Web-based interface for environmental niche modelling

Marine species are subject to anthropogenic impacts, such as noise pollution, marine litter, and direct impact collisions. While there are efforts in the marine community and crowd-sourcing to report the occurrence of marine species, not enough projects explore the prediction of where such animals may be. This dissertation analyzes the state of the art in species distribution model ing (SDM) systems, capable of reporting and predicting marine biodiversity. The proposal implements the algorithms for predicting species through publicly avail able repositories of data, provides means to ease the upload and management of occurrence points as well as methods for prediction analysis. A web-based user interface is proposed using Ecological Niche Modelling (ENM) as an automated alerting mechanism towards ecological awareness. Performed user studies evaluate marine biodiversity concerns from fisherman and whale-watching sea-vessels, assessing attitudes, threats, values, and motiva tion of both samples. Further, biologists and experts on ENMs will evaluate the workflow and interface, reviewing the proposal’s potential to enable ecologists to create solutions for their custom problems using simple protocols without the need for any third-party entities and extensive knowledge in programming.Espécies marinhas estão sujeitas a impactos antropogênicos, tais como poluição sonora, lixo marinho, e colisões com tráfego marinho. Apesar de existirem al guns esforços da comunidade marinha e crowdsourcing relativamente ao registo de ocorrências de biodiversidade marinha, não existem projeto suficientes que exploram as previsões de onde estas espécies poderão estar. Esta dissertação analisa o estado da arte em sistemas de modelação de dis tribuição de espécies, capazes de relatar e prever biodiversidade marinha. A pro posta implementa os algoritmos para prever espécies por meio de repositórios consolidados de dados disponíveis online, fornece meios para facilitar o carrega mento e gestão de pontos de ocorrência, bem como métodos para análise das previsões. Uma interface web de utilizador é proposta utilizando Ecological Niche Modeling como um mecanismo de alerta automatizado para incrementar a con sciência ecológica. Os estudos do sistema irão avaliar as preocupações relativas a biodiversi dade marinha de embarcações de pesca e navios de observação de baleias. Desta forma é possível determinar atitudes, ameaças, valores e motivação de ambas as amostras para com a biodiversidade marinha. Além disso, biólogos e espe cialistas nesta tipologia de sistemas, avaliarão o fluxo de trabalho e a inter face desenvolvida, avaliando o potencial do sistema, permitindo aos ecologistas criar soluções personalizados através de protocolos simples, sem a necessidade de quaisquer entidades terceirizadas e conhecimento em programação

Sustaining Economic Exploitation of Complex Ecosystems in Computational Models of Coupled Human-Natural Networks

Understanding ecological complexity has stymied scientists for decades. Recent elucidation of the famously coined "devious strategies for stability in enduring natural systems" has opened up a new field of computational analyses of complex ecological networks where the nonlinear dynamics of many interacting species can be more realistically mod-eled and understood. Here, we describe the first extension of this field to include coupled human-natural systems. This extension elucidates new strategies for sustaining extraction of biomass (e.g., fish, forests, fiber) from ecosystems that account for ecological complexity and can pursue multiple goals such as maximizing economic profit, employment and carbon sequestration by ecosystems. Our more realistic modeling of ecosystems helps explain why simpler "maxi-mum sustainable yield" bioeconomic models underpinning much natural resource extraction policy leads to less profit, biomass, and biodiversity than predicted by those simple models. Current research directions of this integrated natu-ral and social science include applying artificial intelligence, cloud computing, and multiplayer online games

The Hierarchic treatment of marine ecological information from spatial networks of benthic platforms

Measuring biodiversity simultaneously in different locations, at different temporal scales, and over wide spatial scales is of strategic importance for the improvement of our understanding of the functioning of marine ecosystems and for the conservation of their biodiversity. Monitoring networks of cabled observatories, along with other docked autonomous systems (e.g., Remotely Operated Vehicles [ROVs], Autonomous Underwater Vehicles [AUVs], and crawlers), are being conceived and established at a spatial scale capable of tracking energy fluxes across benthic and pelagic compartments, as well as across geographic ecotones. At the same time, optoacoustic imaging is sustaining an unprecedented expansion in marine ecological monitoring, enabling the acquisition of new biological and environmental data at an appropriate spatiotemporal scale. At this stage, one of the main problems for an effective application of these technologies is the processing, storage, and treatment of the acquired complex ecological information. Here, we provide a conceptual overview on the technological developments in the multiparametric generation, storage, and automated hierarchic treatment of biological and environmental information required to capture the spatiotemporal complexity of a marine ecosystem. In doing so, we present a pipeline of ecological data acquisition and processing in different steps and prone to automation. We also give an example of population biomass, community richness and biodiversity data computation (as indicators for ecosystem functionality) with an Internet Operated Vehicle (a mobile crawler). Finally, we discuss the software requirements for that automated data processing at the level of cyber-infrastructures with sensor calibration and control, data banking, and ingestion into large data portals.Peer ReviewedPostprint (published version

A standard protocol for reporting species distribution models

Species distribution models (SDMs) constitute the most common class of models across ecology, evolution and conservation. The advent of ready-to-use software packages and increasing availability of digital geoinformation have considerably assisted the application of SDMs in the past decade, greatly enabling their broader use for informing conservation and management, and for quantifying impacts from global change. However, models must be fit for purpose, with all important aspects of their development and applications properly considered. Despite the widespread use of SDMs, standardisation and documentation of modelling protocols remain limited, which makes it hard to assess whether development steps are appropriate for end use. To address these issues, we propose a standard protocol for reporting SDMs, with an emphasis on describing how a study's objective is achieved through a series of modeling decisions. We call this the ODMAP (Overview, Data, Model, Assessment and Prediction) protocol, as its components reflect the main steps involved in building SDMs and other empirically-based biodiversity models. The ODMAP protocol serves two main purposes. First, it provides a checklist for authors, detailing key steps for model building and analyses, and thus represents a quick guide and generic workflow for modern SDMs. Second, it introduces a structured format for documenting and communicating the models, ensuring transparency and reproducibility, facilitating peer review and expert evaluation of model quality, as well as meta-analyses. We detail all elements of ODMAP, and explain how it can be used for different model objectives and applications, and how it complements efforts to store associated metadata and define modelling standards. We illustrate its utility by revisiting nine previously published case studies, and provide an interactive web-based application to facilitate its use. We plan to advance ODMAP by encouraging its further refinement and adoption by the scientific community