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1. Predicting near-term variability in ocean carbon uptake

   https://doi.org/10.5194/esd-10-45-2019  

   Lovenduski, Nicole S. ; Yeager, Stephen G. ; Lindsay, Keith ; Long, Matthew C. ( January 2019 , Earth System Dynamics)

   Abstract. Interannual variations in air–sea fluxes of carbon dioxide (CO₂) impactthe global carbon cycle and climate system, and previous studies suggest thatthese variations may be predictable in the near term (from a year to a decadein advance). Here, we quantify and understand the sources of near-termpredictability and predictive skill in air–sea CO₂ flux on global andregional scales by analyzing output from a novel set of retrospective decadalforecasts of an Earth system model. These forecasts exhibit the potential topredict year-to-year variations in the globally integrated air–sea CO₂flux several years in advance, as indicated by the high correlation of theforecasts with a model reconstruction of past CO₂ flux evolution. Thispotential predictability exceeds that obtained solely from foreknowledge ofvariations in external forcing or a simple persistence forecast, with thelongest-lasting forecast enhancement in the subantarctic Southern Ocean andthe northern North Atlantic. Potential predictability in CO₂ fluxvariations is largely driven by predictability in the surface ocean partialpressure of CO₂, which itself is a function of predictability in surfaceocean dissolved inorganic carbon and alkalinity. The potentialpredictability, however, is not realized as predictive skill, as indicated bythe moderate to low correlation of the forecasts with anobservationally based CO₂ flux product. Nevertheless, our results suggestthat year-to-year variations in ocean carbon uptake have the potential to bepredicted well in advance and establish a precedent for forecasting air–seaCO₂ flux in the near future.

    

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2. Integrating Multidisciplinary Observations in Vent Environments (IMOVE): Decadal Progress in Deep-Sea Observatories at Hydrothermal Vents

   https://doi.org/10.3389/fmars.2022.866422  

   Matabos, Marjolaine ; Barreyre, Thibaut ; Juniper, S. Kim ; Cannat, Mathilde ; Kelley, Deborah ; Alfaro-Lucas, Joan M. ; Chavagnac, Valérie ; Colaço, Ana ; Escartin, Javier ; Escobar, Elva ; et al ( May 2022 , Frontiers in Marine Science)

   The unique ecosystems and biodiversity associated with mid-ocean ridge (MOR) hydrothermal vent systems contrast sharply with surrounding deep-sea habitats, however both may be increasingly threatened by anthropogenic activity (e.g., mining activities at massive sulphide deposits). Climate change can alter the deep-sea through increased bottom temperatures, loss of oxygen, and modifications to deep water circulation. Despite the potential of these profound impacts, the mechanisms enabling these systems and their ecosystems to persist, function and respond to oceanic, crustal, and anthropogenic forces remain poorly understood. This is due primarily to technological challenges and difficulties in accessing, observing and monitoring the deep-sea. In this context, the development of deep-sea observatories in the 2000s focused on understanding the coupling between sub-surface flow and oceanic and crustal conditions, and how they influence biological processes. Deep-sea observatories provide long-term, multidisciplinary time-series data comprising repeated observations and sampling at temporal resolutions from seconds to decades, through a combination of cabled, wireless, remotely controlled, and autonomous measurement systems. The three existing vent observatories are located on the Juan de Fuca and Mid-Atlantic Ridges (Ocean Observing Initiative, Ocean Networks Canada and the European Multidisciplinary Seafloor and water column Observatory). These observatories promote stewardship by defining effective environmental monitoring including characterizing biological and environmental baseline states, discriminating changes from natural variations versus those from anthropogenic activities, and assessing degradation, resilience and recovery after disturbance. This highlights the potential of observatories as valuable tools for environmental impact assessment (EIA) in the context of climate change and other anthropogenic activities, primarily ocean mining. This paper provides a synthesis on scientific advancements enabled by the three observatories this last decade, and recommendations to support future studies through international collaboration and coordination. The proposed recommendations include: i) establishing common global scientific questions and identification of Essential Ocean Variables (EOVs) specific to MORs, ii) guidance towards the effective use of observatories to support and inform policies that can impact society, iii) strategies for observatory infrastructure development that will help standardize sensors, data formats and capabilities, and iv) future technology needs and common sampling approaches to answer today’s most urgent and timely questions. 

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3. Interrelated impacts of climate and land‐use change on a widespread waterbird

   https://doi.org/10.1111/1365-2656.13444  

   Saunders, Sarah P. ; Piper, Walter ; Farr, Matthew T. ; Bateman, Brooke L. ; Michel, Nicole L. ; Westerkam, Henrik ; Wilsey, Chad B. ( March 2021 , Journal of Animal Ecology)

   Together climate and land‐use change play a crucial role in determining species distribution and abundance, but measuring the simultaneous impacts of these processes on current and future population trajectories is challenging due to time lags, interactive effects and data limitations. Most approaches that relate multiple global change drivers to population changes have been based on occurrence or count data alone.

   We leveraged three long‐term (1995–2019) datasets to develop a coupled integrated population model‐Bayesian population viability analysis (IPM‐BPVA) to project future survival and reproductive success for common loonsGavia immerin northern Wisconsin, USA, by explicitly linking vital rates to changes in climate and land use.

   The winter North Atlantic Oscillation (NAO), a broad‐scale climate index, immediately preceding the breeding season and annual changes in developed land cover within breeding areas both had strongly negative influences on adult survival. Local summer rainfall was negatively related to fecundity, though this relationship was mediated by a lagged interaction with the winter NAO, suggesting a compensatory population‐level response to climate variability.

   We compared population viability under 12 future scenarios of annual land‐use change, precipitation and NAO conditions. Under all scenarios, the loon population was expected to decline, yet the steepest declines were projected under positive NAO trends, as anticipated with ongoing climate change. Thus, loons breeding in the northern United States are likely to remain affected by climatic processes occurring thousands of miles away in the North Atlantic during the non‐breeding period of the annual cycle.

   Our results reveal that climate and land‐use changes are differentially contributing to loon population declines along the southern edge of their breeding range and will continue to do so despite natural compensatory responses. We also demonstrate that concurrent analysis of multiple data types facilitates deeper understanding of the ecological implications of anthropogenic‐induced change occurring at multiple spatial scales. Our modelling approach can be used to project demographic responses of populations to varying environmental conditions while accounting for multiple sources of uncertainty, an increasingly pressing need in the face of unprecedented global change.

    

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4. A first empirical analysis of population stability in North America using radiocarbon records

   https://doi.org/10.1177/0959683620919975  

   Bird, Darcy ; Freeman, Jacob ; Robinson, Erick ; Maughan, Gideon ; Finley, Judson Byrd ; Lambert, Patricia M ; Kelly, Robert L ( September 2020 , The Holocene)

   null (Ed.)

   Questions regarding population stability among animals and plants are fundamental to population ecology, yet this has not been a topic studied by archeologists focusing on prehistoric human populations. This is an important knowledge gap. The fluctuation of human populations over decades to centuries – population instability – may constrain the expansion of human economies. A first step toward describing basic patterns of population stability would be to identify sizes of fluctuations through time, since smaller fluctuations are more stable than larger fluctuations. We conduct a biogeographic analysis of the long-term stability of human societies in North America using a continental scale radiocarbon dataset. Our analysis compares the stability of summed calibrated radiocarbon date probability distributions (SPDs) with subsistence strategies and modeled climate stability between 6000 and 300 BP. This coarse-grained analysis reveals general trends regarding the stability of human systems in North America that future studies may build upon. Our results demonstrate that agricultural sequences have more stable SPDs than hunter-gatherer sequences in general, but agricultural sequences also experience rare, extreme increases and decreases in SPDs not seen among hunter-gatherers. We propose that the adoption of agriculture has the unintended consequence of increasing population density and stability over most time scales, but also increases the vulnerability of populations to large, rare changes. Conversely, hunter-gatherer systems remain flexible and less vulnerable to large population changes. Climate stability may have an indirect effect on long-term population stability, and climate shocks may be buffered by other aspects of subsistence strategies prior to affecting human demography. 

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5. Ancient Lowland Maya neighborhoods: Average Nearest Neighbor analysis and kernel density models, environments, and urban scale

   https://doi.org/10.1371/journal.pone.0275916  

   Thompson, Amy E. ; Walden, John P. ; Chase, Adrian S. ; Hutson, Scott R. ; Marken, Damien B. ; Cap, Bernadette ; Fries, Eric C. ; Guzman Piedrasanta, M. Rodrigo ; Hare, Timothy S. ; Horn, Sherman W. ; et al ( November 2022 , PLOS ONE)

   Hart, John P. (Ed.)

   Many humans live in large, complex political centers, composed of multi-scalar communities including neighborhoods and districts. Both today and in the past, neighborhoods form a fundamental part of cities and are defined by their spatial, architectural, and material elements. Neighborhoods existed in ancient centers of various scales, and multiple methods have been employed to identify ancient neighborhoods in archaeological contexts. However, the use of different methods for neighborhood identification within the same spatiotemporal setting results in challenges for comparisons within and between ancient societies. Here, we focus on using a single method—combining Average Nearest Neighbor (ANN) and Kernel Density (KD) analyses of household groups—to identify potential neighborhoods based on clusters of households at 23 ancient centers across the Maya Lowlands. While a one-size-fits all model does not work for neighborhood identification everywhere, the ANN/KD method provides quantifiable data on the clustering of ancient households, which can be linked to environmental zones and urban scale. We found that centers in river valleys exhibited greater household clustering compared to centers in upland and escarpment environments. Settlement patterns on flat plains were more dispersed, with little discrete spatial clustering of households. Furthermore, we categorized the ancient Maya centers into discrete urban scales, finding that larger centers had greater variation in household spacing compared to medium-sized and smaller centers. Many larger political centers possess heterogeneity in household clustering between their civic-ceremonial cores, immediate hinterlands, and far peripheries. Smaller centers exhibit greater household clustering compared to larger ones. This paper quantitatively assesses household clustering among nearly two dozen centers across the Maya Lowlands, linking environment and urban scale to settlement patterns. The findings are applicable to ancient societies and modern cities alike; understanding how humans form multi-scalar social groupings, such as neighborhoods, is fundamental to human experience and social organization. 

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