Evaluating static and dynamic landscape connectivity modelling using a 25-year remote sensing time series

Bishop‐Taylor, Robbi; Tulbure, Mirela G.; Broich, Mark

doi:10.1007/s10980-018-0624-1

Cited by 60 publications

(44 citation statements)

References 67 publications

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“…Sentinel-2 is an open-access resource that provides spatial data at a resolution useful and necessary for this task, and, despite its relatively recent release, effective long-term ecosystem monitoring at local, regional, and national levels is planned to be continuously ensured by this satellite. As such, considering the increasing Sentinel-2 temporal span, future studies on conservation planning incorporating information for longer periods, as it is actually done with other satellites [104], may be valuable because they more likely minimize the common pitfall of assuming stable environmental suitability, and therefore populations persistence, over time [105,106].…”

Section: Discussionmentioning

confidence: 99%

Predicting Microhabitat Suitability for an Endangered Small Mammal Using Sentinel-2 Data

et al. 2020

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Accurate mapping is a main challenge for endangered small-sized terrestrial species. Freely available spatio-temporal data at high resolution from multispectral satellite offer excellent opportunities for improving predictive distribution models of such species based on fine-scale habitat features, thus making it easier to achieve comprehensive biodiversity conservation goals. However, there are still few examples showing the utility of remote-sensing-based products in mapping microhabitat suitability for small species of conservation concern. Here, we address this issue using Sentinel-2 sensor-derived habitat variables, used in combination with more commonly used explanatory variables (e.g., topography), to predict the distribution of the endangered Cabrera vole (Microtus cabrerae) in agrosilvopastorial systems. Based on vole surveys conducted in two different seasons over a~176,000 ha landscape in Southern Portugal, we assessed the significance of each predictor in explaining Cabrera vole occurrence using the Boruta algorithm, a novel Random forest variant for dealing with high dimensionality of explanatory variables. Overall, results showed a strong contribution of Sentinel-2-derived variables for predicting microhabitat suitability of Cabrera voles. In particular, we found that photosynthetic activity (NDI45), specific spectral signal (SWIR1), and landscape heterogeneity (Rao's Q) were good proxies of Cabrera voles' microhabitat, mostly during temporally greener and wetter conditions. In addition to remote-sensing-based variables, the presence of road verges was also an important driver of voles' distribution, highlighting their potential role as refuges and/or corridors. Overall, our study supports the use of remote-sensing data to predict microhabitat suitability for endangered small-sized species in marginal areas that potentially hold most of the biodiversity found in human-dominated landscapes. We believe our approach can be widely applied to other species, for which detailed habitat mapping over large spatial extents is difficult to obtain using traditional descriptors. This would certainly contribute to improving conservation planning, thereby contributing to global conservation efforts in landscapes that are managed for multiple purposes.

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Section: Discussionmentioning

confidence: 99%

Predicting Microhabitat Suitability for an Endangered Small Mammal Using Sentinel-2 Data

et al. 2020

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“…Moreover, event-based modeling and data assimilation in low and dry periods were envisaged as pragmatic solutions to improve floodplain inundation forecast skill. Conceptualization of the outcomes of this study can be readily applied to improve the accuracy of long-term flow modeling in the MDB, thus providing a powerful tool to (i) support flood forecast and risk analysis (e.g., Domeneghetti et al, 2018), (ii) complement remote sensing-based investigations of surface flow connectivity and its ecological implications (e.g., Bishop-Taylor et al, 2015;Bishop-Taylor et al, 2018;Heimhuber et al, 2016Heimhuber et al, , 2017Huang et al, 2014;Tulbure et al, 2016), and (iii) support investigation of groundwater recharge due to flooding (e.g., Doble et al, 2014).…”

Section: Significance Of the Study Limitations And Future Workmentioning

confidence: 99%

Challenges, Opportunities, and Pitfalls for Global Coupled Hydrologic‐Hydraulic Modeling of Floods

Grimaldi

Schumann

Shokri

et al. 2019

Water Resources Research

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Flood modeling at the regional to global scale is a key requirement for equitable emergency and land management. Coupled hydrological‐hydraulic models are at the core of flood forecasting and risk assessment models. Nevertheless, each model is subject to uncertainties from different sources (e.g., model structure, parameters, and inputs). Understanding how uncertainties propagate through the modeling cascade is essential to invest in data collection, increase flood modeling accuracy, and comprehensively communicate modeling results to end users. This study used a numerical experiment to quantify the propagation of errors when coupling hydrological and hydraulic models for multiyear flood event modeling in a large basin, with large morphological and hydrological variability. A coupled modeling chain consisting of the hydrological model Hydrologiska Byråns Vattenbalansavdelning and the hydraulic model LISFLOOD‐FP was used for the prediction of floodplain inundation in the Murray Darling Basin (Australia), from 2006 to 2012. The impacts of discrepancies between simulated and measured flow hydrographs on the predicted inundation patterns were analyzed by moving from small upstream catchments to large lowland catchments. The numerical experiment was able to identify areas requiring tailored modeling solutions or data collection. Moreover, this study highlighted the high sensitivity of inundation volume and extent prediction to uncertainties in flood peak values and explored challenges in time‐continuous modeling. Accurate flood peak predictions, knowledge of critical morphological features, and an event‐based modeling approach were outlined as pragmatic solutions for more accurate prediction of large‐scale spatiotemporal patterns of flood dynamics, particularly in the presence of low‐accuracy elevation data.

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“…Although some recent studies highlighted the importance of accounting for temporal aspects in connectivity modeling (Alagador et al 2014, Mui et al 2017, only a few of them accounted for dispersal processes over generations (Saura et al 2014, de la Fuente et al 2018, the variation in importance of habitat patches in maintaining connectivity due to seasonal habitat change (Mui et al 2017, Bishop-Taylor et al 2018, or the implications of ephemeral patches and transient connectivity change in metapopulation dynamics (Reigada et al 2015, Perry andLee 2019). Yet, the importance of temporal dynamics of habitat patches has largely been ignored (Blonder et al 2012).…”

Section: Introductionmentioning

confidence: 99%

Importance of spatio–temporal connectivity to maintain species experiencing range shifts

et al. 2020

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Climate change can affect the habitat resources available to species by changing habitat quantity, suitability and spatial configuration, which largely determine population persistence in the landscape. In this context, dispersal is a central process for species to track their niche. Assessments of the amount of reachable habitat (ARH) using static snap‐shots do not account, however, for the temporal overlap of habitat patches that may enhance stepping‐stone effects. Here, we quantified the impacts of climate change on the ARH using a spatio–temporal connectivity model. We first explored the importance of spatio–temporal connectivity relative to purely spatial connectivity in a changing climate by generating virtual species distributions and analyzed the relative effects of changes in habitat quantity, suitability and configuration. Then, we studied the importance of spatio–temporal connectivity in three vertebrate species with divergent responses to climate change in North America (grey wolf, Canadian lynx and white‐tailed deer). We found that the spatio–temporal connectivity could enhance the stepping‐stone effect for species predicted to experience range contractions, and the relative importance of the spatio–temporal connectivity increased with the reduction in habitat quantity and suitability. Conversely, for species that are likely to expand their ranges, spatio–temporal connectivity had no additional contribution to improve the ARH. We also found that changes in habitat amount (quantity and suitability) were more influential than changes in habitat configuration in determining the relative importance of spatio–temporal connectivity. We conclude that spatio–temporal connectivity may provide less biased and more realistic estimates of habitat connectivity than purely spatial connectivity.

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Evaluating static and dynamic landscape connectivity modelling using a 25-year remote sensing time series

Cited by 60 publications

References 67 publications

Predicting Microhabitat Suitability for an Endangered Small Mammal Using Sentinel-2 Data

Predicting Microhabitat Suitability for an Endangered Small Mammal Using Sentinel-2 Data

Challenges, Opportunities, and Pitfalls for Global Coupled Hydrologic‐Hydraulic Modeling of Floods

Importance of spatio–temporal connectivity to maintain species experiencing range shifts

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