Allocating Logging Rights in Peruvian Amazonia—Does It Matter to Be Local?

Peer reviewe

What Data to Use for Forest Conservation Planning? A Comparison of Coarse Open and Detailed Proprietary Forest Inventory Data in Finland

The boreal region is facing intensifying resource extraction pressure, but the lack of comprehensive biodiversity data makes operative forest conservation planning difficult. Many countries have implemented forest inventory schemes and are making extensive and up-to-date forest databases increasingly available. Some of the more detailed inventory databases, however, remain proprietary and unavailable for conservation planning. Here, we investigate how well different open and proprietary forest inventory data sets suit the purpose of conservation prioritization in Finland. We also explore how much priorities are affected by using the less accurate but open data. First, we construct a set of indices for forest conservation value based on quantitative information commonly found in forest inventories. These include the maturity of the trees, tree species composition, and site fertility. Secondly, using these data and accounting for connectivity between forest types, we investigate the patterns in conservation priority. For prioritization, we use Zonation, a method and software for spatial conservation prioritization. We then validate the prioritizations by comparing them to known areas of high conservation value. We show that the overall priority patterns are relatively consistent across different data sources and analysis options. However, the coarse data cannot be used to accurately identify the high-priority areas as it misses much of the fine-scale variation in forest structures. We conclude that, while inventory data collected for forestry purposes may be useful for forest conservation purposes, it needs to be detailed enough to be able to account for more fine-scaled features of high conservation value. These results underline the importance of making detailed inventory data publicly available. Finally, we discuss how the prioritization methodology we used could be integrated into operative forest management, especially in countries in the boreal zone.Peer reviewe

Prospects and challenges for social media data in conservation science

Peer reviewe

Running a Zonation Planning Project

Zonation is decision support software for land use planning, including uses such as traditional design of conservation area networks or spatial impact avoidance. It is capable of data rich, large scale, high-resolution spatial prioritization. Whether using Zonation for scientific research or in real-life planning, running a successful project involves several project stages that often proceed in a somewhat iterative fashion. This document provides an overview of what those stages are, and what types of issues should be considered when planning to use Zonation. This information is intended for any individual or organization that is considering making use of Zonation. The topics addressed here are those encountered before and after the Zonation prioritization analysis itself: - Budgeting for time and resources - Setting objectives and planning how to meet them - Building a model for spatial prioritization - Data requirements and pre-processing - Setting up and organizing Zonation input files - Visualizing and interpreting the results - Creating planning products Zonation projects are also demonstrated through a set of case-studies that range from national to global scales

Global priorities for national carnivore conservation under land use change

Peer reviewe

Extracting locations from sport and exercise-related social media messages using a neural network-based bilingual toponym recognition model

Sport and exercise contribute to health and well-being in cities. While previous research has mainly focused on activities at specific locations such as sport facilities, "informal sport" that occur at arbitrary locations across the city have been largely neglected. Such activities are more challenging to observe, but this challenge may be addressed using data collected from social media platforms, because social media users regularly generate content related to sports and exercise at given locations. This allows studying all sport, including those "informal sport" which are at arbitrary locations, to better understand sports and exercise-related activities in cities. However, user-generated geographical information available on social media platforms is becoming scarcer and coarser. This places increased emphasis on extracting location information from free-form text content on social media, which is complicated by multilingualism and informal language. To support this effort, this article presents an end-to-end deep learning-based bilingual toponym recognition model for extracting location information from social media content related to sports and exercise. We show that our approach outperforms five state-of-the-art deep learning and machine learning models. We further demonstrate how our model can be deployed in a geoparsing framework to support city planners in promoting healthy and active lifestyles.Peer reviewe

Academic publishing empires need to go

Non peer reviewe

Seasonal fluctuation of riverine navigation and accessibility in Western Amazonia : An analysis combining a cost-efficient GPS-based observation system and interviews

Accessibility and transportation possibilities are key factors influencing societal conditions and land use patterns in rural areas. Thus, information on the spatial patterns of accessibility and transportation can be of paramount importance in understanding regional differences in development, human livelihood and land use patterns. Analysing spatio-temporal transportation patterns is particularly challenging in areas where everyday transportation is based on unscheduled public transportation and a naturally controlled seasonal transportation network, such as rivers. Here, our aim is to provide information on the seasonal dynamics of riverine transportation and its effects on accessibility patterns in Peruvian Amazonia. We analysed riverine transportation speeds using a low-cost GPS-based riverboat observation system. Spatio-temporal accessibility patterns were generalised from the GPS-observations that were classified according to seasons into the high water season, intermediate season and low water season. We show that navigation along the rivers has a clear seasonal and directional (upstream/downstream) variation, which varies with different types of rivers based on channel morphology. In addition, we conducted interviews with local people to study their perceptions of the seasonal changes in navigation and the accuracy of transportation schedules. As the travel distances in Peruvian Amazonia are generally long, seasonal and directional differences have clear impacts on the overall accessibility patterns in the area and on the livelihoods of riverine inhabitants. Furthermore, the lack of clearly scheduled transportation causes considerable uncertainty about transportation options for local communities. The baseline information of the seasonal and directional variation of riverine transportation and travel speeds provided by our work is usable in further accessibility and livelihood analyses for Peruvian Amazonia, but it may also be useful in other areas relying on riverine transportation.Peer reviewe

Dynamic cities : Location-based accessibility modelling as a function of time

The concept of accessibility – the potential of opportunities for interaction – binds together the key physical components of urban structure: people, transport and social activity locations. Most often these components are dynamic in nature and hence the accessibility landscape changes in space and time based on people's mobilities and the temporality of the transport network and activity locations (e.g. services). Person-based accessibility approaches have been successful in incorporating time and space in the analyses and models. Still, the more broadly applied location-based accessibility modelling approaches have, on the other hand, often been static/atemporal in their nature. Here, we present a conceptual framework of dynamic location-based accessibility modelling that captures the dynamic temporality of all three accessibility components. Furthermore, we empirically test the proposed framework using novel data sources and tools. We demonstrate the impact of temporal aspects in accessibility modelling with two examples: by investigating food accessibility and its spatial equity. Our case study demonstrates how the conventional static location-based accessibility models tend to overestimate the access of people to potential opportunities. The proposed framework is universally applicable beyond the urban context, from local to global scale and on different temporal scales and multimodal transport systems. It also bridges the gap between location-based accessibility and person-based accessibility research.The concept of accessibility- the potential of opportunities for interaction- binds together the key physical components of urban structure: people, transport and social activity locations. Most often these components are dynamic in nature and hence the accessibility landscape changes in space and time based on people's mobilities and the temporality of the transport network and activity locations (e.g. services). Person-based accessibility approaches have been successful in incorporating time and space in the analyses and models. Still, the more broadly applied location-based accessibility modelling approaches have, on the other hand, often been static/atemporal in their nature. Here, we present a conceptual framework of dynamic location-based accessibility modelling that captures the dynamic temporality of all three accessibility components. Furthermore, we empirically test the proposed framework using novel data sources and tools. We demonstrate the impact of temporal aspects in accessibility modelling with two examples: by investigating food accessibility and its spatial equity. Our case study demonstrates how the conventional static location-based accessibility models tend to overestimate the access of people to potential opportunities. The proposed framework is universally applicable beyond the urban context, from local to global scale and on different temporal scales and multimodal transport systems. It also bridges the gap between location-based accessibility and person-based accessibility research.Peer reviewe