University of Alcalá

About: University of Alcalá is a education organization based out in Alcalá de Henares, Spain. It is known for research contribution in the topics: Population & Receptor. The organization has 10795 authors who have published 20718 publications receiving 410089 citations. The organization is also known as: University of Alcala & University of Alcala de Henares.

Restoration enhances wetland biodiversity and ecosystem service supply, but results are context-dependent: a meta-analysis.

Abstract: Wetlands are valuable ecosystems because they harbor a huge biodiversity and provide key services to societies. When natural or human factors degrade wetlands, ecological restoration is often carried out to recover biodiversity and ecosystem services (ES). Although such restorations are routinely performed, we lack systematic, evidence-based assessments of their effectiveness on the recovery of biodiversity and ES. Here we performed a meta-analysis of 70 experimental studies in order to assess the effectiveness of ecological restoration and identify what factors affect it. We compared selected ecosystem performance variables between degraded and restored wetlands and between restored and natural wetlands using response ratios and random-effects categorical modeling. We assessed how context factors such as ecosystem type, main agent of degradation, restoration action, experimental design, and restoration age influenced post-restoration biodiversity and ES. Biodiversity showed excellent recovery, though the precise recovery depended strongly on the type of organisms involved. Restored wetlands showed 36% higher levels of provisioning, regulating and supporting ES than did degraded wetlands. In fact, wetlands showed levels of provisioning and cultural ES similar to those of natural wetlands; however, their levels of supporting and regulating ES were, respectively, 16% and 22% lower than in natural wetlands. Recovery of biodiversity and of ES were positively correlated, indicating a win-win restoration outcome. The extent to which restoration increased biodiversity and ES in degraded wetlands depended primarily on the main agent of degradation, restoration actions, experimental design, and ecosystem type. In contrast, the choice of specific restoration actions alone explained most differences between restored and natural wetlands. These results highlight the importance of comprehensive, multi-factorial assessment to determine the ecological status of degraded, restored and natural wetlands and thereby evaluate the effectiveness of ecological restorations. Future research on wetland restoration should also seek to identify which restoration actions work best for specific habitats.

Street-view change detection with deconvolutional networks

Abstract: We propose a system for performing structural change detection in street-view videos captured by a vehicle-mounted monocular camera over time. Our approach is motivated by the need for more frequent and efficient updates in the large-scale maps used in autonomous vehicle navigation. Our method chains a multi-sensor fusion SLAM and fast dense 3D reconstruction pipeline, which provide coarsely registered image pairs to a deep Deconvolutional Network (DN) for pixel-wise change detection. We investigate two DN architectures for change detection, the first one is based on the idea of stacking contraction and expansion blocks while the second one is based on the idea of Fully Convolutional Networks. To train and evaluate our networks we introduce a new urban change detection dataset which is an order of magnitude larger than existing datasets and contains challenging changes due to seasonal and lighting variations. Our method outperforms existing literature on this dataset, which we make available to the community, and an existing panoramic change detection dataset, demonstrating its wide applicability.