6809 research outputs found
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Using social media, machine learning and natural language processing to map multiple recreational beneficiaries
No full textInformation and numbers on the use and appreciation of nature are valuable information for protected area (PA) managers. A promising direction is the utilisation of social media, such as the photo-sharing website Flickr. Here we demonstrate a novel approach, borrowing techniques from machine learning (image analysis), natural Language processing (Latent Semantic Analysis (LSA)) and self-organising maps (SOM), to collect and interpret >20,000 photos from the Camargue region in Southern France. From the perspective of Cultural Ecosystem Services (CES), we assessed the relationship between the use of the Camargue delta and the presence of natural elements by consulting local managers. Clustering algorithms applied to results of the LSA data revealed six distinct user groups, which included those interested in nature, ornithology, religious pilgrimage, general tourists and aviation enthusiasts. For each group, we produced high-resolution spatial and seasonal maps, which matched known recreational attractions and annual festivals in the Camargue. The accuracy of the Group identification, and the spatial and temporal patterns of photo activity, in the Camargue delta were evaluated by local managers of the Camargue regional park. This study demonstrates how PA managers can harness social media to monitor recreation and improve their management decision making
Spatial and spectral pattern identification for the automatic selection of high-quality MODIS images
No full textRemote sensing is providing an increasing number of crucial data about Earth. Systematic revisitation time allows the analysis of long time series as well as imagery utilization in the most interesting moments. Nevertheless, the current huge amount of data makes essential the usage of automatic methods to select the best captures, as many of them are not useful because of clouds, shadows, etc. Because of that, one of the characteristics of the more recent missions is the distribution, along with the spectral data, of a large amount of quality ancillary datasets. These datasets can act synergistically in the aim of selecting the best quality images, but the criteria they provide are not always enough. Indeed, these datasets are often used on a per pixel basis and the spatial pattern of the different spectral bands is forgotten, so ignoring the key information they can provide for our goals.With this aim, our work takes one of the most successful instruments in remote sensing, MODIS, and demonstrates, through geostatistical techniques, that the role of the spatial patterns of the spectral bands can effectively improve image selection in a complex (for climate, relief, and vegetation and crop phenology) region of 63;700 km2. The results show that band 01 (red) is the preferred one, as it achieves a 13% higher success than when only using quality bands criteria: a 94% global accuracy (66 true classifications, and only four omissions and one commission error). A second, important finding, is that the geostatistical selection improves results when using any band, except for band 02 (NIR1), which makes our proposal potentially useful for most remote sensing missions. Finally, the method can be executed in a reasonable computing time due to previously developed high-performance computing techniques
Dataset of occurrence and incidence of pine processionary moth in Andalusia, south Spain
No full textThis dataset provides information about infestation caused by the pine processionary moth (Thaumetopoea pityocampa ([Denis & Schifferm?ller], 1775)) in pure or mixed pine woodlands and plantations in Andalusia. It represents a long-term series (1993-2015) containing 81,908 records that describe the occurrence and incidence of this species. Data were collected within a monitoring programme known as COPLAS, developed by the Regional Ministry of Environment and Territorial Planning of the Andalusian Regional Government within the frame of the Plan de Lucha Integrada contra la Procesionaria del Pino (Plan for Integrated Control Against the Pine Processionary Moth). In particular, this dataset includes 4,386 monitoring stands which, together with the campaign year, define the dataset events in Darwin Core Archive. Events are related with occurrence data which show if the species is present or absent. In turn, the event data have a measurement associated: degree of infestation
Explaining path-dependent rigidity traps: increasing returns, power, discourses, and entrepreneurship intertwined in social-ecological systems
No full textThe current, unprecedented rate of human development is causing major damages to Earth\u27s life-support systems. Therefore, the need for transitions toward sustainability in the use of natural resources and ecosystems has been extensively advocated. To be successful, such transitions must be guided by a sound understanding of the architecture of the policy and institutional designs of both the process of change and the target outcome. Here, we contribute to current research on the institutional conditions necessary for successful transitions toward sustainability in social-ecological systems, addressing two interrelated theoretic-analytical questions through an in-depth case study focused in the Do?ana region (Guadalquivir estuary, southwest Spain). First, we focus on the need for enhanced historical causal explanations of social-ecological systems stuck in maladaptive rigidity traps at present. Second, we focus on the explanatory potential of several factors for shaping maladaptive outcomes, at two different levels of analysis: political-economic interests, prevailing discourses and power, at a contextual level, and institutional entrepreneurship, at an endogenous level. In particular, we address that explanatory potential when the core logic of path dependence fails to predict maladaptive outcomes in a historical, evolutionary perspective. When this occurs, such outcomes are often qualified as unexpected, hence subject to contingency, because of their divergence from purported superior, optimal alternatives. We argue that contingency can be modulated away from randomness and better characterized as unpredictability, through the systematic inclusion of the mentioned factors into analysis. This would, in turn, increase our capacity to inform future policy and institutional transitional designs toward sustainability
Differences in the spatial structure of two Pinus cembra L. populations in the Carpathian Mountains
No full textPinus cembra L. is a key species of high elevation forest ecosystems in Europe. However, in most mountain ranges, its importance has declined considerably. Remnant populations are often isolated and their dynamics and functioning are not well understood. Here, we apply novel approaches in pattern analysis to two P. cembra populations in the Carpathian Mountains in order to identify commonalities and divergences in their spatial structure and dynamics. Four study sites (1.2 ha each) were investigated within the treeline ecotone in two protected areas that dier in terms of protection status. Based on height and diameter, the individuals were classified into three size-classes: sapling, intermediate and adult trees. Spatial distribution and interactions between tree sizes were analyzed using point pattern analysis. The overall structure of all trees was aggregated at a small distance and regular at a greater distance in the population from the Natura 2000 site (p = 0.002), while in the National Park population it was a random pattern. However, the general patterns do not apply to tree size classes and the relationship among them. In the Natura 2000 site, there was no correlation, all the trees were mixed, regardless of their size. In the National Park, the sapling and intermediate were strongly clustered (p = 0.001), but the adult trees were spatially separated from all juveniles, forming patches at a lower elevation. In both areas, spatial patterns indicate the dynamics of the P. cembra population. Whereas in the National Park population, there is evidence of an upward shift, which cannot be confirmed in Natura 2000, where size classes are completely mixed and the dynamic does not translate into an expansion of the population area. The spatial dierences between the two populations indicate that conservation strategies need to be developed more individually to support the regeneration of these isolated populations
Optimal control of invasive species through a dynamical systems approach
No full textEffectively dealing with invasive species is a pervasive problem in environmental management. The damages that stem from invasive species are well known. However, controlling them cost-effectively is an ongoing challenge, and Mathematical modeling and optimization are becoming increasingly popular as a tool to assist management. In this paper we investigate problems where optimal control theory has been implemented. We show that transforming these problems from state-costate systems to state-control systems provides the complete qualitative description of the optimal solution and leads to its theoretical expression for free terminal time problems. We apply these techniques to two case studies: one of feral cats in Australia, where we use logistic growth; and the other of wild-boars in Italy, where we include an Allee effect
Finding the essential: Improving conservation monitoring across scales
No full textTo account for progress towards conservation targets, monitoring systems should capture not only information on biodiversity but also knowledge on the dynamics of ecological processes and the related effects on human well-being. Protected areas represent complex social-ecological systems with strong human-nature interactions. They are able to provide relevant information about how global and local scale drivers (e.g., climate change, land use change) impact biodiversity and ecosystem services. Here we develop a framework that uses an ecosystem-focused approach to support managers in identifying essential variables in an integrated and scalable approach. We advocate that this approach can complement current essential variable developments, by allowing conservation managers to draw on system-level knowledge and theory of biodiversity and ecosystems to identify locally important variables that meet the local or sub-global needs for conservation data. This requires the development of system narratives and causal diagrams that pinpoints the social-ecological variables that represent the state and drivers of the different components, and their relationships. We describe a scalable framework that builds on system based narratives to describe all system components, the models used to represent them and the data needed. Considering the global distribution of protected areas, with an investment in standards, transparency, and on active data mobilisation strategies for essential variables, these have the potential to be the backbone of global biodiversity monitoring, benefiting countries, biodiversity observation networks and the global biodiversity community
Severe Wave-Body Interactions: a Potential-Flow HPC Method and its Strong Domain-Decomposition Coupling with a Level-Set Navier-Stokes Solver
No full textThe main objective of our ongoing research is to investigate wave loads on and motions of floating bodies in steep waves. For modelling non-linear water-wave and wave-body interaction problems, researchers can use two main classes of numerical methods, where the preferred choice depends on the features of the problem. One class consists of potential-flow solvers, which are efficient and accurate in simulating propagating waves. In this framework, we have proposed a method based on the high-order harmonic polynomial cell (HPC) method at the 32nd IWWWFB. In [1], its ability to simulate a variety of wave-propagation problems has been demonstrated in detail, even for steep waves close to breaking. The other class consists of more computationally expensive NavierStokes solvers, able to deal with problems involving wave breaking and fragmentation phenomena and/or important viscous effects. To benefit from the strengths of both classes of solvers, couplings between potentialflow and Navier-Stokes solvers have received increased attention in the research community during the last years. In this framework, in [2], we proposed a 2D strong Domain-Decomposition (DD) strategy between a Level-Set Navier-Stokes (LS-NS) solver and a non-linear potential-flow solver based on the boundary element method (BEM) to analyze a dam-breaking problem and subsequent wave impact on a vertical wall. Here, the HPC-based potential-flow (HPC-PF) solver\u27s capability to handle wave-body interactions, when viscous effects are limited, is documented by comparing against the BEM and available experiments. Then, a 2D strong DD strategy between the HPC-PF solver and the LS-NS solver is proposed to handle more general scenarios and enhancing accuracy and efficiency with respect to using the BEM solver
Scale effects on the performance of niche-based models of freshwater fish distributions
No full textNiche-based species distribution models (SDMs) have become an essential tool in conservation and restoration planning. Given the current threats to freshwater biodiversity, it is of fundamental importance to address scale effects on the performance of niche-based SDMs of freshwater species\u27 distributions. The scale effects are addressed here in the context of hierarchical catchment ordering, considered as counterpart to coarsening grainsize by increasing grid-cell size. We combine fish occurrence data from the Danube River Basin, the hierarchical catchment ordering and multiple environmental factors representing topographic, climatic and anthropogenic effects to model fish occurrence probability across multiple scales. We focus on 1st to 5th order catchments. The spatial scale (hierarchical catchment order) only marginally influences the mean performance of SDMs, however the uncertainty of the estimates increases with scale. Key predictors and their relative importance are scale and species dependent. Our findings have useful implications for choosing proper species dependent spatial scales for river rehabilitation measures, and for conservation planning in areas where fine grain species data are unavailable
Remotely sensed indicators and open-access biodiversity data to assess bird diversity patterns in Mediterranean rural landscapes
No full textBiodiversity monitoring at simultaneously fine spatial resolutions and large spatial extents is needed but limited by operational trade-offs and costs. Open-access data may be cost-effective to address those limitations. We test the use of open-access satellite imagery (NDVI texture variables) and biodiversity data, assembled from GBIF, to investigate the relative importance of variables of habitat extent and structure as indicators of bird community richness and dissimilarity in the Alentejo region (Portugal). Results show that, at the landscape scale, forest bird richness is better indicated by the availability of tree cover in the overall landscape than by the extent or structure of the forest habitats. Open-land birds also respond to landscape structure, namely to the spectral homogeneity and size of open-land patches and to the presence of perennial vegetation amid herbaceous habitats. Moreover, structure variables were more important than climate variables or geographic distance to explain community dissimilarity patterns at the regional scale. Overall, summer imagery, when perennial vegetation is more discernible, is particularly suited to inform indicators of forest and open-land bird community richness and dissimilarity, while spring imagery appears to be also useful to inform indicators of open-land bird richness