Temporal ecology in the Anthropocene

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 compared with many ecological processes [1]. Twentieth century observations also do not take into account major step-changes in climate or natural resource use, including 19th century industrialisation and start of climate warming or the mid-20th century ‘Great Acceleration’. Furthermore, 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 assessing drivers of change and identifying critical ecosystem thresholds.
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 constrained by a persistent disconnection between these fields, 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) responses (the remit of much ecology) generate persistent and generalizable long-term ecological and biogeographical changes (the mainstay of palaeoecology and predictive ecology). This perpetuates a temporal divide in ecology and fragments our ability to understand and evaluate the state of ecosystems or define appropriate management or conservation baselines.
This project aims to develop a robust methodology for integrating palaeo and ecological timeseries and to use this to assess whether ecological trends detected in recent decades are hallmarks of the Anthropocene or whether they represent a continuation or recurrence of ecological responses seen during previous centuries and millennia. It will use the lengthening overlap between ecological and palaeoecological timeseries as the starting point for comparison; this spans c.30-100 years but has been largely overlooked as a basis for collaboration. Doing so will address methodological differences and a lack of confidence amongst ecologists that palaeoecology provides a trusted source of ecological evidence over longer timescales [8,9].


The project will use existing timeseries databases, including BioTIME [10], the 42 year UKCEH Countryside Survey and Ecological Change Network datasets, and palaeoecological databases like Neotoma, with published but currently unarchived datasets.
It will focus on aquatic and terrestrial systems, which are well-documented in both disicplines, and allow analysis of macroecological and ecosystem-specific trends. In freshwater systems, pre-industrial baselines are embedded in the EU Water Framework Directive, providing legislative motivation to connect past change with contemporary management.
The project will use complementary metrics to compare cross-time insights into ecosystem dynamics and establish the strengths of each source, such as biodiversity, species associations and turnover, environmental indicators and functional traits [11,12].
Analyses will (1) begin with the shared time period to compare disciplines, (2) test the sensitivity of trends to variations in spatial, temporal and taxonomic resolution, and (3) extend to longer durations to assess how temporal scaling affects the representation of ecological patterns and attribution of drivers of change. These will be used to develop a protocol for comparative analysis by testing and identifying optimal data characteristics for joint analysis to establish when and how palaeo-data can be used to extend ecological timeseries. This will allow the project to examine whether step-changes in human-nature relations or processes like biotic homogenisation [13] are creating no-analogue states and imposing a filter on future assemblages when considered alongside changes in the type, magnitude and frequency of disturbances [14,15].

Project Timeline

Year 1

Data compilation; literature review; methodological training; identify promising areas and ecosystems/habitats ; exploratory analysis 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, sensitivity testing; apply metrics that are robust in the shared period to longer-term records to test the origins and novelty of observed trends; extend from biodiversity to other metrics; draft and submit 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

& Skills

The project will provide training in data handling, ecological timeseries analysis using a range of metrics and multivariate data comparison to assess possible drivers. The student will benefit from interaction with (1) the St Andrews palaeoecology group whose interests span temperate, tropical and subarctic zones, (2) the St Andrews BioTIME project, including postdoctoral researcher, Dr Amelia Penny whose expertise will allow the student to learn from innovation in palaeobiology, and (3) have opportunities to participate in UK Countryside Survey training and fieldwork and spend time at CEH working with statisticians and ecologists to analyse data. It represents an opportunity for broad, collaborative 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 developing and strengthening cross-discipline networks. The candidate will also have access to training and networking events run by Scottish Alliance for Geosciences, Environment and Society (https://www.sages.ac.uk/).

References & further reading

[1] Morecroft et al. (2009) The UK Environmental Change Network: Emerging trends in the composition of plant and animal communities and the physical environment. Biol Cons 142: 2814-32.[2] Willis & Whittaker (2002) Species Diversity – Scale Matters. Science 295: 1245-8.[3] Dawson et al. (2011) Beyond predictions: biodiversity conservation in a changing climate. Science 332: 53-8.[4] Magurran & Dornelas (2010) Biological diversity in a changing world. Philos Trans R Soc B 365: 3593-7.[5] Wolkovich et al. (2014) Temporal ecology in the Anthropocene. Ecol Lett 17: 1365–79.[6] Froyd & Willis (2008) Emerging issues in biodiversity & conservation management: The need for a palaeoecological perspective. Quat Sci Rev 27: 1723-32.[7] Maguire et al. (2015) Modeling Species and Community Responses to Past, Present, and Future Episodes of Climatic and Ecological Change. Ann Rev Ecol Evol S 46: 343-68.[8] Willis et al. (2005) Providing baselines for biodiversity measurement. Trends in Ecol & Evol 20: 107-8.[9] Davies et al. (2014) Improving the application of long-term ecology in conservation and land management. J Appl Ecol 51: 63-70.[10] Dornelas et al. (2018) BioTIME: A database of biodiversity time series for the Anthropocene. Glob Ecol Biogeog 27: 760-86.[11] Reitalu et al. (2015) Novel insights into post-glacial vegetation change: functional and phylogenetic diversity in pollen records. J Veg Sci 26: 911-22.[12] Carvalho et al. (2019) A method for reconstructing temporal changes in vegetation functional trait composition using Holocene pollen assemblages. PLoS ONE 14: e0216698.[13] Smart et al. (2006) Biotic homogenization and changes in species diversity across human-modified ecosystems. Proc Roy Soc B-Biol Sci 273: 2659-65.[14] Maskell et al. (2020) Long-term trends in the distribution, abundance and impact of native “injurious” weeds. Appl Veg Sci 23: 635-47.[15] Rose 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. Ecol Indic 68: 52–62.

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