hidden worry of the decreased Grallatores number. From the connectivity prospective, three models presented a significant methodology to evaluate the complex impact on the estuary wetland habitat caused by the restoration project. In the long run, the ecological impacts should be highlighted to the change of tidal channel and the corresponding tidal issues, and the continuous and big loss of native plant spices such as S. salsa. The further study needs to explore the longer-term assessment of the ecological restoration project and its multiple effect in the future.

Resilience to drought of dryland wetlands threatened by climate change

Dryland wetlands are resilient ecosystems that can adapt to extreme periodic drought–flood episodes. Climate change projections show increased drought severity in drylands that could compromise wetland resilience and reduce important habitat services. These recognized risks have been difficult to evaluate due to our limited capacity to establish comprehensive relationships between flood–drought episodes and vegetation responses at the relevant spatiotemporal scales. We address this issue by integrating detailed spatiotemporal flood–drought simulations with remotely sensed vegetation responses to water regimes in a dryland wetland known for its highly variable inundation. We show that a combination of drought tolerance and dormancy strategies allow wetland vegetation to recover after droughts and recolonize areas invaded by terrestrial species. However, climate change scenarios show widespread degradation during drought and limited recovery after floods. Importantly, the combination of degradation extent and increase in drought duration is critical for the habitat services wetland systems provide for waterbirds and fish.

Coupling environment and physiology to predict effects of climate change on the taxonomic and functional diversity of fish assemblages in the Murray-Darling Basin, Australia

This study uses species distribution modeling and physiological and functional traits to predict the impacts of climate change on native freshwater fish in the Murray-Darling Basin, Australia. We modelled future changes in taxonomic and functional diversity in 2050 and 2080 for two scenarios of carbon emissions, identifying areas of great interest for conservation. Climatic-environmental variables were used to model the range of 23 species of native fish under each scenario. The consensus model, followed by the physiological filter of lethal temperature was retained for interpretation. Our study predicts a severe negative impact of climate change on both taxonomic and functional components of ichthyofauna of the Murray-Darling Basin. There was a predicted marked contraction of species ranges under both scenarios. The predictions showed loss of climatically suitable areas, species and functional characters. There was a decrease in areas with high values of functional richness, dispersion and uniqueness. Some traits are predicted to be extirpated, especially in the most pessimistic scenario. The climatic refuges for fish fauna are predicted to be in the southern portion of the basin, in the upper Murray catchment. Incorporating future predictions about the distribution of ichthyofauna in conservation management planning will enhance resilience to climate change.

The Landscape Ecology of Rivers: from Patch-Based to Spatial Network Analyses

Purpose of Review

We synthesize recent methodological and conceptual advances in the field of riverscape ecology, emphasizing areas of synergy with current research in landscape ecology.

Recent Findings

Recent advances in riverscape ecology highlight the need for spatially explicit examinations of how network structure influences ecological pattern and process, instead of the simple linear (upstream-downstream) view. Developments in GIS, remote sensing, and computer technologies already offer powerful tools for the application of patch- and gradient-based models for characterizing abiotic and biotic heterogeneity across a range of spatial and temporal scales. Along with graph-based analyses and spatial statistical stream network models (i.e., geostatistical modelling), these approaches offer improved capabilities for quantifying spatial and temporal heterogeneity and connectivity relationships, thereby allowing for rigorous and high-resolution analyses of pattern, process, and scale relationships.

Summary

Spatially explicit network approaches are able to quantify and predict biogeochemical, hydromorphological, and ecological patterns and processes more precisely than models based on longitudinal or lateral riverine gradients alone. Currently, local habitat characteristics appear to be more important than spatial effects in determining population and community dynamics, but this conclusion may change with direct quantification of the movement of materials, energy, and organisms along channels and across ecosystem boundaries—a key to improving riverscape ecology. Coupling spatially explicit riverscape models with optimization approaches will improve land protection and water management efforts, and help to resolve the land sharing vs. land sparing debate.