Zigzag persistence for coral reef resilience using a stochastic spatial model
A complex interplay between species governs the evolution of spatial patterns in ecology. An open problem in the biological sciences is characterizing spatio-temporal data and understanding how changes at the local scale affect global dynamics/behaviour. Here, we extend a well-studied temporal mathe...
| Main Authors: | , , , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
Royal Society
2023
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| _version_ | 1811141115005370368 |
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| author | McDonald, RA Neuhausler, R Robinson, M Larsen, LG Harrington, HA Bruna, M |
| author_facet | McDonald, RA Neuhausler, R Robinson, M Larsen, LG Harrington, HA Bruna, M |
| author_sort | McDonald, RA |
| collection | OXFORD |
| description | A complex interplay between species governs the evolution of spatial patterns in ecology. An open problem in the biological sciences is characterizing spatio-temporal data and understanding how changes at the local scale affect global dynamics/behaviour. Here, we extend a well-studied temporal mathematical model of coral reef dynamics to include stochastic and spatial interactions and generate data to study different ecological scenarios. We present descriptors to characterize patterns in heterogeneous spatio-temporal data surpassing spatially averaged measures. We apply these descriptors to simulated coral data and demonstrate the utility of two topological data analysis techniques—persistent homology and zigzag persistence—for characterizing mechanisms of reef resilience. We show that the introduction of local competition between species leads to the appearance of coral clusters in the reef. We use our analyses to distinguish temporal dynamics stemming from different initial configurations of coral, showing that the neighbourhood composition of coral sites determines their long-term survival. Using zigzag persistence, we determine which spatial configurations protect coral from extinction in different environments. Finally, we apply this toolkit of multi-scale methods to empirical coral reef data, which distinguish spatio-temporal reef dynamics in different locations, and demonstrate the applicability to a range of datasets. |
| first_indexed | 2024-09-25T04:32:44Z |
| format | Journal article |
| id | oxford-uuid:f12bada8-b2b8-420e-8c31-2cc9bf2065a5 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-09-25T04:32:44Z |
| publishDate | 2023 |
| publisher | Royal Society |
| record_format | dspace |
| spelling | oxford-uuid:f12bada8-b2b8-420e-8c31-2cc9bf2065a52024-08-29T15:20:10ZZigzag persistence for coral reef resilience using a stochastic spatial modelJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:f12bada8-b2b8-420e-8c31-2cc9bf2065a5EnglishSymplectic ElementsRoyal Society2023McDonald, RANeuhausler, RRobinson, MLarsen, LGHarrington, HABruna, MA complex interplay between species governs the evolution of spatial patterns in ecology. An open problem in the biological sciences is characterizing spatio-temporal data and understanding how changes at the local scale affect global dynamics/behaviour. Here, we extend a well-studied temporal mathematical model of coral reef dynamics to include stochastic and spatial interactions and generate data to study different ecological scenarios. We present descriptors to characterize patterns in heterogeneous spatio-temporal data surpassing spatially averaged measures. We apply these descriptors to simulated coral data and demonstrate the utility of two topological data analysis techniques—persistent homology and zigzag persistence—for characterizing mechanisms of reef resilience. We show that the introduction of local competition between species leads to the appearance of coral clusters in the reef. We use our analyses to distinguish temporal dynamics stemming from different initial configurations of coral, showing that the neighbourhood composition of coral sites determines their long-term survival. Using zigzag persistence, we determine which spatial configurations protect coral from extinction in different environments. Finally, we apply this toolkit of multi-scale methods to empirical coral reef data, which distinguish spatio-temporal reef dynamics in different locations, and demonstrate the applicability to a range of datasets. |
| spellingShingle | McDonald, RA Neuhausler, R Robinson, M Larsen, LG Harrington, HA Bruna, M Zigzag persistence for coral reef resilience using a stochastic spatial model |
| title | Zigzag persistence for coral reef resilience using a stochastic spatial model |
| title_full | Zigzag persistence for coral reef resilience using a stochastic spatial model |
| title_fullStr | Zigzag persistence for coral reef resilience using a stochastic spatial model |
| title_full_unstemmed | Zigzag persistence for coral reef resilience using a stochastic spatial model |
| title_short | Zigzag persistence for coral reef resilience using a stochastic spatial model |
| title_sort | zigzag persistence for coral reef resilience using a stochastic spatial model |
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