Corrigendum: The Design and Construction of an Ecosystem Simulation Workbench (2019 IOP Conf. Ser.: Earth Environ. Sci. 515 012015)

Please see Article PDF for corrigendum text.

Machine-learning emulation of a forest biogeochemistry model for efficient biosphere optimization

<div> <div> <div> <p>Management controls the spatial configuration of a number of landscapes globally, from forests to rangelands. The majority of landcover change and all land-use change is the result of human decision-making. As human populations and global temperatures continue to increase, an engineering approach is needed to ensure the persistence of biological diversity and natural capital critical to human well-being. Such an approach may be based on manipulating ecosystems to achieve desired future states, informed by the latest simulation models. Models of the land surface are now being used to inform policy in the form of planning and management practices. This often involves the application of models that include spatial dynamics and operate at a landscape scale. The strong correspondence between the resolution and extent of modeling and management activities at this scale, and ability to efficiently simulate the decadal-to-centennial time-scales of interest, provide managers with a credible scientific tool for anticipating future land states under different scenarios. The importance of such tools to managers has grown dramatically with the challenges posed by anthropogenic climate change. As ecosystem simulation models continually improve in precision, accuracy, and robustness, we posit that models may be mathematically optimized as a basis for optimizing the management of real-world systems. Since current ecosystem simulation models are coarse approximations of highly complex and dynamic real-world systems, such optimizations should ideally account for uncertainty and physical or biochemical constraints, thereby improving the tractability of the optimization problem. In this work, we demonstrate the emulation and optimization of a forest biogeochemistry model from the SORTIE-PPA family of models. In doing so, we provide the first demonstration of the concept of biosphere optimization (Erickson 2015), which may one day be extended to include computational genetic manipulation experiments. To perform this work, we utilize the open-source Earth-systems Research and Development Environment (ERDE) library, which contains built-in functions for performing these and other analyses with land models, with a particular focus on forests.</p> </div> </div> </div>

Ecosystem models of Lake Victoria (East Africa): exploring the sensitivity of ecosystem effects of fishing to model choice

Ecosystem simulation models are valuable tools for strengthening and promoting ecosystem-based fisheries management (EBFM). However, utility of these models in practical fisheries management is often undermined by lack of simple means to test the effect of uncertainty on model outputs. Recently, the use of multiple ecosystem models has been recommended as an ‘insurance’ against effects of uncertainty that comes with modelling complex systems. The assumption is that if models with different structure and formulation give consistent results, then, policy prescriptions are robust (i.e. less sensitive to model choice). However, information on the behaviour of trends from structurally-distinct ecosystem models with respect to changes in fishing conditions is limited, especially for freshwater systems. In this study, we compared outputs of two ecosystem models, Ecopath with Ecosim (EwE) and Atlantis, for Lake Victoria under different fishing pressure scenarios. We compared model behaviour at the ecosystem level, and also at a level of functional groups. At functional group level, we determined two questions: what is the change in the targeted group, and what are the consequent effects in other parts of the system? Overall results suggest that different model formulations can provide similar qualitative predictions (direction of change), especially for targeted groups with similar trophic interactions and adequate data for parameterization and calibration. However, considerable variations in predictions (where models predict opposite trends) may also occur due to inconsistencies in the strength of the aggregate multi-species interactions between species and models, and not necessarily due to model detail and complexity. Therefore, with more information and data, especially on diet, and comparable representation of feeding interactions across models, ecosystem models with distinct structure and formulation can give consistent policy evaluations for most biological groups.

MitsuDomoe: Ecosystem Simulation of Virtual Creatures in Mixed Reality Petri Dish

In this study, we propose the use of mixed reality (MR) for the purposes of biological education. Our objective is to create an interactive edutainment MR framework for users to learn about nature and human beings. MitsuDomoe, an interactive ecosystem simulator of virtual creatures in a petri dish, comprises three species of primitive artificial creatures. MitsuDomoe simulates the predation chain of the virtual creatures in the petri dish, and users can interact with this ecosystem via the petri dish interface. Users can also experience immersive observation by wearing HMD. By combining the MR petri dish and immersive virtual reality (VR) interfaces, we synergistically improve user understanding of the experience.

Using ecosystem simulation models to teach about the ‘resilient nature’ / Χρησιμοποιώντας μοντέλα προσομοίωσης οικοσυστημάτων για τη διδασκαλία της «ελαστικής» φύσης

Το παρόν άρθρο αφορά την ανάπτυξη μοντέλων NetLogo τα οποία προσομοιώνουν την πορεία οικοσυστημάτων που διαταράσσονται ή προστατεύονται και βασίζονται σε ευρήματα της σύγχρονης οικολογικής έρευνας. Τα τέσσερα μοντέλα που παρουσιάζονται ενσωματώθηκαν σε ένα μαθησιακό περιβάλλον που στοχεύει να υποστηρίξει μη βιολόγους φοιτητές (α) στην αντικατάστασή της ιδέας της «φύσης σε ισορροπία» από τη σύγχρονη ιδέα της «ελαστικής» φύσης, και (β) στην αξιοποίηση αυτής της αντίληψης για την ενίσχυση «δεξιοτήτων συστημικής σκέψης». Κάθε μοντέλο έχει δύο εκδοχές που προσομοιώνουν δύο διαφορετικές εκδοχές της πορείας του οικοσυστήματος ανάλογα με συγκεκριμένες αρχικές συνθήκες ή δράσεις στην προσπάθεια επαναφοράς. Στις μελέτες περίπτωσης που πραγματοποιήσαμε, οι φοιτητές σε τριάδες διερεύνησαν τα μοντέλα με τη βοήθεια φύλλων εργασίας, που τους ζητούσαν να κάνουν προβλέψεις για την πορεία του υπό μελέτη οικοσυστήματος και έπειτα να τις ελέγξουν «τρέχοντας» το μοντέλο. Οι μισές τριάδες των φοιτητών ασχολήθηκαν με την 1η εκδοχή κάθε μοντέλου και οι άλλες μισές με τη 2η . Στο τέλος κάθε μαθήματος, oι δύο διαφορετικές εκδοχές της πορείας του οικοσυστήματος που προσομοίωνε κάθε μοντέλο γίνονταν θέμα συζήτησης όλης της τάξης ώστε να αναδειχθεί η ιδέα της ενδεχομενικότητας. Τα αποτελέσματα της λειτουργίας της τελευταίας εκδοχής του μαθησιακού περιβάλλοντος είναι ενθαρρυντικά και δημοσιεύονται σε άλλα άρθρα μας.