Drowning in data, thirsty for information and starved for understanding: A biodiversity information hub for cooperative environmental monitoring in South Africa
“…Global efforts to operationalize the collection of Essential Biodiversity Variables and establish global biodiversity observation networks (Pereira et al, 2013;Han et al, 2017;Turak et al, 2017), combined with parallel initiatives to promote improved data management, stewardship and uptake (Wilkinson et al, 2016;MacFadyen et al, 2022), make it clear that the past NBA workflows are inadequate and will greatly benefit from the incorporation of tools and platforms of the information age.…”
Section: Current Contextmentioning
confidence: 99%
“…As signatories to these agreements, parties need to report regularly against a series of indicators that draw on a wide range of biodiversity and environmental observations (including pressures and drivers). This data-to-knowledge pipeline is undergoing rapid change in the information age, with an explosion of available data and the evolution of new tools for analysis and information delivery (Wilkinson et al, 2016;MacFadyen et al, 2022). Policy, planning and decision-making bodies with a mandate over biodiversity conservation and sustainable use are set to benefit from these changes; if the supporting agencies can adapt their processes and avoid "drowning in data. "…”
South Africa’s National Biodiversity Assessment (NBA) is the primary tool for monitoring and reporting on the state of biodiversity, with a focus on spatial information and key indicators. The NBA distills information that informs policies and strategies, meets national and international reporting requirements, and helps prioritize limited resources for managing and conserving biodiversity. The three previous versions of the NBA (2004, 2011 and 2018) are in the form of detailed thematic technical reports and a synthesis report, served on a simple, static web page. Selected spatial products from the report are available via a dedicated web platform (http://nba.sanbi.org.za/). While all methods and data are clearly described in the technical reports, most of the underlying analyses are inaccessible, lacking reproducibility and transparency. This makes iterative updates to indicators or metrics challenging and inefficient, complicates version control, and exacerbates the risk of capacity, knowledge and data loss during staff turnover. To move the assessment process into the information age we aim to develop well documented and reproducible workflows, and to serve the indicators and their accompanying synthesis on an interactive web platform that facilitates uptake. Achieving these aims will deliver efficiency, greater transparency and trust in future NBA products and will strengthen communication and engagement with the content by the many different users of those products. While these visions will not be realized overnight, the skills and systems required to achieve them can be adaptively built towards an improved NBA that better serves the needs of our society.
“…Global efforts to operationalize the collection of Essential Biodiversity Variables and establish global biodiversity observation networks (Pereira et al, 2013;Han et al, 2017;Turak et al, 2017), combined with parallel initiatives to promote improved data management, stewardship and uptake (Wilkinson et al, 2016;MacFadyen et al, 2022), make it clear that the past NBA workflows are inadequate and will greatly benefit from the incorporation of tools and platforms of the information age.…”
Section: Current Contextmentioning
confidence: 99%
“…As signatories to these agreements, parties need to report regularly against a series of indicators that draw on a wide range of biodiversity and environmental observations (including pressures and drivers). This data-to-knowledge pipeline is undergoing rapid change in the information age, with an explosion of available data and the evolution of new tools for analysis and information delivery (Wilkinson et al, 2016;MacFadyen et al, 2022). Policy, planning and decision-making bodies with a mandate over biodiversity conservation and sustainable use are set to benefit from these changes; if the supporting agencies can adapt their processes and avoid "drowning in data. "…”
South Africa’s National Biodiversity Assessment (NBA) is the primary tool for monitoring and reporting on the state of biodiversity, with a focus on spatial information and key indicators. The NBA distills information that informs policies and strategies, meets national and international reporting requirements, and helps prioritize limited resources for managing and conserving biodiversity. The three previous versions of the NBA (2004, 2011 and 2018) are in the form of detailed thematic technical reports and a synthesis report, served on a simple, static web page. Selected spatial products from the report are available via a dedicated web platform (http://nba.sanbi.org.za/). While all methods and data are clearly described in the technical reports, most of the underlying analyses are inaccessible, lacking reproducibility and transparency. This makes iterative updates to indicators or metrics challenging and inefficient, complicates version control, and exacerbates the risk of capacity, knowledge and data loss during staff turnover. To move the assessment process into the information age we aim to develop well documented and reproducible workflows, and to serve the indicators and their accompanying synthesis on an interactive web platform that facilitates uptake. Achieving these aims will deliver efficiency, greater transparency and trust in future NBA products and will strengthen communication and engagement with the content by the many different users of those products. While these visions will not be realized overnight, the skills and systems required to achieve them can be adaptively built towards an improved NBA that better serves the needs of our society.
“…high uncertainty), this should improve with each iteration. Just developing the ecoinformatics pipeline required to collect and feed new observations to the model is a worthy pursuit in itself, because it can facilitate rapid delivery of relevant data to researchers and decision-makers (MacFadyen et al, 2022). Better still would be if the pipeline and potential forecasts delivered on multiple information needs for a region of interest.…”
Section: Introductionmentioning
confidence: 99%
“…While the ecological forecasting paradigm has gained much traction and shows great potential for facilitating rapid advances (Dietze & Lynch, 2019; https://ecofo recast.org/), several challenges remain. Some are logistical, such as the difficulty and expense of collecting sufficient new data and making it available at low enough latency to allow for a useful forecasting time-step or forecast horizon, or developing and maintaining the ecoinformatics pipeline required to build and update models (Fer et al, 2021;MacFadyen et al, 2022). These challenges can be a barrier to developing ecological forecasts in under-resourced environments, as is evident from the global membership of the Ecological Forecasting Initiative (https://efi-membe rs.herok uapp.com/).…”
Iterative near‐term ecological forecasting has great promise to provide vital information to decision‐makers while improving our ecological understanding, yet several logistical and fundamental challenges remain. The ecoinformatics requirements are onerous to develop and maintain, posing a barrier to entry for regions where funding and expertise are limited, and there are fundamental challenges to developing forecasts that fulfil information needs spanning spatial, temporal and biological scales.
Using the hyperdiverse Cape Floristic Region of South Africa as a case study, we propose that developing regionally focussed sets of ecological forecasts will help resolve logistical challenges faced by under‐resourced regions of the world, while comparison or coupling of models across scales will facilitate new fundamental insights. We review information needs and existing models for the region and explore how they could be developed into a set of linked iterative near‐term forecasts.
Comparing or coupling ecological forecasts from different scales within the same domain has much potential to provide new insights for decision‐makers and ecologists alike. They allow us to quantitatively link processes in space and time, potentially revealing feedbacks, interconnections and emergent properties, while providing powerful tools for testing decision scenarios and identifying trade‐offs or unanticipated outcomes. While the development of multiple or combined ecological forecasts that span scales is not trivial, there are logistical gains to be made from developing shared ecoinformatics pipelines that feed multiple models. Even where useful forecasts do not yet exist, the pipelines can be of great value in their own right, delivering frequent and up‐to‐date information to decision‐makers while providing the basis for forecast development and other scientific research.
Viewed together, regionally focussed approaches to ecological forecasting present a compelling opportunity to overcome logistical constraints and to integrate across multiple scales of organisation, ultimately improving our understanding and management of ecosystems.
“…In South Africa, woody tree and shrub species are overrepresented in the invasive alien flora (Richardson et al, 2020). In reviewing the impacts of alien plant species in South Africa, van Wilgen et al (2022) showed that invasive trees and shrubs contribute the majority of recorded impacts. The cause of impacts in invaded ecosystems is mainly through competitive exclusion of native species and by changes to ecosystem functioning.…”
IntroductionAlien trees and shrubs have become increasingly common invaders globally and have caused major negative impacts to ecosystems and society. Non-native woody plant species make up the majority of legislated invasive alien taxa in South Africa and contribute substantially to recorded negative impacts. It is of management interest to elucidate the macroecological processes that mediate the assembly of alien taxa, as this is expected to be associated with anthropogenic factors (e.g., human activity, introduction events, pathways of propagule dispersal mediated by humans) and bioclimatic factors (such as diurnal temperature range and precipitation gradients). These analyses require large species-occurrence datasets with comprehensive sampling across broad environmental conditions. Efforts of citizen scientists produce large numbers of occurrence records in a consistent manner which may be utilised for scientific investigations.MethodsResearch Grade occurrence data on naturalised plants of South Africa were extracted from the citizen scientist platform iNaturalist. Sampling bias was mitigated using statistical modelling of background points estimated from a Target Group of species which identifies well sampled communities. The drivers of assembly for alien plants at different range sizes were identified using multi-site generalised dissimilarity modelling (MS-GDM) of zeta diversity. The predicted compositional similarity between all cells was computed based on the subset of identified well sampled communities and using generalised dissimilarity modelling (GDM). From this, alien bioregions were identified using a k-means cluster analysis.Results and DiscussionBioclimatic factors significantly influenced community turnover in inland areas with large diurnal temperature ranges, and in areas with high precipitation. Communities separated by large geographical distances had significantly different compositions, indicating little contribution of long-range propagule movement by humans, and the presence of localised introduction hubs within the country which harbour unique species compositions. Analyses also showed a significant contribution of road density to turnover, which may be moderated by the habitat service provided by road verges. The same is true for natural dispersal via rivers in arid areas. The distribution of naturalised tree and shrub species is geographically clustered and forms six alien bioregions that are distinct from the South African biomes defined by native species distributionanalysis.
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