Periodic Reporting for period 4 - HOPE (Humans On Planet Earth - Long-term impacts on biosphere dynamics)
Berichtszeitraum: 2022-07-01 bis 2024-06-30
The project Humans on Planet Earth (HOPE) – Long-term Impacts on Biosphere Dynamics started in January 2018 and ended in June 2024. It was based in the Department of Biological Sciences, University of Bergen. The HOPE team consisted of John Birks (PI), Hilary Birks, Alistair Seddon & John-Arvid Grytnes (senior researchers), Kuber Bhatta, Vivian Felde, Suzette Flantua & Ondrej Mottl (post-doctoral research fellows), and Cathy Jenks, Linn Krüger & Arild Breistøl (assistants or computer engineer). HOPE also supported Manuel Steinbauer (Germany) and had as guest researchers Sandra Nogue (Spain) and Triin Reitalu (Estonia). It also had eight advisory mentors from the Netherlands, USA, Germany, Switzerland, and the Czech Republic - all experts on statistics, pollen analysis, computing, databases, plant geography, or human impact.
HOPE had two main objectives.
1. Test the hypothesis that prehistoric human impact altered the fundamental ecological processes that determine the assembly, ecological structure, and composition and dynamics of terrestrial plant communities. Its proponents argue the use of past ‘natural experiments’ and of the past as an analogue to our uncertain future is a “flawed strategy” and the basic concept behind Earth system science and all historical sciences, namely uniformitarianism (‘the present is the key to the past’) should be discarded. It was clearly imperative to test this hypothesis critically as it has far-reaching implications for science and society.
2. Test the associated hypothesis that inter-relationships (correlations) between estimates of ecosystem properties such as turnover, diversity, composition, and rate-of-change (RoC) during the Holocene (last 11,700 years) changed in response to prehistoric human activities.
Testing these two hypotheses is important for the modus operandi of Earth system science, global change biology, and ecological and societal predictions as a whole. If the hypotheses are not falsified, the question arises can the past be used reliably as an analogue to the uncertain future of Planet Earth and its inhabitants in the ‘Anthropocene’. If the hypotheses are not falsified, Earth today has no analogue in the past 11,700 years and the widely employed research approach of using ‘natural experiments’ in the past as a guide to predict what might happen in the future is a “flawed strategy” and should be discontinued. As almost all predictive models in global-change science rely on this approach, these hypotheses needed testing. This was the primary aim of HOPE.
HOPE’s research relied on dated pollen-stratigraphical data from lakes or mires in Europe, Asia, North America, Central & South America, and Oceania. These data were explored in a consistent manner using state-of-the-art numerical techniques to discern patterns in over 15 ecosystem properties. Temporal, spatial, and correlation patterns in these properties were compared statistically within each pollen sequence, between sequences within ecoregions (≡ biomes), between ecoregions within continents, between ecoregions on different continents, and between continents using statistical modelling techniques with human-impact events along with model-simulated climate variables as predictors.
HOPE had two main objectives.
1. Test the hypothesis that prehistoric human impact altered the fundamental ecological processes that determine the assembly, ecological structure, and composition and dynamics of terrestrial plant communities. Its proponents argue the use of past ‘natural experiments’ and of the past as an analogue to our uncertain future is a “flawed strategy” and the basic concept behind Earth system science and all historical sciences, namely uniformitarianism (‘the present is the key to the past’) should be discarded. It was clearly imperative to test this hypothesis critically as it has far-reaching implications for science and society.
2. Test the associated hypothesis that inter-relationships (correlations) between estimates of ecosystem properties such as turnover, diversity, composition, and rate-of-change (RoC) during the Holocene (last 11,700 years) changed in response to prehistoric human activities.
Testing these two hypotheses is important for the modus operandi of Earth system science, global change biology, and ecological and societal predictions as a whole. If the hypotheses are not falsified, the question arises can the past be used reliably as an analogue to the uncertain future of Planet Earth and its inhabitants in the ‘Anthropocene’. If the hypotheses are not falsified, Earth today has no analogue in the past 11,700 years and the widely employed research approach of using ‘natural experiments’ in the past as a guide to predict what might happen in the future is a “flawed strategy” and should be discontinued. As almost all predictive models in global-change science rely on this approach, these hypotheses needed testing. This was the primary aim of HOPE.
HOPE’s research relied on dated pollen-stratigraphical data from lakes or mires in Europe, Asia, North America, Central & South America, and Oceania. These data were explored in a consistent manner using state-of-the-art numerical techniques to discern patterns in over 15 ecosystem properties. Temporal, spatial, and correlation patterns in these properties were compared statistically within each pollen sequence, between sequences within ecoregions (≡ biomes), between ecoregions within continents, between ecoregions on different continents, and between continents using statistical modelling techniques with human-impact events along with model-simulated climate variables as predictors.
The HOPE project has addressed the following three major parts of the entire project.
(1) Development of a rigorous workflow in R to capture, evaluate, format, filter, and check all relevant datasets available in databases such as Neotoma and Pangea. So far about 500 pollen-sequences have been processed from Europe, about 800 from North America, and about 150 from Asia. Work is in progress on expanding Asian coverage, in developing a Latin American pollen database (ca. 150 sequences), and in acquiring Oceania pollen data. Robust age-depth models using chronological controls for each sequence have been made using Bayesian modelling (Bchron) with 50,000 runs to derive model uncertainties.
(2) Ecosystem properties such as diversity, compositional change, and turnover have been estimated for the sequences using the newly developed REcopol package (https://hope-uib-bio.github.io/R-Ecopol-package/). Some properties have turned out to be impossible to derive for the global scale of HOPE. These are functional diversity and spatial beta-diversity. It is impossible to estimate biomass due to insufficient data. Dark diversity is more difficult to estimate than originally envisaged and may be discarded. A new approach to estimate RoC (=temporal beta-diversity) from pollen data has been developed. Taxon-pair co-occurrences have turned out to be uninformative when applied to pollen data and have been discarded.
(3) Multivariate regression approaches have been used to test the statistical significance of relationships between temporal changes in ecosystem properties (responses) and the human-impact events and climate (predictors). Both Hypothesis 1 and Hypothesis 2 have been falsified for the five geographical areas. The principle of uniformitarianism therefore still stands.
(1) Development of a rigorous workflow in R to capture, evaluate, format, filter, and check all relevant datasets available in databases such as Neotoma and Pangea. So far about 500 pollen-sequences have been processed from Europe, about 800 from North America, and about 150 from Asia. Work is in progress on expanding Asian coverage, in developing a Latin American pollen database (ca. 150 sequences), and in acquiring Oceania pollen data. Robust age-depth models using chronological controls for each sequence have been made using Bayesian modelling (Bchron) with 50,000 runs to derive model uncertainties.
(2) Ecosystem properties such as diversity, compositional change, and turnover have been estimated for the sequences using the newly developed REcopol package (https://hope-uib-bio.github.io/R-Ecopol-package/). Some properties have turned out to be impossible to derive for the global scale of HOPE. These are functional diversity and spatial beta-diversity. It is impossible to estimate biomass due to insufficient data. Dark diversity is more difficult to estimate than originally envisaged and may be discarded. A new approach to estimate RoC (=temporal beta-diversity) from pollen data has been developed. Taxon-pair co-occurrences have turned out to be uninformative when applied to pollen data and have been discarded.
(3) Multivariate regression approaches have been used to test the statistical significance of relationships between temporal changes in ecosystem properties (responses) and the human-impact events and climate (predictors). Both Hypothesis 1 and Hypothesis 2 have been falsified for the five geographical areas. The principle of uniformitarianism therefore still stands.
In terms of progress beyond the state-of-the-art, HOPE has achieved the following:
Development of cutting-edge software for paleoecological research, specifically:
1. FOSSILPOL: Development of a complete R workflow for inputting basic pollen-stratigraphical data and associated meta-data from various sources, re-formatting and tabulating the data, applying quality-control criteria, developing Bayesian age-depth models, harmonisation of nomenclature between sequences within an area, and final quality-control filtering (see Figure) to produce the data used in numerical analysis. It is a tool for the global science community to extract relevant pollen sequences for synthesis studies, while maintaining high data quality and promoting reproducibility in research. The software and guidelines accompanying it have been published in Global Ecology and Biogeography. See https://hope-uib-bio.github.io/FOSSILPOL-website/ for further details.
2. R-Ratepol: An important ecosystem property is rate-of-change (RoC) analysis. This estimates the amount of pollen compositional change per unit time. This analysis, first presented in 1986, has a major limitation, namely that the uneven temporal distribution of samples can produce an artefact in RoC estimation. HOPE has developed a statistically rigorous package to analyse RoC and identify peaks of significantly high RoC values, which allows the comparison of RoC at many sites in the same ecoregion or between ecoregions or continents. The RRatepol package has been published in Review in Palaeobotany and Palynology. See https://hope-uib-bio.github.io/R-Ratepol-package/ for more details.
3. R-Ecopol: This R package is a compilation of easy-to-use functions to analyse fossil pollen data and thus lower barriers to scientific exploration. The package contains functions for several key analytical techniques, for example, diversity estimation (including taxonomic, functional, and phylogenetic diversity), multivariate ordinations (including detrended canonical correspondence analysis (DCCA), which was missing in the R ecosystem), temporal analyses, generalised additive models (including Hierarchical GAMs), change-point analyses, regression partitioning, etc. See https://hope-uib-bio.github.io/R-Ecopol-package/ for more details.
Applying and refining these tools has helped HOPE accomplish its goals of testing hypotheses 1 and 2.
Development of cutting-edge software for paleoecological research, specifically:
1. FOSSILPOL: Development of a complete R workflow for inputting basic pollen-stratigraphical data and associated meta-data from various sources, re-formatting and tabulating the data, applying quality-control criteria, developing Bayesian age-depth models, harmonisation of nomenclature between sequences within an area, and final quality-control filtering (see Figure) to produce the data used in numerical analysis. It is a tool for the global science community to extract relevant pollen sequences for synthesis studies, while maintaining high data quality and promoting reproducibility in research. The software and guidelines accompanying it have been published in Global Ecology and Biogeography. See https://hope-uib-bio.github.io/FOSSILPOL-website/ for further details.
2. R-Ratepol: An important ecosystem property is rate-of-change (RoC) analysis. This estimates the amount of pollen compositional change per unit time. This analysis, first presented in 1986, has a major limitation, namely that the uneven temporal distribution of samples can produce an artefact in RoC estimation. HOPE has developed a statistically rigorous package to analyse RoC and identify peaks of significantly high RoC values, which allows the comparison of RoC at many sites in the same ecoregion or between ecoregions or continents. The RRatepol package has been published in Review in Palaeobotany and Palynology. See https://hope-uib-bio.github.io/R-Ratepol-package/ for more details.
3. R-Ecopol: This R package is a compilation of easy-to-use functions to analyse fossil pollen data and thus lower barriers to scientific exploration. The package contains functions for several key analytical techniques, for example, diversity estimation (including taxonomic, functional, and phylogenetic diversity), multivariate ordinations (including detrended canonical correspondence analysis (DCCA), which was missing in the R ecosystem), temporal analyses, generalised additive models (including Hierarchical GAMs), change-point analyses, regression partitioning, etc. See https://hope-uib-bio.github.io/R-Ecopol-package/ for more details.
Applying and refining these tools has helped HOPE accomplish its goals of testing hypotheses 1 and 2.