Novel multivariate, high-resolution mapping of the exposure of ecosystems to climate and land use change

Project Information

CLIMLAN

Grant agreement ID: 748753

DOI

10.3030/748753

Project closed

EC signature date 14 November 2017

Start date 1 May 2018

End date 30 April 2020

Funded under

• EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions

Total cost

€ 177 598,80

EU contribution

€ 177 598,80

Coordinated by

UNIVERSITEIT UTRECHT
Netherlands

Periodic Reporting for period 1 - CLIMLAN (Novel multivariate, high-resolution mapping of the exposure of ecosystems to climate and land use change)

Reporting period: 2018-05-01 to 2020-04-30

Summary of the context and overall objectives of the project

Defining a fast-to-slow gradient of changes in climatic variables is not only useful to understand ecosystem dynamics. Still, it helps to identify mitigation and adaptation strategies aimed at addressing the impact of rapidly accelerating climatic changes. CLIMLAN tackles this challenge to establish what will be the ecological and conservation consequences of climate and land cover change. For this, CLIMLAN focused on evaluating the observed and expected changes in mean, phenological related, and extreme climatic conditions globally. It has also has estimated how fast natural and anthropogenic land cover has and will change. These changes have been evaluated using univariate and multidimensional exposure indices. Then these metrics have been overlapped with the current network of protected areas to assess the climatic safeguard potential of these areas.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

"The work done on CLIMLAN centred around three activities:
1. Data generation:
a. Generate spatial layers of Mean climatic conditions (daily) and land-cover percentages (yearly) between 1900 and 2010, with global coverage.
b. Estimate climatic variables of phenological relevance (Growing Degree Days, Number of days with daily precipitations above 10 mm) across the globe for every year between 1900 and 2010.
c. Estimate extreme climate indexes across the world for every year between 1900 and 2010.
d. Aggregate estimates of the percentage of different land-cover into different anthropogenic and natural categories.
2. Estimate univariate and multidimensional exposure indices:
. Estimate climate velocity (the relation between change in space and time) of individual variables using two different methodological advantages – done for multiple periods between 1900 and 2100.
a. Assess the multivariate velocity of change on climatic conditions – done for various periods between 1900 and 2100.
b. Estimate land-cover velocity (the relation between change in space and time) of individual variables using two different methodological advantages.
c. Assess the multivariate velocity of land-cover change – done for multiple periods between 1900 and 2100.
d. Combine land-cover and climate univariate and multidimensional velocity of changes into single visualizations.
3. Assessing the climate safeguard potential of the network of protected areas:
. Estimate the change in clitic conditions for the global network of protected areas.
a. Simulate how this change would have been in the area was placed at random in space 1000 times for each protected area globally.
b. Determine if the observed difference is larger-smaller than a randomly located area.
c. Assess how long will it take for climatic conditions to completely change within these areas.

The result of CLIMLAN are maps and ranks the speed at which different climate and land cover variables have changed been 1959 and 2013, showing that these changes can be placed in a fast-to-slow gradient. Spatial patterns in this ranking show substantial changes in the fastest/slowest-changing variable accords regions and neighbouring areas. This complexity translates into rearrangement in environmental conditions within the next decades in most protected areas. Addressing the impact of rapidly accelerating climatic changes means that mitigation and adaptation strategies need to consider the fast-to-slow gradient of climate change.

As part of the training activities, I also co-organized a session on the International Union of Quaternary Research 2019 ""Do species move, adapt or die? Exploring biodiversity dynamics in the fossil record"".

As part of the 2-way transfer of knowledge to the host institution, I offered several projects to MSc students. From the host institution, I gained insights on the management and processing of historical and future land cover predictions.

Supported by the fellowship I attended two conferences. The International Biogeography Society Biannual meeting (2019-Malaga) Where I presented some parallel work on the role of historical climate change on the functional composition of temperate floras. I also presented an oral contribution and a poster on the International Union of Quaternary Research 2019 meeting

I also took part in different networking initiatives, namely the TREECHANGE workgroup and the Botanical Information and Ecology Network (BIEN) 2019 meetings. The first aimed to link aiming to link changes in environmental conditions (climate and land cover) emerging from my project to shifts in tree cover and the implications of these changes for carbon sequestration and biodiversity protection. The second focused on linking the distribution data compiled in BIEN, to measurements of environmental change to assess the ""safe operating climatic spaces"" of plants at a global scale.

7 months before the end of the end date of the project, I moved to Aarhus University in Denmark to a tenure track assistant professor in botanical macroecology. But have continued working on the scientific publications coming from this grant two of which are currently under review."

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

Defining a fast-to-slow gradient of changes in climatic variables is more than a useful device for understanding ecosystem dynamics. It has practical value to define mitigation and adaptation strategies aimed at addressing the impact of rapidly accelerating climatic changes. Here, I map and rank the speed at which different climate variables have changed been 1959 and 2013, showing that these changes can be placed in a fast-to-slow gradient.
A novel aspect of this study is the shift on attention away from the long-running focus on average conditions (annual or seasonal) by also considering variables of phenological importance and extreme events.

Spatial patterns in this ranking show substantial changes in the fastest/slowest-changing variable accords regions and neighbouring areas. This complexity translates into rearrangement in climate conditions within the next decades in most protected areas. Furthermore, I here argue that in the fast-changing Anthropocene, the management of ecological systems is complex. This complexity emerges from the challenges of managing different rates of change across climatic variables with and between climatic dimensions. Addressing the impact of rapidly accelerating climatic changes means that mitigation and adaptation strategies need to consider the fast-to-slow gradient of climate change.

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