Seasonal drivers of understorey temperature buffering in temperate deciduous forests across Europe
Zellweger, Florian ; Coomes, David ; Lenoir, Jonathan ; Depauw, Leen ; Maes, Sybryn L. ; Wulf, Monika ; Kirby, Keith J. ; Brunet, Jörg ; Kopecký, Martin ; Máliš, František ; Schmidt, Wolfgang ; Heinrichs, Steffi ; Ouden, Jan den; Jaroszewicz, Bogdan ; Buyse, Gauthier ; Spicher, Fabien ; Verheyen, Kris ; Frenne, Pieter De - \ 2019
Global Ecology and Biogeography 28 (2019)12. - ISSN 1466-822X - p. 1774 - 1786.
canopy density - climate change - forest composition - forest structure - global warming - macroclimate - microclimate - temperature buffering - understorey
Aim: Forest understorey microclimates are often buffered against extreme heat or cold, with important implications for the organisms living in these environments. We quantified seasonal effects of understorey microclimate predictors describing canopy structure, canopy composition and topography (i.e., local factors) and the forest patch size and distance to the coast (i.e., landscape factors). Location: Temperate forests in Europe. Time period: 2017–2018. Major taxa studied: Woody plants. Methods: We combined data from a microclimate sensor network with weather-station records to calculate the difference, or offset, between temperatures measured inside and outside forests. We used regression analysis to study the effects of local and landscape factors on the seasonal offset of minimum, mean and maximum temperatures. Results: The maximum temperature during the summer was on average cooler by 2.1 °C inside than outside forests, and the minimum temperatures during the winter and spring were 0.4 and 0.9 °C warmer. The local canopy cover was a strong nonlinear driver of the maximum temperature offset during summer, and we found increased cooling beneath tree species that cast the deepest shade. Seasonal offsets of minimum temperature were mainly regulated by landscape and topographic features, such as the distance to the coast and topographic position. Main conclusions: Forest organisms experience less severe temperature extremes than suggested by currently available macroclimate data; therefore, climate–species relationships and the responses of species to anthropogenic global warming cannot be modelled accurately in forests using macroclimate data alone. Changes in canopy cover and composition will strongly modulate the warming of maximum temperatures in forest understories, with important implications for understanding the responses of forest biodiversity and functioning to the combined threats of land-use change and climate change. Our predictive models are generally applicable across lowland temperate deciduous forests, providing ecologically important microclimate data for forest understories.
Supplementary material from "Interactive effects of tree size, crown exposure and logging on drought-induced mortality"
Shenkin, Alexander ; Bolker, Benjamin ; Pena Claros, Marielos ; Licona, Juan Carlos ; Ascarrunz, Nataly ; Putz, Francis E. - \ 2018
University of Florida
drought - tree mortality - climate change - tropical forest - logging - forest structure - resilience - climate adaptation
Large trees in the tropics are reportedly more vulnerable to droughts than their smaller neighbours. This pattern is of interest due to what it portends for forest structure, timber production, carbon sequestration and multiple other values given that intensified El Niño Southern Oscillation (ENSO) events are expected to increase the frequency and intensity of droughts in the Amazon region. What remains unclear is what characteristics of large trees renders them especially vulnerable to drought-induced mortality and how this vulnerability changes with forest degradation. Using a large-scale, long-term silvicultural experiment in a transitional Amazonian forest in Bolivia, we disentangle the effects of stem diameter, tree height, crown exposure and logging-induced degradation on risks of drought-induced mortality during the 2004/2005 ENSO event. Overall, tree mortality increased in response to drought in both logged and unlogged plots. Tree height was a much stronger predictor of mortality than stem diameter. In unlogged plots, tree height but not crown exposure was positively associated with drought-induced mortality, whereas in logged plots, neither tree height nor crown exposure was associated with drought-induced mortality. Our results suggest that at the scale of a site, hydraulic factors related to tree height, not air humidity, are a cause of elevated drought-induced mortality of large trees in unlogged plots.This article is part of a discussion meeting issue ‘The impact of the 2015/2016 El Nino on the terrestrial tropical carbon cycle: patterns, mechanisms and implications'.
Fire effects and ecological recovery pathways of tropical montane cloud forests along a time chronosequence
Oliveras, Imma ; Román-Cuesta, Rosa M. ; Urquiaga-Flores, Erickson ; Quintano Loayza, Jose A. ; Kala, Jose ; Huamán, Vicky ; Lizárraga, Nohemi ; Sans, Guissela ; Quispe, Katia ; Lopez, Efrain ; Lopez, David ; Cuba Torres, Israel ; Enquist, Brian J. ; Malhi, Yadvinder - \ 2018
Global Change Biology 24 (2018)2. - ISSN 1354-1013 - p. 758 - 772.
carbon allocation - forest structure - metabolic scaling theory - regeneration - species diversity
Tropical montane cloud forests (TMCFs) harbour high levels of biodiversity and large carbon stocks. Their location at high elevations make them especially sensitive to climate change, because a warming climate is enhancing upslope species migration, but human disturbance (especially fire) may in many cases be pushing the treeline downslope. TMCFs are increasingly being affected by fire, and the long-term effects of fire are still unknown. Here, we present a 28-year chronosequence to assess the effects of fire and recovery pathways of burned TMCFs, with a detailed analysis of carbon stocks, forest structure and diversity. We assessed rates of change of carbon (C) stock pools, forest structure and tree-size distribution pathways and tested several hypotheses regarding metabolic scaling theory (MST), C recovery and biodiversity. We found four different C stock recovery pathways depending on the selected C pool and time since last fire, with a recovery of total C stocks but not of aboveground C stocks. In terms of forest structure, there was an increase in the number of small stems in the burned forests up to 5–9 years after fire because of regeneration patterns, but no differences on larger trees between burned and unburned plots in the long term. In support of MST, after fire, forest structure appears to approximate steady-state size distribution in less than 30 years. However, our results also provide new evidence that the species recovery of TMCF after fire is idiosyncratic and follows multiple pathways. While fire increased species richness, it also enhanced species dissimilarity with geographical distance. This is the first study to report a long-term chronosequence of recovery pathways to fire suggesting faster recovery rates than previously reported, but at the expense of biodiversity and aboveground C stocks.
Multidimensional remote sensing based mapping of tropical forests and their dynamics
Dutrieux, L.P. - \ 2016
Wageningen University. Promotor(en): Martin Herold, co-promotor(en): Lammert Kooistra; Lourens Poorter. - Wageningen : Wageningen UR - ISBN 9789462578906 - 146
tropical forests - remote sensing - mapping - biodiversity - forest structure - monitoring - land use - landsat - tropische bossen - remote sensing - cartografie - biodiversiteit - bosstructuur - monitoring - landgebruik - landsat
Tropical forests concentrate a large part of the terrestrial biodiversity, provide important resources, and deliver many ecosystem services such as climate regulation, carbon sequestration, and hence climate change mitigation. While in the current context of anthropogenic pressure these forests are threatened by deforestation, forest degradation and climate change, they also have shown to be, in certain cases, highly resilient and able to recover from disturbances. Quantitative measures of forest resources and insights into their dynamics and functioning are therefore crucial in this context of climate and land use change. Sensors on-board satellites have been collecting a large variety of data about the surface of the earth in a systematic and objective way, making remote sensing a tool that holds tremendous potential for mapping and monitoring the earth. The main aim of this research is to explore the potential of remote sensing for mapping forest attributes and dynamics. Tropical South America, which contains the largest area of tropical forest on the planet, and is therefore of global significance, is the regional focus of the research. Different methods are developed and assessed to: (i) map forest attributes at national scale, (ii) detect forest cover loss, (iii) quantify land use intensity over shifting cultivation landscapes, and (iv) measure spectral recovery and resilience of regrowing forests.
Remote sensing data are diverse and multidimensional; a constellation of satellite sensors collects data at various spatial, temporal and spectral resolutions, which can be used to inform on different components of forests and their dynamics. To better map and monitor ecological processes, which are inherently multidimensional, this thesis develops methods that combine multiple data sources, and integrate the spatial, temporal and spectral dimensions contained in remote sensing datasets. This is achieved for instance by assembling time-series to fully exploit the temporal signal contained in the data, or by working with multiple spectral channels as a way to better capture subtle ecological features and processes.
After introducing the general objectives of the thesis in Chapter 1, Chapter 2 presents an approach for mapping forest attributes at national scale. In this chapter, 28 coarse resolution remote sensing predictors from diverse sources are used in combination with in-situ data from 220 forest inventory plots to predict nine forest attributes over lowland Bolivia. The attributes include traditional forest inventory variables such as forest structure, floristic properties, and abundance of life forms. Modelling is done using the random forest approach and reasonable prediction potential was found for variables related to floristic properties, while forest attributes relating to structure had a low prediction potential. This methodological development demonstrates the potential of coarse resolution remote sensing for scaling local in-situ ecological measurements to country-wide maps, thus providing information that is highly valuable for biodiversity conservation, resource use planning, and for understanding tropical forest functioning.
Chapter 3 presents an approach to detect forest cover loss from remote sensing time-series. While change detection has been the object of many studies, the novel contribution of the present example concerns the capacity to detect change in environments with strong inter-annual variations, such as seasonally dry tropical forests. By combining Landsat with Moderate Resolution Imaging Spectroradiometer (MODIS) time-series in a change detection framework, the approach provides information at 30 m resolution on forest cover loss, while normalizing for the natural variability of the ecosystem that would otherwise be detected as change. The proposed approach of combining two data streams at different spatial resolutions provides the opportunity to distinguish anthropogenic disturbances from natural change in tropical forests.
Chapter 4 introduces a new method to quantify land use intensity in swidden agriculture systems, using remote sensing time-series. Land use intensity — a parameter known for influencing forest resilience — is retrieved in this case by applying a temporal segmentation algorithm derived from the econometrics field and capable of identifying shifts in land dynamic regimes, to Landsat time-series. These shifts, or breakpoints, are then classified into the different events of the swidden agriculture cycle, which allows to quantify the number of cultivation cycles that has taken place for a given agricultural field. The method enables the production of objective and spatially continuous information on land use intensity for large areas, hence benefiting the study of spatio-temporal patterns of land use and the resulting forest resilience. The results were validated against an independent dataset of reported cultivation frequency and proved to be a reliable indicator of land use intensity.
Chapter 5 further explores the concept of forest resilience. A framework to quantify spectral recovery time of forests that regrow after disturbance is developed, and applied to regrowing forests of the Amazon. Spatial patterns of spectral resilience as well as relations with environmental conditions are explored. Regrowing forests take on average 7.8 years to recover their spectral properties, and large variations in spectral recovery time occur at a local scale. This large local variability suggests that local factors, rather than climate, drive the spectral recovery of tropical forests. While spectral recovery times do not directly correspond to the time required for complete recovery of the biomass and species pool of tropical forests, they provide an indication on the kinetics of the early stages of forest regrowth.
Chapter 6 summarizes the main findings of the thesis and provides additional reflections and prospects for future research. By predicting forest attributes country-wide or retrieving land use history over the 30 years time-span of the Landsat archive, the developed methods provide insights at spatial and temporal scales that are beyond the reach of ground based data collection methods. Remote sensing was therefore able to provide valuable information for better understanding, managing and conserving tropical forest ecosystems, and this was partly achieved by combining multiple sources of data and taking advantage of the available remote sensing dimensions. However, the work presented only explores a small part of the potential of remote sensing, so that future research should intensively focus on further exploiting the multiple dimensions and multi-scale nature of remote sensing data as a way to provide insights on complex multi-scale processes such as interactions between climate change, anthropogenic pressure, and ecological processes. Inspired by recent advances in operational forest monitoring, operationalization of scientific methods to retrieve ecological variables from remote sensing is also discussed. Such transfer of scientific advances to operational platforms that can automatically produce and update ecologically relevant variables globally would largely benefit ecological research, public awareness and the conservation and wise use of natural resources.
Patterns of covariance between airborne laser scanning metrics and Lorenz curve descriptors of tree size inequality
Valbuena, R. ; Maltamo, M. ; Martín-Fernández, S. ; Packalén, P. ; Pascual, C. ; Nabuurs, G.J. - \ 2013
Canadian Journal of Remote Sensing 39 (2013)Suppl. 1. - ISSN 1712-7971 - p. S18 - S31.
nearest-neighbor imputation - partial least-squares - forest structure - lidar data - stand - regression - inventory - northwest - selection - canopies
The Lorenz curve, as a descriptor of tree size inequality within a stand, has been suggested as a reliable means for characterizing forest structure and distinguishing even from uneven-sized areas. The aim of this study was to achieve a thorough understanding on the relations between airborne laser scanning (ALS) metrics and indicators based on Lorenz curve ordering: Gini coefficient (GC) and Lorenz asymmetry (S). Exploratory multivariate analysis was carried out using correlation tests, partial least squares (PLS), and an information-theoretic approach for multimodel inference (MMI). Best subset linear model was selected for GC and S prediction, as variable transformations yielded no improvement in the relation of ALS with the given response. Relative variable importance based on the MMI model showed that GC is best predicted by ALS metrics expressing canopy coverage, return dispersion, and low high percentile combinations. Although ALS metrics showed no correlation with S, they did so against its constituting components: the proportions of basal area (Mg) and stem density (xg) stocked above the mean quadratic diameter. The study of PLS loading vectors illustrated how ALS metrics explain variance in opposing directions for each of these components, so that their effects cancel each other out in the overall S. Cross-validation showed that only marginal differences are nevertheless found between predicting S directly or as the sum Mg and xg estimations. The differing relation of diverse ALS metrics was therefore observed for Mg and xg. The conclusions obtained by this research may assist in selecting relevant Lorenz curve descriptors for forest structure characterization, as well as in variable reduction strategies for their wall-to-wall prediction by means of ALS metrics.
Investigating assumptions of crown archetypes for modelling LiDAR returns
Calders, K. ; Lewis, P. ; Disney, M. ; Verbesselt, J. ; Herold, M. - \ 2013
Remote Sensing of Environment 134 (2013). - ISSN 0034-4257 - p. 39 - 49.
wave-form lidar - forest structure - biophysical properties - canopy structure - simulation
LiDAR has the potential to derive canopy structural information such as tree height and leaf area index (LAI), via models of the LiDAR signal. Such models often make assumptions regarding crown shape to simplify parameter retrieval and crown archetypes are typically assumed to contain a turbid medium to account for within-crown scattering. However, these assumptions may make it difficult to relate derived structural parameters to measurable canopy properties. Here, we test the impact of crown archetype assumptions by developing a new set of analytical expressions for modelling LiDAR signals. The expressions for three crown archetypes (cuboids, cones and spheroids) are derived from the radiative transfer solution for single order scattering in the optical case and are a function of crown macro-structure (height and crown extent) and LAI. We test these expressions against waveforms simulated using a highly-detailed 3D radiative transfer model, for LAI ranging from one to six. This allows us to control all aspects of the crown structure and LiDAR characteristics. The analytical expressions are fitted to both the original and the cumulative simulated LiDAR waveforms and the CV(RMSE) of model fit over archetype trees ranges from 0.3% to 21.2%. The absolute prediction error (APE) for LAI is 7.1% for cuboid archetypes, 18.6% for conical archetypes and 4.5% for spheroid archetypes. We then test the analytical expressions against more realistic 3D representations of broadleaved deciduous (birch) and evergreen needle-leaved (Sitka spruce) tree crowns. The analytical expressions perform more poorly (APE values up to 260.9%, typically ranging from 39.4% to 78.6%) than for the archetype shapes and ignoring clumping and lower branches has a significant influence on the performance of waveform inversion of realistic trees. The poor performance is important as it suggests that the assumption of crown archetypes can result in significant errors in retrieved crown parameters due to these assumptions not being met in real trees. Seemingly reasonable inferred values may arise due to coupling between parameters. Our results suggest care is needed in inferring biophysical properties based on crown archetypes. Relationships between the derived parameters and their physical counterparts need further elucidation
The Liana assemblage of a Congolian rainforest : diversity, structure and dynamics
Ewango Ekokinya, Corneille - \ 2010
Wageningen University. Promotor(en): Frans Bongers; Marc Sosef; Lourens Poorter. - [S.l.] : s.n. - ISBN 9789085858133 - 161
climbing plants - rain forests - species diversity - species richness - forest ecology - congo - forest structure - klimplanten - regenbossen - soortendiversiteit - soortenrijkdom - bosecologie - congo - bosstructuur
Key words: Liana assemblage, species composition, community, dynamics, canopy openness, Manniophyton fulvum, functional traits, population density, pervasive change.
This study analyzes the diversity, composition, and dynamics of the liana assemblage of the Ituri rain forest in northeastern DR Congo. I used data from two 10-ha plots of the Ituri Forest Dynamics Plots, in which all liana stems ≥2 cm diameter at breast height (dbh) were marked, mapped, measured and identified in 1994, 2001 and 2007. In addition, the plot topography and canopy structure were measured.
Chapter 2 analyzes the liana assemblage (in terms of species richness, abundance and diversity), characterizes liana functional traits and determines effects of forest structure, topography and edaphic variation on liana species composition. In 20 ha, 15008 liana individuals were found, representing 195 species, 83 genera and 34 plant families. Per hectare species number averaged 64, basal area was 0.71 m2 and Fisher alpha, Shannon and Simpson diversity indices were 17.9, 3.1 and 11.4, respectively. There was oligarchic dominance of 10 plant families that represented 69% of total species richness, 92% of liana abundance and 92% of basal area, while ten dominant species accounted for 63% of abundance and 59% of basal area. Forty-one species (21%) were represented by one individual only. Most lianas were light-demanding, climbed their hosts by twining, and had conspicuous flowers, medium-sized leaves and animal-dispersed propagules. Liana abundance increased with abundance of medium-sized and large trees but was, surprisingly, independent of small-tree abundance. Canopy openness, soil moisture, and tree size were the most important environmental factors influencing abundance and distribution of lianas.
In Chapter 3 I investigate changes in structural characteristics, diversity, recruitment, mortality and growth of the liana community over the thirteen years (1994 ¬- 2007). Liana density decreased from 750 (1994) through 547 (2001) to 499 (2007) stems ha-1, with concomitant declines in basal area and above-ground biomass. Despite lower stem densities the species richness remained constant over time. Total liana recruitment rates decreased slightly from 8.6% per year in the first period to 6.6% in the second, but this decrease was not significant. Liana mortality rates decreased significantly from 7.2% to 4.4% per year over the two census intervals. Diameter growth rates and survival increased with liana stem diameter. Surprisingly, liana abundance in Ituri showed recent declines, rather than recent increases, as has been reported for tropical and temperate forests in the Americas. Interestingly, changes in overall liana community structure and composition were mostly driven by one species only: the dramatic collapse of superabundant Manniophyton fulvum between the first and the second census.
In chapter 4 I investigated species-specific dynamics of the 79 most abundant liana species, representing 13,156 of the stems (97% of total) in two 10-ha plots. I evaluated their demographic performance and the relation if the vital rates (growth, mortality, recruitment) to the species abundance and four functional traits (climbing strategy, dispersal syndrome, leaf size and light requirements) to determine across species variations and major strategies characterizing species. Vital rates shared a wide interspecific variation; species-specific recruitment rates varied from 0.0-10.9%, mortality rates from 0.43-7.89% over 13-year, and growth rates from -0.03-3.51 mm y-1. Most species had low to moderate rates. Species that grew fast tended also to recruit and die fast, but recruitment and mortality rates were not directly related, suggesting that species shift in absolute abundance over the 13 year period. However, with the exception of the collapsing Manniophyton fulvum population, species maintained their rank-dominance over time. Species growth declined with abundance, but recruitment and mortality rates were not related to abundance. The demographic performance of liana species varied weakly with their climbing strategy and dispersal mode but was, surprisingly, not related to their lifetime light requirements. A principle components analysis of liana strategies in terms of functional traits and vital rates showed that light demand, and dispersal syndrome were the most determining traits. Based on the PCA three functional guilds were distinguished. I conclude that old-growth forest liana species show a large variation in abundance and vital rates, and that density-dependent mechanisms are insufficient to explain the species abundance patterns over time.
Lianas are thought to globally increase in density, but we have limited knowledge about the taxonomic patterns of change in liana abundance, and the underlying vital rates that explain changes in liana density. In chapter 5 the changes in abundance of 79 relatively abundant liana species are evaluated. The Ituri forest showed a pervasive change in liana population density in the last decade. 37 species changed significantly in their abundance over time: 12 (15% of total) species increased, and 25 (32%) species decreased. 42 (53%) species did not change. Of the 48 genera, 40% decreased and 52% stayed the same. Five of the 12 increasing species belonged to the Celastraceae, which also was the only significantly increasing family. Surprisingly, none of the four functional traits (lifetime light requirements, climbing mechanism, dispersal mechanism, and leaf size) was significantly associated with species change in population density. Many decreasing species, however, are associated with disturbed habitats and are short-lived. Many increasing species are late successional and longer-lived. Increasing species have a slightly higher recruitment, decreasing species a higher mortality. This study suggests that changes in the liana community result from forest recovery from past disturbances. Rising atmospheric CO2 level was not a likely explanation for liana change: more species declined than increased, and increasing species did not have higher growth rates. In the Ituri Forest local stand dynamics override more global drivers of liana change.
Natuurlijke ontwikkelingen in het Amsterdamse Bos : een studie naar de bosontwikkeling in de Natuurboszone en de Parkboszone
Verkaik, E. ; Koop, H.G.J.M. ; Clerkx, A.P.P.M. - \ 2010
Wageningen : Alterra (Alterra-rapport 2102) - 48
bossen - bosbouw in steden - beschermde bossen - bosstructuur - bosbedrijfsvoering - stedelijke gebieden - natuurontwikkeling - verjonging - botanische samenstelling - amsterdam - noord-holland - forests - urban forestry - reserved forests - forest structure - forest management - urban areas - nature development - regeneration - botanical composition - amsterdam - noord-holland
De bosontwikkeling in de Noordboszone en Parkboszone van het Amsterdamse bos zijn onderling vergeleken op openheid van het bos, mate van ontmenging van de boomlaag en hoeveelheid dood hout. Beide beheersvormen verschillen onderling in openheid, mate van verjonging, belevingswaarde en boomsoortensamenstelling nu en in de toekomst. De afwisseling van beide beheersvormen geeft een extra meerwaarde aan het bos en zou naast elkaar gehandhaafd moeten worden. Ontmenging of veresdoorning door nietsdoen-beheer treedt nauwelijks op. De waterkwaliteit moet gewaarborgd blijven door afvoeren van blad- en takafval, waarbij voorkomen moet worden dat de oevers worden opgehoogd.
Space-born spectrodirectional estimation of forest properties
Verrelst, J. - \ 2010
Wageningen University. Promotor(en): Michael Schaepman, co-promotor(en): Jan Clevers; B. Koetz. - [S.l. : S.n. - ISBN 9789085856214 - 152
bossen - bosecologie - achteruitgang, bossen - gezondheidstoestand van het bos - bosinventarisaties - remote sensing - spectrometrie - bosbedrijfsvoering - bosmonitoring - bosstructuur - nabij infrarood spectroscopie - geïntegreerd bosbeheer - forests - forest ecology - forest decline - forest health - forest inventories - remote sensing - spectrometry - forest management - forest monitoring - forest structure - near infrared spectroscopy - integrated forest management
With the upcoming global warming forests are under threat. To forecast climate change impacts and adaptations, there is need for developing improved forest monitoring services, which are able to record, quantify and map bio-indicators of the forests’ health status across the globe. In this context, Earth observation (EO) can provide a substantial amount of up-to-date information about the biochemical and structural conditions of our forests at a local-to-global scale. Among the optical EO instruments in space, one of the most innovative instruments is the experimental Compact High Resolution Imaging Spectrometer (CHRIS) on board the PROBA-1 (Project for On Board Autonomy) satellite. CHRIS is capable of sampling reflected radiation at five viewing angles over the visible and near-infrared (VNIR) region of the solar spectrum with a relatively high spatial resolution (~17 m). The as such acquired spectrodirectional (combined multi-angular and spectroscopy) data may lead to new opportunities for space-based forest monitoring applications, yet the added value of canopy reflectance anisotropy measured over the whole VNIR spectral region is largely unknown. This is why the use of space-borne spectrodirectional data of a forested target has been investigated in this thesis.
Bosontwikkeling na het stopzetten van houtoogst : een analyse van de bosstructuur in bosreservaten
Verkaik, E. - \ 2008
Wageningen : Alterra (Alterra-rapport 1760) - 58
bossen - bosecologie - natuurreservaten - monitoring - plantensuccessie - beschermde bossen - bomen - nederland - bosstructuur - ecologische successie - forests - forest ecology - nature reserves - monitoring - plant succession - reserved forests - trees - netherlands - forest structure - ecological succession
Vanaf 1983 zijn in Nederland zestig bosreservaten aangewezen in het kader van het Programma Bosreservaten. Binnen deze bosreservaten worden in zogenaamde steekproefcirkels gegevens over de bosstructuur verzameld. Het onderzoek dat hier wordt beschreven had als doel om overkoepelende processen en patronen in de bosstructuur van alle bosreservaten te ontdekken. Daarbij wordt in het rapport een vergelijking gemaakt tussen de bosontwikkeling in de bosreservaten en de bosontwikkeling in bos buiten de reservaten. De boompopulatie van het bos in de reservaten blijkt te verschuiven waarbij dikke (oudere) bomen algemener worden en dunne (jonge) bomen in aantallen afnemen. Het bos in de reservaten lijkt verder dichter te worden, waardoor zowel de stamvorm als de kroonvorm van bomen lijken te veranderen.
Quantitative remote sensing for monitoring forest canopy structural variables in the Three Gorges region of China
Zeng, Y. - \ 2008
Wageningen University. Promotor(en): Michael Schaepman, co-promotor(en): Jan Clevers; B. Wu. - S.l. : s.n. - ISBN 9789085049111 - 119
kroondak - bossen - remote sensing - schaalverandering - china - bosstructuur - beeldvormende spectroscopie - canopy - forests - remote sensing - scaling - china - forest structure - imaging spectroscopy
Bridging various scales ranging from local to regional and global, remote sensing has facilitated extraordinary advances in modeling and mapping ecosystems and their functioning. Since forests are one of the most important natural resources on the terrestrial Earth surface, accurate and up-to-date information on forest structure and its changes are essential for many aspects of forest management. In particular the quantitative monitoring of forest structure using remote sensing techniques strongly supports conservation strategies that take into account biodiversity and the impact of the global carbon cycle.
China is a vast country with abundant forest resources. This thesis focuses in particular on the Three Gorges region of China, where currently major changes are taking place in the forest ecosystem. Certainly, the Three Gorges region is widely known due to the construction of the Three Gorges Dam. But the Chinese government also puts great importance on eco-environmental aspects of the Three Gorges Dam project and has therefore implemented a long-term investigation intending to monitor the changing environment. Within the Three Gorges region, the Longmenhe forest nature reserve has been selected as one of the main study sites for this thesis. This forest nature reserve is dominated by subtropical broadleaved and coniferous forests and the pilot study in the reserve enables monitoring forest structural variables as well as detecting their changes in the whole Three Gorges region.
Quantitative retrieval methods for assessing forest canopy structural variables using remote sensing are commonly grouped into statistical and physical approaches. Inverting physical-based canopy reflectance models for estimating forest variables generally can be applied at different sites and with different sensors. Dealing with scales and scaling currently is one of the central issues in quantitative remote sensing. A better understanding of the different spectral, spatial and temporal scales and a further study on scaling the information from local to regional scales are necessary. Therefore, the main objective of this thesis is to develop a methodology for quantitatively monitoring forest canopy structural variables and their change by integrating multiple scale remote sensing techniques.
In Chapter 2, the potential of hyperspectral EO-1 Hyperion data combined with the inverted physical-based Li-Strahler geometric-optical model for retrieving mean crown closure (CC) and mean crown diameter (CD) as forest canopy structural variables in the Longmenhe forest nature reserve is studied. One of the most important inputs for the model inversion is the fractional contribution of sunlit background (Kg), which is obtained by using linear spectral unmixing methods based on image-derived endmembers of the viewed scene components (sunlit and shaded canopy, sunlit and shaded background). Validation results (37 field samples) show confidence (R2CC=0.61, RMSECC=0.046, R2CD=0.39 and RMSECD=0.984) in the approach selected.
Chapter 3 studies the feasibility of up-scaling from very high spatial resolution data (QuickBird) to high spatial resolution hyperspectral data (Hyperion) for extracting the endmembers of sunlit canopy, sunlit background and shadow. It can be concluded that the regional scaling-based endmembers calculated in the overlapping region of QuickBird and Hyperion using the linear unmixing model are the best ones to be used in combination with the Li-Strahler model inversion for mapping CC and CD in the Longmenhe forest nature reserve. Additionally, the estimation of CC is better than that of CD by inverting the Li-Strahler model on a per-pixel basis.
The inverted Li-Strahler model combined with the regional scaling method, used at a local scale in the Longmenhe study area with QuickBird and Hyperion images, can also be applied at the scale of the Three Gorges region by using the combination of Landsat TM and MODIS images as shown in Chapter 4. For the two years 2002 and 2004, this methodology yields similar accuracies in CC estimation based on 25 field validation samples (R22002=0.614, RMSE2002=0.060; and R22004=0.631, RMSE2004=0.052). The produced map with changes in CC from 2002 to 2004 shows a decrease in CC in the eastern counties of the Three Gorges region located close to the Three Gorges Dam and an increase in CC in other counties implying a positive response to certain policies taken safeguarding forest resources.
The inversion of two canopy reflectance models (the Kuusk-Nilson forest reflectance and transmittance (FRT) model and the Li-Strahler geometric-optical model) for estimating forest CC using Hyperion data in the Longmenhe study area is compared in Chapter 5. The “infeasible” areas (i.e. pixels for which the estimated fraction sunlit background falls not in the range between [0, 1]) from the Li-Strahler model inversion are filled by using a spatial interpolation algorithm based on regression kriging. Validation results (40 field samples) show that the estimated CC by the FRT model inversion has a limited range of variation and is less accurate (R2=0.53, RMSE=0.072) than the estimation by inverting the Li-Strahler model combined with the scaling method and interpolation (R2=0.67, RMSE=0.043). Consequently, in Chapter 6, spatially continuous CC maps for the Three Gorges region in both 2002 and 2004 are produced by integrating the results of Chapter 4 and this spatial interpolation technique. The final improved change map of CC is more suitable to predict and analyze the overall situation of the forest structural change in the whole Three Gorges region.
The main contribution of this work is the integration of the inverted Li-Strahler model, a regional scaling-based endmember extraction method and a spatial interpolation technique to achieve quantitative monitoring of forest canopy structural changes. The approach includes the careful assessment of various scaling aspects namely ranging from multi-spectral to hyperspectral, from high spatial resolution to low spatial resolution, from mono-temporal to multi-temporal and from local to regional study areas. Systematic and structural monitoring of forest ecosystem changes will be feasible at unprecedented quality based on the suggested approach.