Iterative near-term ecological forecasting Dietze, Michael C.; Fox, Andrew; Beck-Johnson, Lindsay M. ...
Proceedings of the National Academy of Sciences - PNAS,
02/2018, Letnik:
115, Številka:
7
Journal Article
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Two foundational questions about sustainability are “How are ecosystems and the services they provide going to change in the future?” and “How do human decisions affect these trajectories?” Answering ...these questions requires an ability to forecast ecological processes. Unfortunately, most ecological forecasts focus on centennial-scale climate responses, therefore neither meeting the needs of near-term (daily to decadal) environmental decision-making nor allowing comparison of specific, quantitative predictions to new observational data, one of the strongest tests of scientific theory. Near-term forecasts provide the opportunity to iteratively cycle between performing analyses and updating predictions in light of new evidence. This iterative process of gaining feedback, building experience, and correcting models and methods is critical for improving forecasts. Iterative, near-term forecasting will accelerate ecological research, make it more relevant to society, and inform sustainable decision-making under high uncertainty and adaptive management. Here, we identify the immediate scientific and societal needs, opportunities, and challenges for iterative near-term ecological forecasting. Over the past decade, data volume, variety, and accessibility have greatly increased, but challenges remain in interoperability, latency, and uncertainty quantification. Similarly, ecologists have made considerable advances in applying computational, informatic, and statistical methods, but opportunities exist for improving forecast-specific theory, methods, and cyberinfra-structure. Effective forecasting will also require changes in scientific training, culture, and institutions. The need to start forecasting is now; the time for making ecology more predictive is here, and learning by doing is the fastest route to drive the science forward.
Widespread deoxygenation of temperate lakes Jane, Stephen F.; Hansen, Gretchen J. A.; Kraemer, Benjamin M. ...
Nature (London),
06/2021, Letnik:
594, Številka:
7861
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The concentration of dissolved oxygen in aquatic systems helps to regulate biodiversity1'2, nutrient biogeochemistry3, greenhouse gas emissions4, and the quality of drinking water5. The long-term ...declines in dissolved oxygen concentrations in coastal and ocean waters have been linked to climate warming and human activity6,7, but little is known about the changes in dissolved oxygen concentrations in lakes. Although the solubility of dissolved oxygen decreases with increasing water temperatures, long-term lake trajectories are difficult to predict. Oxygen losses in warming lakes may be amplified by enhanced decomposition and stronger thermal stratification8,9 or oxygen may increase as a result of enhanced primary production10. Here we analyse a combined total of45,148 dissolved oxygen and temperature profiles and calculate trends for 393 temperate lakes that span 1941 to 2017. We find that a decline in dissolved oxygen is widespread in surface and deep-water habitats. The decline in surface waters is primarily associated with reduced solubility under warmer water temperatures, although dissolved oxygen in surface waters increased in a subset of highly productive warming lakes, probably owing to increasing production of phytoplankton. By contrast, the decline in deep waters is associated with stronger thermal stratification and loss of water clarity, but not with changes in gas solubility. Our results suggest that climate change and declining water clarity have altered the physical and chemical environment of lakes. Declines in dissolved oxygen in freshwater are 2.75 to 9.3 times greater than observed in the world's oceans6,7 and could threaten essential lake ecosystem services2,3,5'11.
Predicting algal blooms has become a priority for scientists, municipalities, businesses, and citizens. Remote sensing offers solutions to the spatial and temporal challenges facing existing lake ...research and monitoring programs that rely primarily on high-investment, in situ measurements. Techniques to remotely measure chlorophyll a (chl a) as a proxy for algal biomass have been limited to specific large water bodies in particular seasons and narrow chl a ranges. Thus, a first step toward prediction of algal blooms is generating regionally robust algorithms using in situ and remote sensing data. This study explores the relationship between in-lake measured chl a data from Maine and New Hampshire, USA lakes and remotely sensed chl a retrieval algorithm outputs. Landsat 8 images were obtained and then processed after required atmospheric and radiometric corrections. Six previously developed algorithms were tested on a regional scale on 11 scenes from 2013 to 2015 covering 192 lakes. The best performing algorithm across data from both states had a 0.16 correlation coefficient (R²) and P ≤ 0.05 when Landsat 8 images within 5 d, and improved to R² of 0.25 when data from Maine only were used. The strength of the correlation varied with the specificity of the time window in relation to the in-situ sampling date, explaining up to 27% of the variation in the data across several scenes. Two previously published algorithms using Landsat 8’s Bands 1–4 were best correlated with chl a, and for particular late-summer scenes, they accounted for up to 69% of the variation in in-situ measurements. A sensitivity analysis revealed that a longer time difference between in situ measurements and the satellite image increased uncertainty in the models, and an effect of the time of year on several indices was demonstrated. A regional model based on the best performing remote sensing algorithm was developed and was validated using independent in situ measurements and satellite images. These results suggest that, despite challenges including seasonal effects and low chl a thresholds, remote sensing could be an effective and accessible regional-scale tool for chl a monitoring programs in lakes.
Salting our freshwater lakes Dugan, Hilary A.; Bartlett, Sarah L.; Burke, Samantha M. ...
Proceedings of the National Academy of Sciences - PNAS,
04/2017, Letnik:
114, Številka:
17
Journal Article
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The highest densities of lakes on Earth are in north temperate ecosystems, where increasing urbanization and associated chloride runoff can salinize freshwaters and threaten lake water quality and ...the many ecosystem services lakes provide. However, the extent to which lake salinity may be changing at broad spatial scales remains unknown, leading us to first identify spatial patterns and then investigate the drivers of these patterns. Significant decadal trends in lake salinization were identified using a dataset of long-term chloride concentrations from 371 North American lakes. Landscape and climate metrics calculated for each site demonstrated that impervious land cover was a strong predictor of chloride trends in Northeast and Midwest North American lakes. As little as 1% impervious land cover surrounding a lake increased the likelihood of long-term salinization. Considering that 27% of large lakes in the United States have >1% impervious land cover around their perimeters, the potential for steady and long-term salinization of these aquatic systems is high. This study predicts that many lakes will exceed the aquatic life threshold criterion for chronic chloride exposure (230 mg L−1), stipulated by the US Environmental Protection Agency (EPA), in the next 50 y if current trends continue.
Macrosystems ecology is the study of diverse ecological phenomena at the scale of regions to continents and their interactions with phenomena at other scales. This emerging subdiscipline addresses ...ecological questions and environmental problems at these broad scales. Here, we describe this new field, show how it relates to modern ecological study, and highlight opportunities that stem from taking a macrosystems perspective. We present a hierarchical framework for investigating macrosystems at any level of ecological organization and in relation to broader and finer scales. Building on well-established theory and concepts from other subdisciplines of ecology, we identify feedbacks, linkages among distant regions, and interactions that cross scales of space and time as the most likely sources of unexpected and novel behaviors in macrosystems. We present three examples that highlight the importance of this multiscaled systems perspective for understanding the ecology of regions to continents.
Recent technological developments have increased the number of variables being monitored in lakes and reservoirs using automatic high frequency monitoring (AHFM). However, design of AHFM systems and ...posterior data handling and interpretation are currently being developed on a site-by-site and issue-by-issue basis with minimal standardization of protocols or knowledge sharing. As a result, many deployments become short-lived or underutilized, and many new scientific developments that are potentially useful for water management and environmental legislation remain underexplored. This Critical Review bridges scientific uses of AHFM with their applications by providing an overview of the current AHFM capabilities, together with examples of successful applications. We review the use of AHFM for maximizing the provision of ecosystem services supplied by lakes and reservoirs (consumptive and non consumptive uses, food production, and recreation), and for reporting lake status in the EU Water Framework Directive. We also highlight critical issues to enhance the application of AHFM, and suggest the establishment of appropriate networks to facilitate knowledge sharing and technological transfer between potential users. Finally, we give advice on how modern sensor technology can successfully be applied on a larger scale to the management of lakes and reservoirs and maximize the ecosystem services they provide.
Here we draw attention to the potential for pelagic bloom-forming cyanobacteria to have substantial effects on nutrient cycling and ecosystem resilience across a wide range of lakes. Specifically, we ...hypothesize that cyanobacterial blooms can influence lake nutrient cycling, resilience, and regime shifts by tapping into pools of nitrogen (N)
and
phosphorus (P) not usually accessible to phytoplankton. The ability of many cyanobacterial taxa to fix dissolved N
2
gas is a well-known potential source of N, but some taxa can also access pools of P in sediments and bottom waters. Both of these nutrients can be released to the water column via leakage or mortality, thereby increasing nutrient availability for other phytoplankton and microbes. Moreover, cyanobacterial blooms are not restricted to high nutrient (eutrophic) lakes: blooms also occur in lakes with low nutrient concentrations, suggesting that changes in nutrient cycling and ecosystem resilience mediated by cyanobacteria could affect lakes across a gradient of nutrient concentrations. We used a simple model of coupled N and P cycles to explore the effects of cyanobacteria on nutrient dynamics and resilience. Consistent with our hypothesis, parameters reflecting cyanobacterial modification of N and P cycling alter the number, location, and/or stability of model equilibria. In particular, the model demonstrates that blooms of cyanobacteria in low-nutrient conditions can facilitate a shift to the high-nutrient state by reducing the resilience of the low-nutrient state. This suggests that cyanobacterial blooms warrant attention as potential drivers of the transition from a low-nutrient, clear-water regime to a high-nutrient, turbid-water regime, a prediction of particular concern given that such blooms are reported to be increasing in many regions of the world due in part to global climate change.
A synergistic future for AI and ecology Han, Barbara A.; Varshney, Kush R.; LaDeau, Shannon ...
Proceedings of the National Academy of Sciences - PNAS,
09/2023, Letnik:
120, Številka:
38
Journal Article
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Research in both ecology and AI strives for predictive understanding of complex systems, where nonlinearities arise from multidimensional interactions and feedbacks across multiple scales. After a ...century of independent, asynchronous advances in computational and ecological research, we foresee a critical need for intentional synergy to meet current societal challenges against the backdrop of global change. These challenges include understanding the unpredictability of systems-level phenomena and resilience dynamics on a rapidly changing planet. Here, we spotlight both the promise and the urgency of a convergence research paradigm between ecology and AI. Ecological systems are a challenge to fully and holistically model, even using the most prominent AI technique today: deep neural networks. Moreover, ecological systems have emergent and resilient behaviors that may inspire new, robust AI architectures and methodologies. We share examples of how challenges in ecological systems modeling would benefit from advances in AI techniques that are themselves inspired by the systems they seek to model. Both fields have inspired each other, albeit indirectly, in an evolution toward this convergence. We emphasize the need for more purposeful synergy to accelerate the understanding of ecological resilience whilst building the resilience currently lacking in modern AI systems, which have been shown to fail at times because of poor generalization in different contexts. Persistent epistemic barriers would benefit from attention in both disciplines. The implications of a successful convergence go beyond advancing ecological disciplines or achieving an artificial general intelligence—they are critical for both persisting and thriving in an uncertain future.
Interdisciplinary collaboration is essential to understand ecological systems at scales critical to human decision making. Current reward structures are problematic for scientists engaged in ...interdisciplinary research, particularly early career researchers, because academic culture tends to value only some research outputs, such as primary-authored publications. Here, we present a framework for the costs and benefits of collaboration, with a focus on early career stages, and show how the implementation of novel measures of success can help defray the costs of collaboration. Success measures at team and individual levels include research outputs other than publications, including educational outcomes, dataset creation, outreach products (eg blogs or social media), and the application of scientific results to policy or management activities. Promotion and adoption of new measures of success will require concerted effort by both collaborators and their institutions. Expanded measures should better reflect and reward the important work of both disciplinary and interdisciplinary teams at all career stages, and help sustain and stimulate a collaborative culture within ecology.
Lakes at Risk of Chloride Contamination Dugan, Hilary A; Skaff, Nicholas K; Doubek, Jonathan P ...
Environmental science & technology,
06/2020, Letnik:
54, Številka:
11
Journal Article
Recenzirano
Lakes in the Midwest and Northeast United States are at risk of anthropogenic chloride contamination, but there is little knowledge of the prevalence and spatial distribution of freshwater ...salinization. Here, we use a quantile regression forest (QRF) to leverage information from 2773 lakes to predict the chloride concentration of all 49 432 lakes greater than 4 ha in a 17-state area. The QRF incorporated 22 predictor variables, which included lake morphometry characteristics, watershed land use, and distance to the nearest road and interstate. Model predictions had an
of 0.94 for all chloride observations, and an
of 0.86 for predictions of the median chloride concentration observed at each lake. The four predictors with the largest influence on lake chloride concentrations were low and medium intensity development in the watershed, crop density in the watershed, and distance to the nearest interstate. Almost 2000 lakes are predicted to have chloride concentrations above 50 mg L
and should be monitored. We encourage management and governing agencies to use lake-specific model predictions to assess salt contamination risk as well as to augment their monitoring strategies to more comprehensively protect freshwater ecosystems from salinization.
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