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Connor Nolan

Publications and source records attributed to Connor Nolan.

5 recordsLinked to original sources

Comparing and improving methods for reconstructing peatland water-table depth from testate amoebae

Proxies that use changes in the composition of ecological communities to reconstruct temporal changes in an environmental covariate are commonly used in paleoclimatology and paleolimnology. Existing methods, such as weighted averaging and modern analog technique, relate compositional data to the covariate in very simple ways, and different methods are seldom compared systematically. We present a new Bayesian model that better represents the underlying data and the complexity in the relationships between species’ abundances and a paleoenvironmental covariate. Using testate amoeba-based reconstructions of water-table depth as a test case, we systematically compare new and existing models in a cross-validation experiment on a large training dataset from North America. We then apply the different models to a new 7500-year record of testate amoeba assemblages from Caribou Bog in Maine and compare the resulting water-table depth reconstructions. We find that Bayesian models represent an improvement over existing methods in three key ways: more complete use of the underlying compositional data, full and meaningful treatment of uncertainty, and clear paths toward methodological improvements. Furthermore, we highlight how developing and systematically comparing methods leads to an improved understanding of the proxy system. This paper focuses on testate amoebae and water-table depth, but the framework and ideas are widely applicable to other proxies based on compositional data.

Continental United States and Alaska

Predicting paleoclimate from compositional data using multivariate Gaussian process inverse prediction

Multivariate compositional count data arise in many applications including ecology, microbiology, genetics and paleoclimate. A frequent question in the analysis of multivariate compositional count data is what underlying values of a covariate(s) give rise to the observed composition. Learning the relationship between covariates and the compositional count allows for inverse prediction of unobserved covariates given compositional count observations. Gaussian processes provide a flexible framework for modeling functional responses with respect to a covariate without assuming a functional form. Many scientific disciplines use Gaussian process approximations to improve prediction and make inference on latent processes and parameters. When prediction is desired on unobserved covariates given realizations of the response variable, this is called inverse prediction. Because inverse prediction is often mathematically and computationally challenging, predicting unobserved covariates often requires fitting models that are different from the hypothesized generative model. We present a novel computational framework that allows for efficient inverse prediction using a Gaussian process approximation to generative models. Our framework enables scientific learning about how the latent processes co-vary with respect to covariates while simultaneously providing predictions of missing covariates. The proposed framework is capable of efficiently exploring the high dimensional, multi-modal latent spaces that arise in the inverse problem. To demonstrate flexibility, we apply our method in a generalized linear model framework to predict latent climate states given multivariate count data. Based on cross-validation, our model has predictive skill competitive with current methods while simultaneously providing formal, statistical inference on the underlying community dynamics of the biological system previously not available.

Annals of Applied Statistics

Placing the Common Era in a Holocene context: Millennial to centennial patterns and trends in the hydroclimate of North America over the past 2000 years

A synthesis of 93 hydrologic records from across North and Central America, and adjacent tropical and Arctic islands, reveals centennial to millennial trends in the regional hydroclimates of the Common Era (CE; past 2000 years). The hydrological records derive from materials stored in lakes, bogs, caves, and ice from extant glaciers, which have the continuity through time to preserve low-frequency ( > 100 year) climate signals that may extend deeper into the Holocene. The most common pattern, represented in 46 (49 %) of the records, indicates that the centuries before 1000 CE were drier than the centuries since that time. Principal component analysis indicates that millennial-scale trends represent the dominant pattern of variance in the southwestern US, northeastern US, mid-continent, Pacific Northwest, Arctic, and tropics, although not all records within a region show the same direction of change. The Pacific Northwest and the southernmost tier of the tropical sites tended to dry toward present, as many other areas became wetter than before. In 22 records (24 %), the Medieval Climate Anomaly period (800–1300 CE) was drier than the Little Ice Age (1400–1900 CE), but in many cases the difference was part of the longer millennial-scale trend, and, in 25 records (27 %), the Medieval Climate Anomaly period represented a pluvial (wet) phase. Where quantitative records permitted a comparison, we found that centennial-scale fluctuations over the Common Era represented changes of 3–7 % in the modern interannual range of variability in precipitation, but the accumulation of these long-term trends over the entirety of the Holocene caused recent centuries to be significantly wetter, on average, than most of the past 11 000 years.

Climate of the Past

Past and future global transformation of terrestrial ecosystems under climate change

Impacts of global climate change on terrestrial ecosystems are imperfectly constrained by ecosystem models and direct observations. Pervasive ecosystem transformations occurred in response to warming and associated climatic changes during the last glacial-to-interglacial transition, which was comparable in magnitude to warming projected for the next century under high-emission scenarios. We reviewed 594 published paleoecological records to examine compositional and structural changes in terrestrial vegetation since the last glacial period and to project the magnitudes of ecosystem transformations under alternative future emission scenarios. Our results indicate that terrestrial ecosystems are highly sensitive to temperature change and suggest that, without major reductions in greenhouse gas emissions to the atmosphere, terrestrial ecosystems worldwide are at risk of major transformation, with accompanying disruption of ecosystem services and impacts on biodiversity.

Science

Climatic history of the northeastern United States during the past 3000 years

Many ecosystem processes that influence Earth system feedbacks, including vegetation growth, water and nutrient cycling, and disturbance regimes, are strongly influenced by multi-decadal to millennial-scale variations in climate that cannot be captured by instrumental climate observations. Paleoclimate information is therefore essential for understanding contemporary ecosystems and their potential trajectories under a variety of future climate conditions. With the exception of fossil pollen records, there are a limited number of northeastern US (NE US) paleoclimate archives that can provide constraints on its temperature and hydroclimate history. Moreover, the records that do exist have not been considered together. Tree-ring data indicate that the 20th century was one of the wettest of the past 500 years in the eastern US (Pederson et al., 2014), and lake-level records suggest it was one of the wettest in the Holocene (Newby et al., 2014); how such results compare with other available data remains unclear, however. Here we conduct a systematic review, assessment, and comparison of paleotemperature and paleohydrological proxies from the NE US for the last 3000 years. Regional temperature reconstructions are consistent with the long-term cooling trend (1000 BCE–1700 CE) evident in hemispheric-scale reconstructions, but hydroclimate reconstructions reveal new information, including an abrupt transition from wet to dry conditions around 550–750 CE. NE US paleo data suggest that conditions during the Medieval Climate Anomaly were warmer and drier than during the Little Ice Age, and drier than today. There is some evidence for an acceleration over the past century of a longer-term wetting trend in the NE US, and coupled with the abrupt shift from a cooling trend to a warming trend from increased greenhouse gases, may have wide-ranging implications for species distributions, ecosystem dynamics, and extreme weather events. More work is needed to gather paleoclimate data in the NE US, make inter-proxy comparisons, and improve estimates of uncertainty in the reconstructions.

Climate of the Past