Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Compositional response of Amazon forests to climate change
Esquivel-Muelbert, Adriane ; Baker, Timothy R. ; Dexter, Kyle G. ; Lewis, Simon L. ; Brienen, Roel J.W. ; Feldpausch, Ted R. ; Lloyd, Jon ; Monteagudo-Mendoza, Abel ; Arroyo, Luzmila ; Álvarez-Dávila, Esteban ; Higuchi, Niro ; Marimon, Beatriz S. ; Marimon-Junior, Ben Hur ; Silveira, Marcos ; Vilanova, Emilio ; Gloor, Emanuel ; Malhi, Yadvinder ; Chave, Jerôme ; Barlow, Jos ; Bonal, Damien ; Davila Cardozo, Nallaret ; Erwin, Terry ; Fauset, Sophie ; Hérault, Bruno ; Laurance, Susan ; Poorter, Lourens ; Qie, Lan ; Stahl, Clement ; Sullivan, Martin J.P. ; Steege, Hans ter; Vos, Vincent Antoine ; Zuidema, Pieter A. ; Almeida, Everton ; Almeida de Oliveira, Edmar ; Andrade, Ana ; Vieira, Simone Aparecida ; Aragão, Luiz ; Araujo-Murakami, Alejandro ; Arets, Eric ; Aymard C, Gerardo A. ; Baraloto, Christopher ; Camargo, Plínio Barbosa ; Barroso, Jorcely G. ; Bongers, Frans ; Boot, Rene ; Camargo, José Luís ; Castro, Wendeson ; Chama Moscoso, Victor ; Comiskey, James ; Peña-Claros, Marielos - \ 2019
Global Change Biology 25 (2019)1. - ISSN 1354-1013 - p. 39 - 56.
bioclimatic niches - climate change - compositional shifts - functional traits - temporal trends - tropical forests

Most of the planet's diversity is concentrated in the tropics, which includes many regions undergoing rapid climate change. Yet, while climate-induced biodiversity changes are widely documented elsewhere, few studies have addressed this issue for lowland tropical ecosystems. Here we investigate whether the floristic and functional composition of intact lowland Amazonian forests have been changing by evaluating records from 106 long-term inventory plots spanning 30 years. We analyse three traits that have been hypothesized to respond to different environmental drivers (increase in moisture stress and atmospheric CO2 concentrations): maximum tree size, biogeographic water-deficit affiliation and wood density. Tree communities have become increasingly dominated by large-statured taxa, but to date there has been no detectable change in mean wood density or water deficit affiliation at the community level, despite most forest plots having experienced an intensification of the dry season. However, among newly recruited trees, dry-affiliated genera have become more abundant, while the mortality of wet-affiliated genera has increased in those plots where the dry season has intensified most. Thus, a slow shift to a more dry-affiliated Amazonia is underway, with changes in compositional dynamics (recruits and mortality) consistent with climate-change drivers, but yet to significantly impact whole-community composition. The Amazon observational record suggests that the increase in atmospheric CO2 is driving a shift within tree communities to large-statured species and that climate changes to date will impact forest composition, but long generation times of tropical trees mean that biodiversity change is lagging behind climate change.

Embolism resistance drives the distribution of Amazonian rainforest tree species along hydro-topographic gradients
Oliveira, Rafael S. ; Costa, Flavia R.C. ; Baalen, Emma van; Jonge, Arjen de; Bittencourt, Paulo R. ; Almanza, Yanina ; V. Barros, Fernanda de; Cordoba, Edher C. ; Fagundes, Marina V. ; Garcia, Sabrina ; Guimaraes, Zilza T.T.M. ; Hertel, Mariana ; Schietti, Juliana ; Rodrigues-Souza, Jefferson ; Poorter, Lourens - \ 2019
New Phytologist 221 (2019)3. - ISSN 0028-646X - p. 1457 - 1465.
drought vulnerability - forest resilience - functional ecology - hydrological niches - P - phosphorus - tropical forests - water table

Species distribution is strongly driven by local and global gradients in water availability but the underlying mechanisms are not clear. Vulnerability to xylem embolism (P50) is a key trait that indicates how species cope with drought and might explain plant distribution patterns across environmental gradients. Here we address its role on species sorting along a hydro-topographical gradient in a central Amazonian rainforest and examine its variance at the community scale. We measured P50 for 28 tree species, soil properties and estimated the hydrological niche of each species using an indicator of distance to the water table (HAND). We found a large hydraulic diversity, covering as much as 44% of the global angiosperm variation in P50. We show that P50: contributes to species segregation across a hydro-topographic gradient in the Amazon, and thus to species coexistence; is the result of repeated evolutionary adaptation within closely related taxa; is associated with species tolerance to P-poor soils, suggesting the evolution of a stress-tolerance syndrome to nutrients and drought; and is higher for trees in the valleys than uplands. The large observed hydraulic diversity and its association with topography has important implications for modelling and predicting forest and species resilience to climate change.

“Embodied Deforestation” as a New EU Policy Debate to Tackle Tropical Forest Loss: Assessing Implications for REDD+ Performance
Weatherley-Singh, Janice ; Gupta, A. - \ 2018
Forests 9 (2018)12. - ISSN 1999-4907 - 23 p.
REDD+ - European Union - forest policy - deforestation drivers - tropical forests
The need to tackle international drivers of deforestation has long been acknowledged; but remains little addressed via policy measures. In the European Union (EU), a new policy debate is emerging around the concept of “embodied deforestation”, which targets EU Agricultural commodity imports as drivers of deforestation. The notion views deforestation as an externality generated by EU imports associated with tropical deforestation. Our article examines whether this
concept represents a shift in tackling international-level drivers of tropical deforestation within EU policy. We also examine, from a networked governance perspective, whether this new debate fuels further fragmentation or rather a move towards a more integrated approach to combating tropical forest loss within EU policy, and what the implications are for other initiatives, such as the climate change related “reducing emissions from deforestation and forest degradation” (REDD+). Our analysis draws on an extensive analysis of EU policy documents and semi-structured interviews with stakeholders and EU decision-makers. We find that, despite growing debate around the concept of embodied deforestation, policy measures necessary to reduce the impact of EU consumption of agricultural commodities associated with tropical deforestation have not yet been developed. We conclude that “embodied deforestation” remains more an idea than reality within EU policy to date, with the burden of responsibility for addressing international deforestation drivers still largely remaining on developing countries. There is still potential, however, for this
debate to lead to a more integrated approach to tackling tropical deforestation within EU policy, if it comes to be seen, together with REDD+, as one of a number of linked approaches to EU efforts to combat deforestation.
Tropical land carbon cycle responses to 2015/16 El Niño as recorded by atmospheric greenhouse gas and remote sensing data
Gloor, Emanuel ; Wilson, Chris ; Chipperfield, Martyn P. ; Chevallier, Frederic ; Buermann, Wolfgang ; Boesch, Hartmut ; Parker, Robert ; Somkuti, Peter ; Gatti, Luciana V. ; Correia, Caio ; Domingues, Lucas G. ; Peters, Wouter ; Miller, John ; Deeter, Merritt N. ; Sullivan, Martin J.P. - \ 2018
Philosophical Transactions of the Royal Society B. Biological sciences 373 (2018)1760. - ISSN 0962-8436 - 12 p.
carbon cycle - fire - global warming - tropical forests

The outstanding tropical land climate characteristic over the past decades is rapid warming, with no significant large-scale precipitation trends. This warming is expected to continue but the effects on tropical vegetation are unknown. El Niño-related heat peaks may provide a test bed for a future hotter world. Here we analyse tropical land carbon cycle responses to the 2015/16 El Niño heat and drought anomalies using an atmospheric transport inversion. Based on the global atmospheric CO2 and fossil fuel emission records, we find no obvious signs of anomalously large carbon release compared with earlier El Niño events, suggesting resilience of tropical vegetation. We find roughly equal net carbon release anomalies from Amazonia and tropical Africa, approximately 0.5 PgC each, and smaller carbon release anomalies from tropical East Asia and southern Africa. Atmospheric CO anomalies reveal substantial fire carbon release from tropical East Asia peaking in October 2015 while fires contribute only a minor amount to the Amazonian carbon flux anomaly. Anomalously large Amazonian carbon flux release is consistent with downregulation of primary productivity during peak negative near-surface water anomaly (October 2015 to March 2016) as diagnosed by solar-induced fluorescence. Finally, we find an unexpected anomalous positive flux to the atmosphere from tropical Africa early in 2016, coincident with substantial CO release.This article is part of a discussion meeting issue 'The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications'.

Recent progress in understanding climate thresholds : Ice sheets, the Atlantic meridional overturning circulation, tropical forests and responses to ocean acidification
Good, Peter ; Bamber, Jonathan ; Halladay, Kate ; Harper, Anna B. ; Jackson, Laura C. ; Kay, Gillian ; Kruijt, Bart ; Lowe, Jason A. ; Phillips, Oliver L. ; Ridley, Jeff ; Srokosz, Meric ; Turley, Carol ; Williamson, Phillip - \ 2018
Progress in Physical Geography 42 (2018)1. - ISSN 0309-1333 - p. 24 - 60.
Atlantic meridional overturning circulation - climate change - ice sheets - ocean acidification - thresholds - tropical forests
This article reviews recent scientific progress, relating to four major systems that could exhibit threshold behaviour: ice sheets, the Atlantic meridional overturning circulation (AMOC), tropical forests and ecosystem responses to ocean acidification. The focus is on advances since the Intergovernmental Panel on Climate Change Fifth Assessment Report (IPCC AR5). The most significant developments in each component are identified by synthesizing input from multiple experts from each field. For ice sheets, some degree of irreversible loss (timescales of millennia) of part of the West Antarctic Ice Sheet (WAIS) may have already begun, but the rate and eventual magnitude of this irreversible loss is uncertain. The observed AMOC overturning has decreased from 2004–2014, but it is unclear at this stage whether this is forced or is internal variability. New evidence from experimental and natural droughts has given greater confidence that tropical forests are adversely affected by drought. The ecological and socio-economic impacts of ocean acidification are expected to greatly increase over the range from today’s annual value of around 400, up to 650 ppm CO2 in the atmosphere (reached around 2070 under RCP8.5), with the rapid development of aragonite undersaturation at high latitudes affecting calcifying organisms. Tropical coral reefs are vulnerable to the interaction of ocean acidification and temperature rise, and the rapidity of those changes, with severe losses and risks to survival at 2 °C warming above pre-industrial levels. Across the four systems studied, however, quantitative evidence for a difference in risk between 1.5 and 2 °C warming above pre-industrial levels is limited.
Demographic drivers of functional composition dynamics
Muscarella, Robert ; Lohbeck, Madelon ; Martínez-Ramos, Miguel ; Poorter, Lourens ; Rodríguez-Velázquez, Jorge Enrique ; Breugel, Michiel van; Bongers, Frans - \ 2017
Ecology 98 (2017)11. - ISSN 0012-9658 - p. 2743 - 2750.
community-weighted mean traits - leaf phosphorus - seed size - specific leaf area - succession - tropical forests - wood density

Mechanisms of community assembly and ecosystem function are often analyzed using community-weighted mean trait values (CWMs). We present a novel conceptual framework to quantify the contribution of demographic processes (i.e., growth, recruitment, and mortality) to temporal changes in CWMs. We used this framework to analyze mechanisms of secondary succession in wet tropical forests in Mexico. Seed size increased over time, reflecting a trade-off between colonization by small seeds early in succession, to establishment by large seeds later in succession. Specific leaf area (SLA) and leaf phosphorus content decreased over time, reflecting a trade-off between fast growth early in succession vs. high survival late in succession. On average, CWM shifts were driven mainly (70%) by growth of surviving trees that comprise the bulk of standing biomass, then mortality (25%), and weakly by recruitment (5%). Trait shifts of growing and recruiting trees mirrored the CWM trait shifts, and traits of dying trees did not change during succession, indicating that these traits are important for recruitment and growth, but not for mortality, during the first 30 yr of succession. Identifying the demographic drivers of functional composition change links population dynamics to community change, and enhances insights into mechanisms of succession.

Space-time monitoring of tropical forest changes using observations from multiple satellites
Hamunyela, Eliakim - \ 2017
Wageningen University. Promotor(en): Martin Herold, co-promotor(en): Jan Verbesselt. - Wageningen : Wageningen University - ISBN 9789463436403 - 188
tropical forests - monitoring - satellites - deforestation - ecological disturbance - tropische bossen - satellieten - ontbossing - ecologische verstoring

Forests provide essential goods and services to humanity, but human-induced forest disturbances have been on ongoing at alarming rates, undermining the capacity for forests to continue providing essential goods and services. In recent years, the understanding of the short-term and long-term impacts of deforesting and degrading forest ecosystems has improved, and global efforts to reduce forest loss are ongoing. However, in many parts of the globe, significant forest areas continue to be lost. To fully protect forest ecosystems efficiently, timely, reliable and location-specific information on new forest disturbances is needed. Frequent and large-area forest mapping and monitoring using satellite observations can provide timely and cost-effective information about new forest disturbances. However, there are still key weaknesses associated with existing forest monitoring systems. For example, the capacity for forest monitoring systems to detect new disturbances accurately and timely is often limited by persistent cloud cover and strong seasonal dynamics. Persistent cloud can be addressed by using observations from multiple satellite sensors, but satellite sensors often have inter-sensor differences which make integration of observations from multiple sensors challenging. Seasonality can be accounted for using a seasonal model, but image time series are often acquired at irregular intervals, making it difficult to properly account for seasonality. Furthermore, with existing forest monitoring systems, detecting subtle, low-magnitude disturbances remains challenging, and timely detection of forest disturbances is often accompanied by many false detections. The overall objective of this thesis is to improve forest change monitoring by addressing the key challenges which hinders accurate and timely detection of forest disturbances from satellite data. In the next paragraphs, I summarise how this thesis tackled some of the key challenges which hamper effective monitoring of forest disturbances using satellite observations.

Chapter 2 addresses the challenge of seasonality by developing a spatial normalisation approach that allows us to account for seasonality in irregular image time series when monitoring forest disturbances. In this chapter, I showed that reducing seasonality in image time series using spatial normalisation leads to timely detection of forest disturbances when compared to a seasonal model approach. With spatial normalisation, near real-time forest monitoring in dry forests, which has been challenging for many years, is now possible. Applying spatial normalisation in areas where evergreen and deciduous forests co-exist is however challenging. Therefore, further research is needed to improve the spatial normalisation approach to ensure that it is applicable to areas with a combination of different forest types. In particular, a spatial normalisation approach which is forest type-specifics is desirable. In this chapter, forest disturbances were detected by analysing single pixel-time series. Spatial information was only used to reduce seasonality.

Taking in account the fact that forest disturbances are spatio-temporal events, I investigated whether there is an added-value of combining both spatial and temporal information when monitoring forest disturbances from satellite image time series. To do this, I first developed a space-time change detection method that detects forest disturbances as extreme events in satellite data cubes (Chapter 3). I showed that, by combining spatial and temporal information, forest disturbances can still be detected reliably even with limited historical observations. Therefore, unlike approaches which detect forest disturbances by analysing single pixel- time series, the space-time approach does not require huge amount of historical images to be pre-processed when monitoring forest disturbances. I then evaluated the added-value of using space-time features when confirming forest disturbances (Chapter 4). I showed that using a set of space-time features to confirm forest disturbances enhance forest monitoring significantly by reducing false detections without compromising temporal accuracy. With space-time features, the discrimination of forest disturbances from false detections is no longer based on temporal information only, hence providing opportunity to also detect low-magnitude disturbances with high confidence. Based on the analysis for conditional variable importance, I showed that features which are computed using both spatial and temporal information were the most important predictors of forest disturbances, thus enforcing the view that forest disturbances should be treated as spatio-temporal in order to improve forest change monitoring.

In Chapter 2 – 4, forest disturbances where detected from medium resolution Landsat time series. Yet, recent studies showed that small-scale forest disturbances are often omitted when using Landsat time series. In Chapter 5, I investigated whether detection of small-scale forest disturbances can be improved by using the 10m resolution time series from recently launched Sentinel-2 sensor. I also investigated whether the spatial normalisation approach developed in Chapter 2 can be used to reduce inter-sensor differences in multi-sensor optical time series. I showed that the 10m resolution Sentinel-2 time series improves the detection of small-scale forest disturbances when compared to 30m resolution. However, the 10m resolution does not supersede the importance of frequent satellite observations when monitoring forest disturbances. I also showed that spatial normalisation approach developed in Chapter 2 can reduce inter-sensor differences in multi-sensor optical time series significantly to generate temporally consistent time series suitable for forest change detection. Spatial normalisation does not completely remove inter-sensor differences, but the differences are significantly reduced.

Monitoring of forest disturbances is increasingly done using a combination of Synthetic Aperture Radar (SAR) and optical time series. Therefore, Chapter 6 investigated whether the spatial normalisation approach developed in Chapter 2 can also reduce seasonal variations in SAR time series to facilitate the integration of SAR-optical time series for forest monitoring in dry tropical forests. This Chapter demonstrated that seasonal variations in SAR time series can also be reduced through spatial normalisation. As a result, observations from SAR and optical time series were combined to improve near real-time forest change detection in dry tropical forest. In Chapter 7, it is demonstrated that spatial normalisation has potential to also reduce inter-sensor differences in SAR-optical time series, resulting into temporally consistent SAR-optical time series.

In conclusion, this thesis developed a space-time forest monitoring framework that addresses some key challenges affecting satellite-based forest monitoring. In particular, new methods that allow for timely and accurate detection of forest disturbances using observations from multiple satellites were developed. Overall, the methods developed in this research contribute to our capacity to accurately and timely detect forest disturbances in both dry and humid forests.

Super-performance in a palm species
Jansen, Merel - \ 2016
Wageningen University. Promotor(en): Niels Anten; Pieter Zuidema, co-promotor(en): Frans Bongers; M. Martínez-Ramos. - Wageningen : Wageningen University - ISBN 9789462579996 - 193
chamaedorea elegans - understorey - tropical forests - spatial variation - leaves - growth - population ecology - defoliation - genetic variation - onderlaag - tropische bossen - ruimtelijke variatie - bladeren - groei - populatie-ecologie - ontbladering - genetische variatie

The world is changing rapidly due to anthropogenic disturbance. Effects include: global warming, massive pollution, a changed global nitrogen cycle, high rates of land-use change, and exotic species spread. This has a tremendous impact on both natural and agricultural systems. To understand these impacts, good understanding of ecological systems and underlying drivers is necessary. Ecological systems can be studied at different levels of aggregation. Different levels of aggregation influence each other and are also influenced by external drivers like the environment. The population level is of particular interest, because many important ecological processes occur at the population level, like evolution, extinction, and invasion. Ecologists are increasingly recognizing that population processes are strongly influenced by one level of aggregation lower, the individual level. Individual heterogeneity (i.e. differences between individuals in performance), determines many population processes including population growth rate. However, the exact relations between individual heterogeneity, the external drivers of it, and the population level are not always well understood. Furthermore, methods to analyze these relations are not always available.

Individual heterogeneity occurs at different temporal scales, ranging from short- to long-term performance differences between individuals, where short- and long-term refer to the expected lifespan of the species in question. Short-term differences between individuals are relatively easily identifiable and are common in almost all species. But long-term differences are much harder to determine especially for long-lived organisms. Long-term differences between individuals in reproduction have been identified for several animal species, and in growth for several tree species, but less is known about the existence of such differences in other life forms (e.g. palms, lianas or clonal plants). Quantifying the extent to which individuals differ is essential for understanding the influence of individual heterogeneity on population processes. Super-performing individuals (i.e. individuals that persistently grow faster and reproduce more than others), probably contribute more to the growth of the population and therefore to future generations. Future populations will, therefore, have the genetic characteristics of the super-performers. Which characteristics this will be, depends on the genetic and environmental drivers of super-performance. Full understanding of the influence of individual heterogeneity on population processes, therefore, requires knowledge of the underlying causes of individual heterogeneity.

For many species, it is known that spatial variation in environmental conditions can cause short-term performance differences between individuals, but it is often not clear if the same environmental factors that cause short-term performance differences are also the environmental factors that cause long-term performance differences. Furthermore, genetic variation is known to cause performance differences, but to what extent is not well studied in natural long-lived plant populations. Within-population genetic variation can be maintained in habitats that are characterized by strong temporal or spatial heterogeneity in environmental conditions if the performance of a genotype relative to others depends on the environment it experiences.

Super-performing individuals possibly play an important role in the resistance and resilience of populations to disturbance (i.e. maintaining and recovering population growth rate under stress), because super-performers potentially contribute more to the recovery of the population. However, this depends on the relative tolerance to disturbance of super-performers compared to under-performers. A positive relation between performance and tolerance would make super-performers more important, while a negative relation would make them less important. Many types of disturbances entail leaf loss and tolerance to leaf loss is associated with performance being larger than what one would assume based on the amount of leaf area loss. Tolerance can be achieved by compensating for leaf loss in terms of growth rate, which entails either allocating more new assimilates to leaves, allocating new assimilates more efficiently to leaf area (i.e. by increasing specific leaf area), or growing faster with existing leaf area (i.e. by increasing net assimilation rate). Genetic variation in tolerance and compensatory responses would allow populations to adapt to changes in disturbance events that entail leaf loss.

Individual heterogeneity could also have implications for management. Plant and animal populations are managed at many different levels ranging from harvest from natural populations to modern agricultural practices. When harvesting from natural populations, it might be beneficial to spare the individuals that are most important for future production. Individuals could be spared, either because they contribute most to population growth, because they are tolerant to harvesting (which is relevant when only part of a plant is harvested), or when they start producing less or lower quality product. The productivity of natural populations could also be increased by actively promoting those environmental conditions and genotypes that allow for high productivity, which is the basis of agriculture and common practice in forest management. To determine how this can best be done, knowledge of the causes of individual heterogeneity is necessary.

The general aim of this thesis is to identify and quantify the mechanisms that determine individual heterogeneity and to determine how this heterogeneity, in turn, affects population level processes. This aim was divided into four main questions that I addressed: (1) To what extent do individuals differ in performance? (2) What causes individual heterogeneity in performance? (3) What are the demographic consequences of individual heterogeneity? (4) Can individual differences be used to improve the management of populations? To answer these questions, we used the tropical forest understorey palm Chamaedorea elegans as a study system, of which the leaves are an important non-timber forest product that is being used in the floral industry worldwide. We collected demographic data, measured spatial variation in environmental conditions, and applied a defoliation treatment to simulate leaf harvesting, in a natural population in Chiapas, Mexico. Furthermore, we grew seedlings from different mothers from our study population in the greenhouses of Wageningen University, where we also applied a defoliation treatment.

In Chapter 2 we quantified the extent to which individuals differ in long-term growth rate, and analyzed the importance of fast growers for population growth. We reconstructed growth histories from internodes and showed that growth differences between individuals are very large and persistent in our study population. This led to large variation in life growth trajectories, with individuals of the same age varying strongly in size. This shows that not only in canopy trees but also in species in the light limited understorey growth differences can be very large. Past growth rate was found to be a very good predictor of current performance (i.e. growth and reproduction). Using an Integral Projection Model (i.e. a type of demographic model) that was based on size and past growth rate, we showed that fast-growing individuals are much more important for population growth than others: the 50% fastest growing individuals contributed almost two times as much to population growth as the 50% slowest growing individuals.

In Chapter 3 we analyzed the extent to which observed long-term growth differences can be caused by environmental heterogeneity. Short-term variation in performance was mainly driven by light availability, while soil variables and leaf damage had smaller effects, and spatial heterogeneity in light availability and soil pH were autocorrelated over time. Using individual-based simulation models, we analyzed the extent to which spatial environmental heterogeneity could explain observed long-term variation in growth, and showed that this could largely be explained if the temporal persistence of light availability and soil pH was taken into account. We also estimated long-term inter-individual variation in reproduction to be very large. We further analyzed the importance of temporal persistence in environmental variation for long-term performance differences, by analyzing the whole range of values of environmental persistence, and the strength of the effect of the environmental heterogeneity on short-term performance. We showed that long-term performance differences become large when either the strength of the effect of the environmental factor on short-term performance is large, or when the spatial variation in the environmental factor is persistent over time. This shows that an environmental factor that in a short-term study might have been dismissed as unimportant for long-term performance variation, might, in reality, contribute strongly.

In Chapter 4 we tested for genetic variation in growth potential, tolerance to leaf loss, compensatory growth responses, and if growth potential and tolerance were genetically correlated in our study population. We quantified compensatory responses with an iterative growth model that takes into account the timing of leaf loss. Genetic variation in growth potential was large, and plants compensated strongly for leaf loss, but genetic variation in tolerance and compensatory growth responses was very limited. Growth performances in defoliated and undefoliated conditions were positively genetically correlated (i.e. the same genotypes perform relatively well compared to others, both with and without the stress of leaf loss). The high genetic variation in growth potential and the positive correlation between treatments suggests that the existence of super-performing individuals in our study population likely has (at least in part) a genetic basis. These super-performing individuals, that grow fast even under the stress of leaf loss, possibly contribute disproportionately to population resistance and resilience to disturbance. The low genetic variation in tolerance and compensatory responses, however, suggests that populations might have limited ability to adapt to changes in disturbance regimes that entail increases in leaf loss. Furthermore, the high genetic variation in growth potential could potentially be used in management practices like enrichment planting.

In Chapter 5 we explore the potential of using individual heterogeneity to design smarter harvest schemes, by sparing individuals that contribute most to future productivity. We tested if fast and slow growers, and small and large individuals, responded differently to leaf loss in terms of vital rates, but found only very limited evidence for this. Using Integral Projection Models that were based on stem length and past growth rate, we simulated leaf harvest over a period of 20 years, in several scenarios of sparing individuals, which we compared to “Business as usual” (i.e. no individuals being spared, BAU). Sparing individuals that are most important for population growth, was beneficial for population size (and could, therefore, reduce extinction risk), increased annual leaf harvest at the end of the simulation period, but cumulated leaf harvest over 20 years was much lower compared to BAU. Sparing individuals that produced leaves of non-commercial size (i.e. <25cm), therefore allowing them to recover, also resulted in a lower total leaf harvest over 20 years. However, a much higher harvest (a three-fold increase) was found when only leaves of commercial size were considered. These results show that it is possible to increase yield quality and sustainability (in terms of population size) of harvesting practices, by making use of individual heterogeneity. The analytical and modeling methods that we present are applicable to any natural system from which either whole individuals, or parts of individuals, are harvested, and provide an extra tool that could be considered by managers and harvest practitioners to optimize harvest practices.

In conclusion, in this thesis, I showed that in a long-lived understorey palm growth differences are very large and persistent (Chapter 2) and that it is likely that long-term differences in reproduction are also very large (Chapter 3). I also showed that spatial heterogeneity in environmental conditions can to a large extent explain these differences and that when evaluating the environmental drivers of individual heterogeneity, it is important to take the persistence of spatial variation into account (Chapter 3). Individual heterogeneity also is partly genetically determined. I showed that genetic variation in growth potential to be large (Chapter 4), and that fast growers keep on growing fast under the stress of leaf loss (Chapters 4,5). Therefore it is likely that genetic variation contributes to long-term differences between individuals. Genetic variation for tolerance and compensatory responses was estimated to be low (Chapter 4), suggesting that the adaptive potential of our study population to changes in disturbance events that entail leaf loss might be low. I also showed that super-performing individuals are much more important for the growth of the population (Chapter 2) and that individuals that are important for future production could be used to improve the management of natural populations (Chapter 5).

This study provides improved insight into the extent of individual heterogeneity in a long-lived plant species and its environmental and genetic drivers, and clearly shows the importance of individual heterogeneity and its drivers for population processes and management practices. It also presents methods on how persistent performance differences between individuals can be incorporated into demographic tools, how these can be used to analyze individual contributions to population dynamics, to extrapolate short-term to long–term environmental effects, and to analyze smart harvesting scenarios that take differences between individuals into account. These results indicate that individual heterogeneity, underlying environmental and genetic drivers, and population processes are all related. Therefore, when evaluating the effect of environmental change on population processes, and in the design of management schemes, it is important to keep these relations in mind. The methodological tools that we presented provide a means of doing this.

RAINBIO : A mega-database of tropical African vascular plants distributions
Dauby, Gilles ; Zaiss, Rainer ; Blach-Overgaard, Anne ; Catarino, Luís ; Damen, T.H.J. ; Deblauwe, Vincent ; Dessein, Steven ; Dransfield, John ; Droissart, Vincent ; Duarte, Maria Cristina ; Engledow, Henry ; Fadeur, Geoffrey ; Figueira, Rui ; Gereau, Roy E. ; Hardy, Olivier J. ; Harris, David J. ; Heij, Janneke De; Janssens, Steven ; Klomberg, Yannick ; Ley, Alexandra C. ; Mackinder, Barbara A. ; Meerts, Pierre ; Poel, Jeike van de; Sonké, Bonaventure ; Sosef, M.S.M. ; Stévart, Tariq ; Stoffelen, Piet ; Svenning, Jens Christian ; Sepulchre, Pierre ; Burgt, Xander Van Der; Wieringa, J.J. ; Couvreur, T.L.P. - \ 2016
Herbarium specimens - tropical forests - georeferencing - taxonomic backbone - habit - digitization - native species - cultivated species - biodiversity assessment
The tropical vegetation of Africa is characterized by high levels of species diversity but is undergoing important shifts in response to ongoing climate change and increasing anthropogenic pressures. Although our knowledge of plant species distribution patterns in the African tropics has been improving over the years, it remains limited. Here we present RAINBIO, a unique comprehensive mega-database of georeferenced records for vascular plants in continental tropical Africa. The geographic focus of the database is the region south of the Sahel and north of Southern Africa, and the majority of data originate from tropical forest regions. RAINBIO is a compilation of 13 datasets either publicly available or personal ones. Numerous in depth data quality checks, automatic and manual via several African flora experts, were undertaken for georeferencing, standardization of taxonomic names and identification and merging of duplicated records. The resulting RAINBIO data allows exploration and extraction of distribution data for 25,356 native tropical African vascular plant species, which represents ca. 89% of all known plant species in the area of interest. Habit information is also provided for 91% of these species.
Examining variation in the leaf mass per area of dominant species across two contrasting tropical gradients in light of community assembly
Neyret, Margot ; Bentley, Lisa Patrick ; Oliveras Menor, Imma ; Marimon, Beatriz S. ; Marimon-Junior, Ben Hur ; Almeida de Oliveira, Edmar ; Barbosa Passos, Fábio ; Castro Ccoscco, Rosa ; Santos, Josias dos; Matias Reis, Simone ; Morandi, Paulo S. ; Rayme Paucar, Gloria ; Robles Cáceres, Arturo ; Valdez Tejeira, Yolvi ; Yllanes Choque, Yovana ; Salinas, Norma ; Shenkin, Alexander ; Asner, Gregory P. ; Díaz, Sandra ; Enquist, Brian J. ; Malhi, Yadvinder - \ 2016
Ecology and Evolution 6 (2016)16. - ISSN 2045-7758 - p. 5674 - 5689.
Community assembly - environmental filtering - interspecific variation - intraspecific variation - leaf mass per area - limiting similarity - T-statistics - tropical forests

Understanding variation in key functional traits across gradients in high diversity systems and the ecology of community changes along gradients in these systems is crucial in light of conservation and climate change. We examined inter- and intraspecific variation in leaf mass per area (LMA) of sun and shade leaves along a 3330-m elevation gradient in Peru, and in sun leaves across a forest–savanna vegetation gradient in Brazil. We also compared LMA variance ratios (T-statistics metrics) to null models to explore internal (i.e., abiotic) and environmental filtering on community structure along the gradients. Community-weighted LMA increased with decreasing forest cover in Brazil, likely due to increased light availability and water stress, and increased with elevation in Peru, consistent with the leaf economic spectrum strategy expected in colder, less productive environments. A very high species turnover was observed along both environmental gradients, and consequently, the first source of variation in LMA was species turnover. Variation in LMA at the genus or family levels was greater in Peru than in Brazil. Using dominant trees to examine possible filters on community assembly, we found that in Brazil, internal filtering was strongest in the forest, while environmental filtering was observed in the dry savanna. In Peru, internal filtering was observed along 80% of the gradient, perhaps due to variation in taxa or interspecific competition. Environmental filtering was observed at cloud zone edges and in lowlands, possibly due to water and nutrient availability, respectively. These results related to variation in LMA indicate that biodiversity in species rich tropical assemblages may be structured by differential niche-based processes. In the future, specific mechanisms generating these patterns of variation in leaf functional traits across tropical environmental gradients should be explored.

Repeated fires trap Amazonian blackwater floodplains in an open vegetation state
Flores, Bernardo M. ; Fagoaga, Raquel ; Nelson, Bruce W. ; Holmgren, Milena - \ 2016
Journal of Applied Ecology 53 (2016)5. - ISSN 0021-8901 - p. 1597 - 1603.
drought - ecological transition - ecosystem shift - El Niño Southern Oscillation (ENSO) - forest succession - igapó - recovery rates - resilience - tropical forests - wetlands

Climate change may increase the occurrence of droughts and fires in the Amazon. Most of our understanding on how fire affects tropical ecosystems is based on studies of non-flooded forest–savanna ecotones. Nonetheless, tropical floodplain forests in the Amazon can burn severely during extreme droughts. The mechanisms slowing down forest regeneration in these ecosystems remain poorly understood and have never been assessed in the field. We studied the recovery of Amazonian blackwater floodplain forests after one and two fire events. We used Landsat images to map fire history and conducted field surveys to measure forest structure, tree species richness, tree seed bank and post-fire invasion of herbaceous plants. Sites burnt once had on average 0% trees, 6% tree seed abundance, 23% tree seed species richness and 8% root mat thickness compared to unburnt forests. In contrast, herbaceous cover increased from 0 to 72%. Nonetheless, forest structure and diversity recovered slowly towards pre-burn levels, except for tree seed banks that remained depleted even 15 years after fire. Sites burnt twice had on average 0% trees, 1% tree seed abundance, 3% tree seed species richness and 1% root mat thickness compared to unburnt forests. Herbaceous cover increased to 100%. Mean recovery of tree basal area was 50% slower and of root mat thickness 93% slower compared to recovery in sites burnt once. Tree seed banks did not recover at all, and herbaceous cover persisted close to 100% for more than 20 years after the second fire. Synthesis and applications. Our results indicate that after a second fire event, Amazonian blackwater floodplain forests lose their recovery capacity, and persist in a non-forested state dominated by herbaceous vegetation. Such fragility implies that preventing human ignited fires during drought episodes is a particularly important conservation strategy for these ecosystems.

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 p.
tropical forests - remote sensing - mapping - biodiversity - forest structure - monitoring - land use - landsat - tropische bossen - cartografie - biodiversiteit - bosstructuur - landgebruik

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.

Biodiversity and the functioning of tropical forests
Sande, M.T. van der - \ 2016
Wageningen University. Promotor(en): Lourens Poorter, co-promotor(en): Marielos Pena Claros; Eric Arets. - Wageningen : Wageningen University - ISBN 9789462578029 - 282 p.
tropical forests - biodiversity - forest ecology - forest management - climatic change - tropische bossen - biodiversiteit - bosecologie - bosbedrijfsvoering - klimaatverandering

Tropical forests are the most diverse terrestrial ecosystems. Moreover, their capacity for removal of carbon from the atmosphere makes them important for climate change mitigation. Theories predict that species use resources in a different way, and therefore high species diversity would result in more efficient resource use and higher total carbon removal. These theories, however, have yet not been clearly demonstrated for tropical forests. In this thesis, I evaluated how biodiversity of plants and their traits influenced carbon removal. I used data collected in different tropical forest types and at different spatial and temporal scales. I found that biodiversity was important for carbon removal especially at large spatial scales (e.g. the Amazon) where biodiversity varies strongly, and at long temporal scales (e.g. >200 years) where high biodiversity functions as a buffer for changing environmental conditions. In this way biodiversity contributes to long-term stable forests and a safe climate.

Remote sensing of land use and carbon losses following tropical deforestation
Sy, V. de - \ 2016
Wageningen University. Promotor(en): Martin Herold, co-promotor(en): Jan Clevers; L. Verchot. - Wageningen : Wageningen University - ISBN 9789462578036 - 142 p.
remote sensing - tropical forests - land use - carbon - losses - environmental degradation - forest monitoring - tropische bossen - landgebruik - koolstof - verliezen - milieuafbraak - bosmonitoring

The new Paris Agreement, approved by 195 countries under the auspice of the United Nations Framework Convention on Climate Change (UNFCCC), calls for limiting global warming to “well below" 2°Celsius. An important part of the climate agreement relates to reducing emissions from deforestation and forest degradation, and enhancing carbon stocks (REDD+) in non-Annex I (mostly developing) countries. Over the last decades the growing demand for food, fibre and fuel has accelerated the pace of forest loss. In consequence, tropical deforestation and forest degradation are responsible for a large portion of global carbon emissions to the atmosphere, and destroy an important global carbon sink that is critical in future climate change mitigation.

Within the REDD+ framework, participating countries are given incentives to develop national strategies and implementation plans that reduce emissions and enhance sinks from forests and to invest in low carbon development pathways. For REDD+ activities to be effective, accurate and robust methodologies to estimate emissions from deforestation and forest degradation are crucial. Remote sensing is an essential REDD+ observation tool, and in combination with ground measurements it provides an objective, practical and cost-effective solution for developing and maintaining REDD+ monitoring systems. The remote sensing monitoring objective for REDD+ is not only to map deforestation but also to support policy formulation and implementation. Identifying and addressing drivers and activities causing forest carbon change is crucial in this respect. Despite the importance of identifying and addressing drivers, quantitative information on these drivers, and the related carbon emissions, is scarce at the national level.

The main objective of this thesis is to explore the role of remote sensing for monitoring tropical forests for REDD+ in general, and for assessing land use and related carbon emissions linked to drivers of tropical deforestation in particular. To achieve this, this thesis investigates the following research questions:

What is the current role and potential of remote sensing technologies and methodologies for monitoring tropical forests for REDD+ and for assessing drivers of deforestation?

What is the current state of knowledge on drivers of deforestation and degradation in REDD+ countries?

What are land use patterns and related carbon emissions following deforestation, capitalising on available land use and biomass remote sensing data?

The research conducted in this PhD thesis contributes to the understanding of the role of remote sensing in forest monitoring for REDD+ and in the assessment of drivers of deforestation. In addition, this thesis contributes to the improvement of spatial and temporal quantification of land use and related carbon emissions linked to drivers of tropical deforestation. The results and insights described herein are valuable for ongoing REDD+ forest monitoring efforts and capacity development as REDD+ moves closer to becoming an operational mitigation mechanism.

Conservation genetics of the frankincense tree
Bekele, A.A. - \ 2016
Wageningen University. Promotor(en): Frans Bongers, co-promotor(en): Rene Smulders; K. Tesfaye Geletu. - Wageningen : Wageningen University - ISBN 9789462576865 - 158 p.
boswellia - genomes - dna sequencing - tropical forests - genetic diversity - genetic variation - genetics - forest management - plant breeding - genomen - dna-sequencing - tropische bossen - genetische diversiteit - genetische variatie - genetica - bosbedrijfsvoering - plantenveredeling

Boswellia papyrifera is an important tree species of the extensive Combretum-Terminalia dry tropical forests and woodlands in Africa. The species produces a frankincense which is internationally traded because of its value as ingredient in cosmetic, detergent, food flavor and perfumes productions, and because of its extensive use as incense during religious and cultural ceremonies in many parts of the world. The forests in which B. papyrifera grows are increasingly overexploited at the expense of the economic benefit and the wealth of ecological services they provide. Populations of B. papyrifera have declined in size and are increasingly fragmented. Regeneration has been blocked for the last 50 years in most areas and adult productive trees are dying. Projections showed a 90% loss of B. papyrifera trees in the coming 50 years and a 50% loss of frankincense production in 15 years time.

This study addressed the conservation genetics of B. papyrifera. Forty six microsatellite (SSR) markers were developed for this species, and these genetic markers were applied to characterize the genetic diversity pattern of 12 B. papyrifera populations in Ethiopia. Next to this, also the generational change in genetic diversity and the within-population genetic structure (FSGS) of two cohort groups (adults and seedlings) were studied in two populations from Western Ethiopia. In these populations seedlings and saplings were found and natural regeneration still takes place, a discovery that is important for the conservation of the species.

Despite the threats the populations are experiencing, ample genetic variation was present in the adult trees of the populations, including the most degraded populations. Low levels of population differentiation and isolation-by-distance patterns were detected. Populations could be grouped into four genetic clusters: the North eastern (NE), Western (W), North western (NW) and Northern (N) part of Ethiopia. The clusters corresponded to environmentally different conditions in terms of temperature, rainfall and soil conditions. We detected a low FSGS and found that individuals are significantly related up to a distance of 60-130 m.

Conservation of the B. papyrifera populations is urgently needed. The regeneration bottlenecks in most existing populations are an urgent prevailing problem that needs to be solved to ensure the continuity of the genetic diversity, species survival and sustainable production of frankincense. Local communities living in and around the forests should be involved in the use and management of the forests. In situ conservation activities will promote gene flow among fragmented populations and scattered remnant trees, so that the existing level of genetic diversity may be preserved. Geographical distance among populations is the main factor to be considered in sampling for ex situ conservation. A minimum of four conservation sites for B. papyrifera is recommended, representing each of the genetic clusters. Based on the findings of FSGS analyses, seed collection for ex situ conservation and plantation programmes should come from trees at least 100 m, but preferably 150 m apart.

Tropical forests in a changing world
Zuidema, P.A. - \ 2015
Wageningen : Wageningen University - ISBN 9789462573765 - 24 p.
tropical forests - forests - forest ecology - climatic change - forest management - tropische bossen - bossen - bosecologie - klimaatverandering - bosbedrijfsvoering
Monitoring tropical forest dynamics using Landsat time series and community-based data
DeVries, B.R. - \ 2015
Wageningen University. Promotor(en): Martin Herold, co-promotor(en): Lammert Kooistra; Jan Verbesselt. - Wageningen : Wageningen University - ISBN 9789462574762 - 161
tropische bossen - bosdynamiek - monitoring - landsat - satellieten - tijdreeksen - remote sensing - tropical forests - forest dynamics - satellites - time series

Tropical forests cover a significant portion of the earth's surface and provide a range of

ecosystem services, but are under increasing threat due to human activities. Deforestation

and forest degradation in the tropics are responsible for a large share of global CO2

emissions. As a result, there has been increased attention and effort invested in the

reduction of emission from deforestation and degradation and the protection of remaining

tropical forests in recent years. Methods for tropical forest monitoring are therefore vital

to track progress on these goals. Two data streams in particular have the potential to

play an important role in forest monitoring systems. First, satellite remote sensing is

recognized as a vital technology in supporting the monitoring of tropical forests, of which

the Landsat family of satellite sensors has emerged as one of the most important. Owing

to its open data policy, a large range of methods using dense Landsat time series have

been developed recently which have the potential to greatly enhance forest monitoring

in the tropics. Second, community-based monitoring is supported in many developing

countries as a way to engage forest communities and lower costs of monitoring activities.

The development of operational monitoring systems will need to consider how these data

streams can be integrated for the effective monitoring of forest dynamics.

This thesis is concerned with the monitoring of tropical forest dynamics using a combi-

nation of dense Landsat time series and community-based monitoring data. The added

value conferred by these data streams in monitoring deforestation, degradation and re-

growth in tropical forests is assessed. This goal is approached from two directions. First,

the application of econometric structural change monitoring methods to Landsat time

series is explored and the efficacy and accuracy of these methods over several tropical

forest sites is tested. Second, the integration of community-based monitoring data with

Landsat time series is explored in an operational setting. Using local expert monitoring

data, the reliability and consistency of these data against very high resolution optical

imagery are assessed. A bottom-up approach to characterize forest change in high the-

matic detail using a priori community-based observations is then developed based on

these findings.

Chapter 2 presents a robust data-driven approach to detect small-scale forest disturbances

driven by small-holder agriculture in a montane forest in southwestern Ethiopia. The

Breaks For Additive Season and Trend Monitoring (BFAST Monitor) method is applied

to Landsat NDVI time series using sequentially defined one-year monitoring periods. In

addition to time series breakpoints, the median magnitude of residuals (expected versus

observed observations) is used to characterize change. Overall disturbances are mapped

with producer's and user's accuracies of 73%. Using ordinal logistic regression (OLR)

models, the extent to which degradation and deforestation can be separately mapped is

explored. The OLR models fail to distinguish between deforestation and degradation,

however, owing to the subtle and diffuse nature of forest degradation processes.

Chapter 3 expands upon the approach presented in Chapter 2 by tracking post-disturbance

forest regrowth in a lowland tropical forest in southeastern Peru using Landsat Normalized

Difference Moisture Index (NDMI) time series. Disturbance between 1999 and 2013 are

mapped using the same sequential monitoring method as in Chapter 2. Pixels where

disturbances are detected are then monitored for follow-up regrowth using the reverse of

the method employed in Chapter 2. The time of regrowth onset is recorded based on a

comparison to defined stable history period. Disturbances are mapped with 91% accuracy,

while post-disturbance regrowth is mapped with a total accuracy of 61% for disturbances

before 2006.

Chapter 4 and 5 explore the integration of community-based forest monitoring data and

remote sensing data streams. Major advantages conferred by community-based forest dis-

turbance observations include the ability to report on drivers and other thematic details

of forest change and the ability to detect low-level forest degradation before these changes

are visible above the forest canopy. Chapter 5 builds on these findings and presents a

novel bottom-up approach to characterize forest changes using local expert disturbance

reports to calibrate and validate forest change models based on Landsat time series. Using

random forests and a selection of Landsat spectral and temporal metrics, models describ-

ing forest state variables (deforested, degraded or stable) at a given time are produced.

As local expert data are continually acquired, the ability of these models to predict forest

degradation are shown to improve.

Chapter 6 summarizes the main findings of the thesis and provides a future outlook, given

the prospect of increasing availability of satellite and in situ data for tropical forest mon-

itoring. This chapter argues that forest change methods should strive to utilize satellite

time series and ground data to their maximum potential. As “big data" emerges in the

field of earth observation, new data streams need to be accommodated in monitoring

methods. Operational forest monitoring systems that are able to integrate such diverse

data streams can support broader forest monitoring goals such as quantitative monitoring

of forest dynamics. Even with a wealth of time series based forest disturbance methods

developed recently, forest monitoring systems require locally calibrated forest change esti-

mates with higher spatial, temporal and thematic resolution to support a variety of forest

monitoring objectives.

Interactive community-based tropical forest monitoring using emerging technologies
Pratihast, A.K. - \ 2015
Wageningen University. Promotor(en): Martin Herold, co-promotor(en): L. Ribbe; Sytze de Bruin; Valerio Avitabile. - Wageningen : Wageningen University - ISBN 9789462574786 - 164
tropische bossen - bosmonitoring - remote sensing - satellietbeelden - monitoring - technologie - sociale netwerken - geografische informatiesystemen - participatie - tropical forests - forest monitoring - satellite imagery - technology - social networks - geographical information systems - participation

Forests cover approximately 30% of the Earth’s land surface and have played an indispensable role in the human development and preserving natural resources. At the moment, more than 300 million people are directly dependent on these forests and their resources. Forests also provide habitats for a wide variety of species and offer several ecological necessities to natural and anthropological systems. In spite of this importance, unprecedented destruction of tropical forest cover has been witnessed over the past four decades. Annually, approximately 2.1x105 hectares of forests are lost, with serious negative consequences on the regulation of the world’s climate cycle, biodiversity and other environmental variables. To mitigate these consequences, the United Nations Framework Convention on Climate Change (UNFCCC) has requested the developing countries to adapt new policy in reducing emissions from deforestation and forest degradation (REDD+). Under this policy, countries have been mandated to engage local communities and indigenous groups as critical stakeholders in the design and implementation of a national forest monitoring system (NFMS) that supports measuring, reporting and verification (MRV) of actions and achievements of REDD+ activities.

Current schemes for tropical monitoring are based on remote sensing and field measurements which typically originate from national forest inventories. Remotely sensed imagery has been considered as the principal data source used to calculate forest area change across large areas, assess rates of deforestation and establish baselines for national forest area change databases. Advancements in medium and high resolution satellites, open data policies, time-series analysis methods and big data processing environments are considered valuable for deforestation monitoring at local to global scales. However, cloud cover, seasonality and the restricted spatial and temporal resolution of remote sensing observations limits their applicability in the tropics. Enhancing the interpretation of remote sensing analysis require substantial ground verification and validation. Accomplishing these tasks through national forest inventory data is expensive, time-consuming and difficult to implement across large spatial scales.

Next to remote sensing, community-based monitoring (CBM) has also demonstrated potential in the collection and interpretation of forest monitoring data. However effective implementation of community-based forest monitoring systems is currently lacking due to two reasons: 1) the role of communities in NFMS is unclear and 2) tools that can support local communities to explore opportunities and facilitate forest monitoring are still scarce. This thesis addresses these two issues by proposing technical solutions (computer and geo-information science) and assessing the capacities and needs of communities in developing countries with a REDD+ implementation and forest monitoring context.

The main goal of this thesis, therefore, is to develop an approach that combines emerging technologies and community-based observations for tropical forest monitoring. To accomplish the main goal, four specific research questions were formulated: 1) What are the potentials to link community-based efforts to national forest monitoring systems? 2) How can information and communication technologies (ICTs) support the automation of community data collection process for monitoring forest carbon stocks and change activities using modern handheld devices? 3) What is the accuracy and compatibility of community collected data compared to other data (e.g., optical remote sensing and expert field measurements) for quantifying forest carbon stocks and changes? and 4) What is a suitable design for an interactive remote sensing and community-based near real-time forest change monitoring system and how can such system be operationalized?

In Chapter 2, scientific literature and 28 readiness preparation proposals from the World Bank Forest Carbon Partnership Facility are reviewed to better define the role and technical conditions for CBM. Based on this review, a conceptual framework was developed under which CBM can contribute as a dedicated and independent stream of measuring and monitoring data to national level forest monitoring efforts. The following chapters are built upon this framework.

Chapter 3 describes a process of designing and implementing an integrated data collection system based on mobile devices that streamlines the community-based forest monitoring data collection, transmission and visualization process. The usability of the system is evaluated in the Tra Bui commune, Quang Nam province, Central Vietnam, where forest carbon and change activities were measured by different means such as local, regional and national experts and high resolution satellite imagery. The results indicate that the local communities were able to provide forest carbon measurements with accuracy comparable to that of expert measurements at lower costs. Furthermore, the results show that communities are more effective in detecting small scale forest degradation caused by subsistence fuelwood collection and selective logging than image analysis using SPOT imagery.

To support the findings of chapter 3, the data acquisition form (mostly activity data related to forest change) for mobile device was further improved in chapter 4. The system was tested by thirty local experts in the UNESCO Kafa Biosphere Reserve, Ethiopia. High resolution satellite imagery and professional measurements were combined to assess the accuracy and complementary use of local datasets in terms of spatial, temporal and thematic accuracy. Results indicate that the local communities were capable of describing processes of change associated with deforestation, forest degradation and reforestation, in terms of their spatial location, extent, timing and causes within ten administrative units. Furthermore, the results demonstrate that communities offer complementary information to remotely sensed data, particularly to signal forest degradation and mapping deforestation over small areas. Based on this complementarity, a framework is proposed for integrating local expert monitoring data with satellite-based monitoring data into a NFMS in support of REDD+ MRV and near real-time forest change monitoring.

Having identified the framework for integrated monitoring systems in chapter 4, chapter 5 describes an interactive web-based forest monitoring system using four levels of geographic information services: 1) the acquisition of continuous data streams from satellite and community-based monitoring using mobile devices, 2) near real-time forest disturbance detection based on satellite time-series, 3) presentation of forest disturbance data through a web-based application and social media and 4) interaction of the satellite-based disturbance alerts with the end-user communities to enhance the collection of ground data. The system was developed using open source technologies and has been implemented together with local experts in UNESCO Kafa Biosphere Reserve, Ethiopia. The results show that the system was able to provide easy access to information on forest change and considerably improve the collection and storage of ground observation by local experts. Social media lead to higher levels of user interaction and noticeably improved communication among stakeholders. Finally, an evaluation of the system confirmed its usability in Ethiopia.

Chapter 6 presents the final conclusions and provides recommendations for further research. The overall conclusion is that the emerging technologies, such as smartphones, Web-GIS and social media, incorporated with user friendly interface improve the interactive participation of local communities in forest monitoring and decrease errors in data collection. The results show that CBM can provide data on forest carbon stocks, forest area changes as well as data that help to understand local drivers of emissions. The thesis also shows, in theory and in practice, how local data can be used to link with medium and high resolution remote sensing satellite images for an operational near real-time forest monitoring system at a local scale. The methods presented in this thesis are applicable to a broader geographic scope. Hence, this thesis emphasizes that policies and incentives should be implemented to empower communities and to create institutional frameworks for community-based forest monitoring in the tropics.

Inauguratie Pieter Zuidema
Zuidema, P.A. - \ 2015
Wageningen UR
tropische bossen - ontbossing - ecosysteemdiensten - bosfragmentatie - klimaatverandering - bosbouweconomie - bosexploitatie - tropical forests - deforestation - ecosystem services - forest fragmentation - climatic change - forest economics - forest exploitation
Hoogleraar Pieter Zuidema vertelt over zijn onderzoek naar invloed van global change op tropische bossen.
Recently evolved diversity and convergent radiations of rainforest mahoganies (Meliaceae) shed new light on the origins of rainforest hyperdiversity
Koenen, E.J.M. ; Clarkson, J.J. ; Pennington, T.D. ; Chatrou, L.W. - \ 2015
New Phytologist 207 (2015)2. - ISSN 0028-646X - p. 327 - 339.
plastid dna-sequences - plant diversity - molecular phylogenetics - south-america - rapid diversification - evolutionary history - tropical forests - guarea meliaceae - global patterns - east dispersal
•Tropical rainforest hyperdiversity is often suggested to have evolved over a long time-span (the ‘museum’ model), but there is also evidence for recent rainforest radiations. The mahoganies (Meliaceae) are a prominent plant group in lowland tropical rainforests world-wide but also occur in all other tropical ecosystems. We investigated whether rainforest diversity in Meliaceae has accumulated over a long time or has more recently evolved. •We inferred the largest time-calibrated phylogeny for the family to date, reconstructed ancestral states for habitat and deciduousness, estimated diversification rates and modeled potential shifts in macro-evolutionary processes using a recently developed Bayesian method. •The ancestral Meliaceae is reconstructed as a deciduous species that inhabited seasonal habitats. Rainforest clades have diversified from the Late Oligocene or Early Miocene onwards. Two contemporaneous Amazonian clades have converged on similar ecologies and high speciation rates. •Most species-level diversity of Meliaceae in rainforest is recent. Other studies have found steady accumulation of lineages, but the large majority of plant species diversity in rainforests is recent, suggesting (episodic) species turnover. Rainforest hyperdiversity may best be explained by recent radiations from a large stock of higher level taxa.
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