The Regenerative Potential of Managed Calluna Heathlands—Revealing Optical and Structural Traits for Predicting Recovery Dynamics
The potential of vegetation recovery through resprouting of plant tissue from buds after the removal of aboveground biomass is a key resilience strategy for populations under abrupt environmental change. Resprouting leads to fast regeneration, particularly after the implementation of mechanical mowi...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-02-01
|
| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/13/4/625 |
| _version_ | 1797412167898628096 |
|---|---|
| author | Carsten Neumann Anne Schindhelm Jörg Müller Gabriele Weiss Anna Liu Sibylle Itzerott |
| author_facet | Carsten Neumann Anne Schindhelm Jörg Müller Gabriele Weiss Anna Liu Sibylle Itzerott |
| author_sort | Carsten Neumann |
| collection | DOAJ |
| description | The potential of vegetation recovery through resprouting of plant tissue from buds after the removal of aboveground biomass is a key resilience strategy for populations under abrupt environmental change. Resprouting leads to fast regeneration, particularly after the implementation of mechanical mowing as part of active management for promoting open habitats. We investigated whether recovery dynamics of resprouting and the threat of habitat conversion can be predicted by optical and structural stand traits derived from drone imagery in a protected heathland area. We conducted multivariate regression for variable selection and random forest regression for predictive modeling using 50 spectral predictors, textural features and height parameters to quantify <i>Calluna</i> resprouting and grass invasion in before-mowing images that were related to vegetation recovery in after-mowing imagery. The study reveals that <i>Calluna</i> resprouting can be explained by significant optical predictors of mainly green reflectance in parental individuals. In contrast, grass encroachment is identified by structural canopy properties that indicate before-mowing grass interpenetration as starting points for after-mowing dispersal. We prove the concept of trait propagation through time providing significant derivates for a low-cost drone system. It can be utilized to build drone-based decision support systems for evaluating consequences and requirements of habitat management practice. |
| first_indexed | 2024-03-09T04:58:11Z |
| format | Article |
| id | doaj.art-798d35585bef4f2189f1c27631ca163b |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-09T04:58:11Z |
| publishDate | 2021-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-798d35585bef4f2189f1c27631ca163b2023-12-03T13:03:31ZengMDPI AGRemote Sensing2072-42922021-02-0113462510.3390/rs13040625The Regenerative Potential of Managed Calluna Heathlands—Revealing Optical and Structural Traits for Predicting Recovery DynamicsCarsten Neumann0Anne Schindhelm1Jörg Müller2Gabriele Weiss3Anna Liu4Sibylle Itzerott5Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences, 14473 Potsdam, GermanyHelmholtz Centre Potsdam GFZ German Research Centre for Geosciences, 14473 Potsdam, GermanyHeinz Sielmann Foundation, 14641 Wustermark (OT Elstal), GermanyEcostrat GmbH Berlin, 12203 Berlin, GermanyGeoinformation in Environmental Planning Lab, Technische Universität Berlin, 10623 Berlin, GermanyHelmholtz Centre Potsdam GFZ German Research Centre for Geosciences, 14473 Potsdam, GermanyThe potential of vegetation recovery through resprouting of plant tissue from buds after the removal of aboveground biomass is a key resilience strategy for populations under abrupt environmental change. Resprouting leads to fast regeneration, particularly after the implementation of mechanical mowing as part of active management for promoting open habitats. We investigated whether recovery dynamics of resprouting and the threat of habitat conversion can be predicted by optical and structural stand traits derived from drone imagery in a protected heathland area. We conducted multivariate regression for variable selection and random forest regression for predictive modeling using 50 spectral predictors, textural features and height parameters to quantify <i>Calluna</i> resprouting and grass invasion in before-mowing images that were related to vegetation recovery in after-mowing imagery. The study reveals that <i>Calluna</i> resprouting can be explained by significant optical predictors of mainly green reflectance in parental individuals. In contrast, grass encroachment is identified by structural canopy properties that indicate before-mowing grass interpenetration as starting points for after-mowing dispersal. We prove the concept of trait propagation through time providing significant derivates for a low-cost drone system. It can be utilized to build drone-based decision support systems for evaluating consequences and requirements of habitat management practice.https://www.mdpi.com/2072-4292/13/4/625resproutinghabitat managementheathlandtrait mappingUAV |
| spellingShingle | Carsten Neumann Anne Schindhelm Jörg Müller Gabriele Weiss Anna Liu Sibylle Itzerott The Regenerative Potential of Managed Calluna Heathlands—Revealing Optical and Structural Traits for Predicting Recovery Dynamics Remote Sensing resprouting habitat management heathland trait mapping UAV |
| title | The Regenerative Potential of Managed Calluna Heathlands—Revealing Optical and Structural Traits for Predicting Recovery Dynamics |
| title_full | The Regenerative Potential of Managed Calluna Heathlands—Revealing Optical and Structural Traits for Predicting Recovery Dynamics |
| title_fullStr | The Regenerative Potential of Managed Calluna Heathlands—Revealing Optical and Structural Traits for Predicting Recovery Dynamics |
| title_full_unstemmed | The Regenerative Potential of Managed Calluna Heathlands—Revealing Optical and Structural Traits for Predicting Recovery Dynamics |
| title_short | The Regenerative Potential of Managed Calluna Heathlands—Revealing Optical and Structural Traits for Predicting Recovery Dynamics |
| title_sort | regenerative potential of managed calluna heathlands revealing optical and structural traits for predicting recovery dynamics |
| topic | resprouting habitat management heathland trait mapping UAV |
| url | https://www.mdpi.com/2072-4292/13/4/625 |
| work_keys_str_mv | AT carstenneumann theregenerativepotentialofmanagedcallunaheathlandsrevealingopticalandstructuraltraitsforpredictingrecoverydynamics AT anneschindhelm theregenerativepotentialofmanagedcallunaheathlandsrevealingopticalandstructuraltraitsforpredictingrecoverydynamics AT jorgmuller theregenerativepotentialofmanagedcallunaheathlandsrevealingopticalandstructuraltraitsforpredictingrecoverydynamics AT gabrieleweiss theregenerativepotentialofmanagedcallunaheathlandsrevealingopticalandstructuraltraitsforpredictingrecoverydynamics AT annaliu theregenerativepotentialofmanagedcallunaheathlandsrevealingopticalandstructuraltraitsforpredictingrecoverydynamics AT sibylleitzerott theregenerativepotentialofmanagedcallunaheathlandsrevealingopticalandstructuraltraitsforpredictingrecoverydynamics AT carstenneumann regenerativepotentialofmanagedcallunaheathlandsrevealingopticalandstructuraltraitsforpredictingrecoverydynamics AT anneschindhelm regenerativepotentialofmanagedcallunaheathlandsrevealingopticalandstructuraltraitsforpredictingrecoverydynamics AT jorgmuller regenerativepotentialofmanagedcallunaheathlandsrevealingopticalandstructuraltraitsforpredictingrecoverydynamics AT gabrieleweiss regenerativepotentialofmanagedcallunaheathlandsrevealingopticalandstructuraltraitsforpredictingrecoverydynamics AT annaliu regenerativepotentialofmanagedcallunaheathlandsrevealingopticalandstructuraltraitsforpredictingrecoverydynamics AT sibylleitzerott regenerativepotentialofmanagedcallunaheathlandsrevealingopticalandstructuraltraitsforpredictingrecoverydynamics |