Temporal ecology in the Anthropocene

Overview

Understanding and anticipating ecosystem response to global environmental change is one of the biggest challenges facing ecology and society. Timeseries are an invaluable tool for disentangling species interactions and drivers of change and are essential for predicting future responses. Long-term monitoring programmes and ecological timeseries like the UKCEH Countryside Survey (https://countrysidesurvey.org.uk/) and global BioTime biodiversity timeseries database (http://biotime.st-andrews.ac.uk/) provide decadal to multi-decadal insight into such trends and relationships. However, even these are limited by their relatively short duration: as noted in a review of findings from the UK Environmental Change Network, “after 15 years, trends in physical, chemical and biological parameters are emerging which could not have been detected at an earlier stage. This is still, however, a relatively short time compared to many ecological processes” [1].
Twentieth century observations thus represent a snapshot of species-environment interactions and do not take into account the impacts and legacies of major step-changes in climate or natural resource use, such as 19th century industrialisation, the post-Little Ice Age start of climate warming or the mid-20th century “Great Acceleration”. Furthermore, the mechanisms governing change are geared to different temporal scales, so it may be misleading to scale relationships up or down beyond the observation period on which they are based [2]. A secure understanding of these interactions is essential for understanding the relative roles of climatic and human factors as drivers of change, and for identifying critical thresholds within ecosystems.
Recognition of this mismatch between observation and process has stimulated calls for a more holistic approach to temporal ecology, incorporating longer-term sources like palaeoecology [3-5]. Efforts to achieve this are, however, constrained by a persistent disconnection between these fields of ecology, which often study processes on contrasting timescales, using mutually unfamiliar techniques that provide related but non-identical measures of change [6-7]. Limited connectivity across ecology and palaeoecology means that we lack a secure understanding of the extent to which shorter-term (50 year) data remain all but absent from major ecosystem assessments and methodological differences remain a key barrier to the inclusion of palaeoecology [8-10]. Only collaborative effort that specifically tests the ecological significance of contrasting disciplinary approaches and timeframes will shift this persistent status quo.

Methodology

The project will use the rich array of existing data, drawing on ecological and palaeoecological databases of ecological timeseries and augmenting these with additional published but currently unarchived datasets. Existing sources will include the global BioTIME database (developed at St Andrews [11]), the 42 year UKCEH Countryside Survey and Ecological Change Network monitoring datasets, and records drawn from European and global palaeoecological databases such as the European Pollen Database, Neotoma and Pangaea.

What/where? The project will focus on aquatic and terrestrial systems. In freshwater systems the links between hydrological conditions and ecosystem health are well-established for flora and fauna from ecological and palaeolimnological perspectives. Long-term, specifically pre-industrial, baselines are embedded in the EU Water Framework Directive, providing legislative motivation to connect past change with contemporary management and “good condition” goals. While this provides strong impetus for integrated monitoring and assessment, routine data integration and uptake of palaeo-data in freshwater management remain limited. Records of terrestrial land cover dynamics are abundant in ecology and palaeoecology. These provide scope to analyse both macroecological and ecosystem-specific trends.

How? The project will use a selection of complementary metrics to compare cross-time insights into ecosystem dynamics and establish the complementary strengths of each source. The metrics will be refined by the student but may include (1) biodiversity: the merits and limitations of differing measurements are well-established across the disciplines; (2) species associations and community reorganisation: essential for understanding resilience, critical thresholds and the viability of community-based conservation goals; (3) environmental indicators, such as Ellenberg indicators [12]; and (4) functional traits: a rapidly growing field of research in ecology that is beginning to be explored in palaeoecology [13-14].

Analyses will (1) begin with the shared time period to examine contrasts and similarities across disciplines, (2) test the sensitivity of palaeoecological and ecological trends to variations in spatial, temporal and taxonomic resolution (e.g. how robust are trends to changes in functional or broad habitat groups, or to using lower taxonomic resolution; the latter is a frequent concern with palaeo-data), and (3) extend to longer durations to assess how temporal scaling affects the representation of ecological patterns and processes, including attribution of the drivers of change. These methods will allow us to develop a protocol for comparative analysis by identifying optimal data characteristics for joint analysis, providing the rigorous testing needed to how methodological differences affect representation of trends, and thus establish when and how palaeo-data can be used to extend ecological timeseries. They will allow the project to examine whether step-changes in human-nature relations, such as the Great Acceleration in the 1950s, and processes like biotic homogenisation [15] are creating no-analogue states, imposing a filter on future assemblages and eroding resilience, particularly when considered alongside changes in the type, magnitude and frequency of disturbance pressures.

Project Timeline

Year 1

Data compilation (including data-mining existing databases, requests for non-archived records from key data-holders); literature review; methodological training; identify key geographical areas and ecosystem/habitat categories for further study; exploratory analysis of palaeo and ecological data based on overlapping time period using biodiversity metrics; sensitivity testing of taxonomic resolution; review and assemble records of potential drivers of change (e.g. pollution, land-use, climate); begin to develop integrated trend models from different sources and accounting for methodological differences

Year 2

Refine comparative data analysis for shared time period, sensitivity testing; apply metrics that are robust in the comparative period to longer-term records to test the origins and novelty of observed trends; extend from biodiversity to other metrics; draft and submit first paper on methodology (e.g. relating to diversity metrics and comparative trends from palaeo+ecology)

Year 3

Continue comparative testing for traits and environmental indicator analysis; extend these to pre-observational periods; draft and submit second manuscript

Year 3.5

Finalise manuscripts and write thesis

Training
& Skills

The project will provide training in data handling, ecological timeseries analysis using a range of metrics and relating these to multivariate datasets from terrestrial and aquatic ecosystems. The student will benefit from interaction with (1) the St Andrews palaeoecology group whose ecosystems of interest span temperate, tropical and subarctic zones, (2) the BioTIME project at St Andrews, including newly appointed postdoctoral researcher, Dr Amelia Penny whose expertise in palaeontology will bring a valuable deep time dimension to the project, allowing the student to learn from innovation in palaeobiology, and (3) have opportunities to participate in the UK Countryside Survey training and fieldwork and to spend time at CEH working with statisticians and ecologists understanding and analysing the data. It represents an opportunity for broad training in methods and approaches that will equip a successful student for a career in ecology, spanning macroecology, ecoinformatics and global change ecology, and allows the candidate to take a leading role in strengthening and developing cross-discipline networks. The successful candidate will also have access to training and networking events run by the Scottish Alliance for Geosciences, Environment and Society (https://www.sages.ac.uk/).

References & further reading

[1] Morecroft MD et al. (2009) The UK Environmental Change Network: Emerging trends in the composition of plant and animal communities and the physical environment. Biological Conservation 142: 2814-32.[2] Willis KJ and Whittaker RJ. (2002) Species Diversity – Scale Matters. Science 295: 1245-8.[3] Dawson TP et al. (2011) Beyond predictions: biodiversity conservation in a changing climate. Science 332: 53-8.[4] Magurran AE and Dornelas M. (2010) Biological diversity in a changing world. Philosophical Transactions of the Royal Society B: Biological Sciences 365: 3593-7.[5] Wolkovich et al. (2014) Temporal ecology in the Anthropocene. Ecology Letters 17: 1365–79.[6] Froyd CA and Willis KJ. (2008) Emerging issues in biodiversity & conservation management: The need for a palaeoecological perspective. Quaternary Science Reviews 27: 1723-32.[7] Maguire KC et al. (2015) Modeling Species and Community Responses to Past, Present, and Future Episodes of Climatic and Ecological Change. Annual Review of Ecology, Evolution, and Systematics 46: 343-68.[8] Willis KJ et al. (2005) Providing baselines for biodiversity measurement. Trends in Ecology & Evolution 20: 107-8.[9] Davies AL et al. (2014) Improving the application of long-term ecology in conservation and land management. Journal of Applied Ecology 51: 63-70.[10] Rull V. (2014) Time continuum and true long-term ecology: from theory to practice. Frontiers in Ecology and Evolution 2. https://doi.org/10.3389/fevo.2014.00075[11] Dornelas M et al. (2018) BioTIME: A database of biodiversity time series for the Anthropocene. Global Ecology and Biogeography 27: 760-86.[12] Reitalu T et al. (2015) Novel insights into post-glacial vegetation change: functional and phylogenetic diversity in pollen records. Journal of Vegetation Science 26: 911-22.[13] Carvalho F et al. (2019) A method for reconstructing temporal changes in vegetation functional trait composition using Holocene pollen assemblages. PLoS ONE 14: e0216698.[14] van der Sande MT et al. (2019) A 7000-year history of changing plant trait composition in an Amazonian landscape; the role of humans and climate. Ecology Letters 22: 925-35.[15] Smart SM et al. (2006) Biotic homogenization and changes in species diversity across human-modified ecosystems. Proceedings of the Royal Society B-Biological Sciences 273: 2659-65.
Additional useful reading:
Maskell LC et al. (2020) Long-term trends in the distribution, abundance and impact of native “injurious” weeds. Applied Vegetation Science https://doi.org/10.1111/avsc.12518.
Rose R et al. (2016) Evidence for increases in vegetation-species richness across the UK Environmental Change Network sites resulting from changes in air pollution and weather patterns. Ecological Indicators 68: 52–62.
Wood CM et al. (2017) Long-term vegetation monitoring in Great Britain – the Countryside Survey 1978-2007 and beyond. Earth System Science Data, 9, 445-59.

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