Spatial Correlation Increase in Single‐Sensor Satellite Data Reveals Loss of Amazon Rainforest Resilience
Abstract The Amazon rainforest (ARF) is threatened by deforestation and climate change, which could trigger a regime shift to a savanna‐like state. Whilst previous work has suggested that forest resilience has declined in recent decades, that work was based only on local resilience indicators, and m...
Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2024-07-01
|
| Series: | Earth's Future |
| Subjects: | |
| Online Access: | https://doi.org/10.1029/2023EF004040 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832582843430076416 |
|---|---|
| author | Lana L. Blaschke Da Nian Sebastian Bathiany Maya Ben‐Yami Taylor Smith Chris A. Boulton Niklas Boers |
| author_facet | Lana L. Blaschke Da Nian Sebastian Bathiany Maya Ben‐Yami Taylor Smith Chris A. Boulton Niklas Boers |
| author_sort | Lana L. Blaschke |
| collection | DOAJ |
| description | Abstract The Amazon rainforest (ARF) is threatened by deforestation and climate change, which could trigger a regime shift to a savanna‐like state. Whilst previous work has suggested that forest resilience has declined in recent decades, that work was based only on local resilience indicators, and moreover was potentially biased by the employed multi‐sensor and optical satellite data and undetected anthropogenic land‐use change. Here, we show that the average correlation between neighboring grid cells' vegetation time series, which is referred to as spatial correlation, provides a more robust resilience indicator than local estimations. We employ it to measure resilience changes in the ARF, based on single‐sensor Vegetation Optical Depth data under conservative exclusion of human activity. Our results show an overall loss of resilience until around 2019, which is especially pronounced in the southwestern and northern Amazon for the time period from 2002 to 2011. The results from the reliable spatial correlation indicator suggest that in particular the southwest of the ARF has experienced pronounced resilience loss over the last two decades. |
| format | Article |
| id | doaj-art-15e2ecc85ce2427191081726a4a41f16 |
| institution | Kabale University |
| issn | 2328-4277 |
| language | English |
| publishDate | 2024-07-01 |
| publisher | Wiley |
| record_format | Article |
| series | Earth's Future |
| spelling | doaj-art-15e2ecc85ce2427191081726a4a41f162025-01-29T07:58:53ZengWileyEarth's Future2328-42772024-07-01127n/an/a10.1029/2023EF004040Spatial Correlation Increase in Single‐Sensor Satellite Data Reveals Loss of Amazon Rainforest ResilienceLana L. Blaschke0Da Nian1Sebastian Bathiany2Maya Ben‐Yami3Taylor Smith4Chris A. Boulton5Niklas Boers6Earth System Modeling School of Engineering and Design Technical University of Munich Munich GermanyPotsdam Institute for Climate Impact Research Potsdam GermanyEarth System Modeling School of Engineering and Design Technical University of Munich Munich GermanyEarth System Modeling School of Engineering and Design Technical University of Munich Munich GermanyInstitute of Geosciences University of Potsdam Potsdam GermanyGlobal Systems Institute University of Exeter Exeter UKEarth System Modeling School of Engineering and Design Technical University of Munich Munich GermanyAbstract The Amazon rainforest (ARF) is threatened by deforestation and climate change, which could trigger a regime shift to a savanna‐like state. Whilst previous work has suggested that forest resilience has declined in recent decades, that work was based only on local resilience indicators, and moreover was potentially biased by the employed multi‐sensor and optical satellite data and undetected anthropogenic land‐use change. Here, we show that the average correlation between neighboring grid cells' vegetation time series, which is referred to as spatial correlation, provides a more robust resilience indicator than local estimations. We employ it to measure resilience changes in the ARF, based on single‐sensor Vegetation Optical Depth data under conservative exclusion of human activity. Our results show an overall loss of resilience until around 2019, which is especially pronounced in the southwestern and northern Amazon for the time period from 2002 to 2011. The results from the reliable spatial correlation indicator suggest that in particular the southwest of the ARF has experienced pronounced resilience loss over the last two decades.https://doi.org/10.1029/2023EF004040Amazon rainforestvegetation resiliencecritical slowing downvegetation optical depth |
| spellingShingle | Lana L. Blaschke Da Nian Sebastian Bathiany Maya Ben‐Yami Taylor Smith Chris A. Boulton Niklas Boers Spatial Correlation Increase in Single‐Sensor Satellite Data Reveals Loss of Amazon Rainforest Resilience Earth's Future Amazon rainforest vegetation resilience critical slowing down vegetation optical depth |
| title | Spatial Correlation Increase in Single‐Sensor Satellite Data Reveals Loss of Amazon Rainforest Resilience |
| title_full | Spatial Correlation Increase in Single‐Sensor Satellite Data Reveals Loss of Amazon Rainforest Resilience |
| title_fullStr | Spatial Correlation Increase in Single‐Sensor Satellite Data Reveals Loss of Amazon Rainforest Resilience |
| title_full_unstemmed | Spatial Correlation Increase in Single‐Sensor Satellite Data Reveals Loss of Amazon Rainforest Resilience |
| title_short | Spatial Correlation Increase in Single‐Sensor Satellite Data Reveals Loss of Amazon Rainforest Resilience |
| title_sort | spatial correlation increase in single sensor satellite data reveals loss of amazon rainforest resilience |
| topic | Amazon rainforest vegetation resilience critical slowing down vegetation optical depth |
| url | https://doi.org/10.1029/2023EF004040 |
| work_keys_str_mv | AT lanalblaschke spatialcorrelationincreaseinsinglesensorsatellitedatarevealslossofamazonrainforestresilience AT danian spatialcorrelationincreaseinsinglesensorsatellitedatarevealslossofamazonrainforestresilience AT sebastianbathiany spatialcorrelationincreaseinsinglesensorsatellitedatarevealslossofamazonrainforestresilience AT mayabenyami spatialcorrelationincreaseinsinglesensorsatellitedatarevealslossofamazonrainforestresilience AT taylorsmith spatialcorrelationincreaseinsinglesensorsatellitedatarevealslossofamazonrainforestresilience AT chrisaboulton spatialcorrelationincreaseinsinglesensorsatellitedatarevealslossofamazonrainforestresilience AT niklasboers spatialcorrelationincreaseinsinglesensorsatellitedatarevealslossofamazonrainforestresilience |