Complementary network-based approaches for exploring genetic structure and functional connectivity in two vulnerable, endemic ground squirrels

The persistence of small populations is influenced by genetic structure and functional connectivity. We used two network-based approaches to understand the persistence of the northern Idaho ground squirrel (Urocitellus brunneus) and the southern Idaho ground squirrel (U. endemicus), two congeners of conservation concern. These graph theoretic approaches are conventionally applied to social or transportation networks, but here are used to study population persistence and connectivity. Population graph analyses revealed that local extinction rapidly reduced connectivity for the southern species, while connectivity for the northern species could be maintained following local extinction. Results from gravity models complemented those of population graph analyses, and indicated that potential vegetation productivity and topography drove connectivity in the northern species. For the southern species, development (roads) and small-scale topography reduced connectivity, while greater potential vegetation productivity increased connectivity. Taken together, the results of the two network-based methods (population graph analyses and gravity models) suggest the need for increased conservation action for the southern species, and that management efforts have been effective at maintaining habitat quality throughout the current range of the northern species. To prevent further declines, we encourage the continuation of management efforts for the northern species, whereas conservation of the southern species requires active management and additional measures to curtail habitat fragmentation. Our combination of population graph analyses and gravity models can inform conservation strategies of other species exhibiting patchy distributions

Quantifying cross-scale patch contributions to spatial connectivity

Context: Connectivity between habitat patches is vital for ecological processes at multiple scales. Traditional metrics do not measure the scales at which individual habitat patches contribute to the overall ecological connectivity of the landscape. Connectivity has previously been evaluated at several different scales based on the dispersal capabilities of particular organisms, but these approaches are data-heavy and conditioned on just a few species. Objectives: Our objective was to improve cross-scale measurement of connectivity by developing and testing a new landscape metric, cross-scale centrality. Methods: Cross-scale centrality (CSC) integrates over measurements of patch centrality at different scales (hypothetical dispersal distances) to quantify the cross-scale contribution of each individual habitat patch to overall landscape or seascape connectivity. We tested CSC against an independent metapopulation simulation model and demonstrated its potential application in conservation planning by comparison to an alternative approach that used individual dispersal data. Results: CSC correlated significantly with total patch occupancy across the entire landscape in our metapopulation simulation, while being much faster and easier to calculate. Standard conservation planning software (Marxan) using dispersal data was weaker than CSC at capturing locations with high cross-scale connectivity. Conclusions: Metrics that measure pattern across multiple scales are much faster and more efficient than full simulation models and more rigorous and interpretable than ad hoc incorporation of connectivity into conservation plans. In reality, connectivity matters for many different organisms across many different scales. Metrics like CSC that quantify landscape pattern across multiple different scales can make a valuable contribution to multi-scale landscape measurement, planning, and management

Graph models of habitat mosaics

Graph theory is a body of mathematics dealing with problems of connectivity, flow, and routing in networks ranging from social groups to computer networks. Recently, network applications have erupted in many fields, and graph models are now being applied in landscape ecology and conservation biology, particularly for applications couched in metapopulation theory. In these applications, graph nodes represent habitat patches or local populations and links indicate functional connections among populations (i.e. via dispersal). Graphs are models of more complicated real systems, and so it is appropriate to review these applications from the perspective of modelling in general. Here we review recent applications of network theory to habitat patches in landscape mosaics. We consider (1) the conceptual model underlying these applications; (2) formalization and implementation of the graph model; (3) model parameterization; (4) model testing, insights, and predictions available through graph analyses; and (5) potential implications for conservation biology and related applications. In general, and for a variety of ecological systems, we find the graph model a remarkably robust framework for applications concerned with habitat connectivity. We close with suggestions for further work on the parameterization and validation of graph models, and point to some promising analytic insights. © 2009 Blackwell Publishing Ltd/CNRS

Optimization of canopy conductance models from concurrent measurements of sap flow and stem water potential on Drooping Sheoak in South Australia

This project is supported by National Centre for Groundwater Research and Training (NCGRT, Australia). The first author is supported by China Scholarship Council and NCGRT for his PhD study at Flinders University of South Australia. Xiang Xu and Yunhui Guo provided assistance in the field. Constructive comments and suggestion from three anonymous reviewers significantly improve the manuscript. This article also appears in: Patterns in Soil-Vegetation-Atmosphere Systems: Monitoring, Modelling and Data Assimilation.Peer reviewedPublisher PD

Is the Hyporheic Zone Relevant beyond the Scientific Community?

Rivers are important ecosystems under continuous anthropogenic stresses. The hyporheic zone is a ubiquitous, reactive interface between the main channel and its surrounding sediments along the river network. We elaborate on the main physical, biological, and biogeochemical drivers and processes within the hyporheic zone that have been studied by multiple scientific disciplines for almost half a century. These previous efforts have shown that the hyporheic zone is a modulator for most metabolic stream processes and serves as a refuge and habitat for a diverse range of aquatic organisms. It also exerts a major control on river water quality by increasing the contact time with reactive environments, which in turn results in retention and transformation of nutrients, trace organic compounds, fine suspended particles, and microplastics, among others. The paper showcases the critical importance of hyporheic zones, both from a scientific and an applied perspective, and their role in ecosystem services to answer the question of the manuscript title. It identifies major research gaps in our understanding of hyporheic processes. In conclusion, we highlight the potential of hyporheic restoration to efficiently manage and reactivate ecosystem functions and services in river corridors. View Full-Tex

FluTO: Graded Multiscale Fluid Topology Optimization using Neural Networks

Fluid-flow devices with low dissipation, but high contact area, are of importance in many applications. A well-known strategy to design such devices is multi-scale topology optimization (MTO), where optimal microstructures are designed within each cell of a discretized domain. Unfortunately, MTO is computationally very expensive since one must perform homogenization of the evolving microstructures, during each step of the homogenization process. As an alternate, we propose here a graded multiscale topology optimization (GMTO) for designing fluid-flow devices. In the proposed method, several pre-selected but size-parameterized and orientable microstructures are used to fill the domain optimally. GMTO significantly reduces the computation while retaining many of the benefits of MTO. In particular, GMTO is implemented here using a neural-network (NN) since: (1) homogenization can be performed off-line, and used by the NN during optimization, (2) it enables continuous switching between microstructures during optimization, (3) the number of design variables and computational effort is independent of number of microstructure used, and, (4) it supports automatic differentiation, thereby eliminating manual sensitivity analysis. Several numerical results are presented to illustrate the proposed framework

Advances in Sustainable River Management

The main objective of this Special Issue is to contribute in understanding and provide science-based knowledge, new ideas/approaches and solutions in sustainable river management, to improve water management policies and practices following different environmental requirements aspects

Modified home range kernel density estimators that take environmental interactions into account

International audienceBackground: Kernel density estimation (KDE) is a major tool in the movement ecologist toolbox that is used to delineate where geo-tracked animals spend their time. Because KDE bandwidth optimizers are sensitive to temporal autocorrelation, statistically-robust alternatives have been advocated, first, data-thinning procedures, and more recently, autocorrelated kernel density estimation (AKDE). These yield asymptotically consistent, but very smoothed distributions, which may feature biologically unrealistic aspects such as spilling beyond impassable borders.Method: I introduce a semi-parametric variant of AKDE designed to extrapolate more realistic home range shapes by incorporating movement mechanisms into the bandwidth optimizer and into the base kernels. I implement a first approximative version based on the step selection framework. This method allows accommodating land cover selection, permeability of linear features, and attraction for select landscape features when delineating home ranges.Results: In a plains zebra (Equus quagga), the reluctance to cross a railway, the avoidance of dense woodland, and the preference for grassland when foraging created significant differences between the estimated home range contours by the new and by previous methods.Conclusion: There is a tradeoff to find between fully parametric density estimators, which can be very realistic but need to be provided with a good model and adequate environmental data, and non-parametric density estimators, which are more widely applicable and asymptotically consistent, but whose details are bandwidth-limited. The proposed semi-parametric approach attempts to strike this balance, but I outline a few areas of future improvement. I expect the approach to find its use in studies that compare extrapolated resource availability and interpolated resource use, in order to discover the movement mechanisms that we need to improve the extrapolations

Ecological Security Pattern Analysis Based on InVEST and Least-Cost Path Model: A Case Study of Dongguan Water Village

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Assessment of check dams’ role in flood hazard mapping in a semi-arid environment

This study aimed to examine flood hazard zoning and assess the role of check dams as effective hydraulic structures in reducing flood hazards. To this end, factors associated with topographic, hydrologic and human characteristics were used to develop indices for flood mapping and assessment. These indices and their components were weighed for flood hazard zoning using two methods: (i) a multi-criterion decision-making model in fuzzy logic and (ii) entropy weight. After preparing the flood hazard map by using the above indices and methods, the characteristics of the change‐point were used to assess the role of the check dams in reducing flood risk. The method was used in the Ilanlu catchment, located in the northwest of Hamadan province, Iran, where it is prone to frequent flood events. The results showed that the area of ‘very low’, ‘low’ and ‘moderate’ flood hazard zones increased from about 2.2% to 7.3%, 8.6% to 19.6% and 22.7% to 31.2% after the construction of check dams, respectively. Moreover, the area of ‘high’ and ‘very high’ flood hazard zones decreased from 39.8% to 29.6%, and 26.7% to 12.2%, respectively