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WP6: Searching the brink: assessing indicators for system change through hyper-spectral analyses of mangrove systems

Research group
Project leaders:
Prof. Dr. A.K.Skidmore
Prof. Dr. Wawan Kustiawan

Researcher:
Mr. A. Fauzi, MSc

Other participants:
Prof. Dr. H.H.T. Prins
Dr. ir. I.M.A. Heitkönig
Dr. J. De Leeuw

3. Summary of the project
Mangroves provide ecosystem services and economic values in many tropical coastlines. The mangroves of East Kalimantan are threatened by two anthropogenic disturbances. Firstly, upstream deforestation causes a washing out of nutrients and soils, which have mainly negative ecological effects on downstream mangrove communities. Secondly, the building of shrimp ponds results both in a loss and fragmentation of mangrove forests, and in a subsequent increase of pollution. Although mangrove communities appear to be resilient to low and moderate disturbances, the transition from an undegraded to a degraded state can be very fast. Such transitions from a desirable to an undesirable state are difficult to predict and show the hallmarks of an associated hysteresis effect. Since degraded states are stable, they are difficult or even impossible to restore. Therefore, finding indicators to detect early signs of degradation may help taking counter measures in time to prevent further degradation of the desirable state past the point of no return.
A desirable state looses its resilience when the associated feed-back mechanisms fail to operate. This is when e.g., closed mangrove canopies form open patches, recruitment lags behind, and seedlings fail to establish themselves. We hypothesize that early signs of disturbance-induced stress in mangrove plants may be found in changes in the chemical composition of foliage. We furthermore hypothesize that relevant leaf physiological changes can be studied with hyperspectral remote sensing.

Our objectives are:

  • To detect hyperspectral wavebands sensitive to changes in chemical levels in mangrove foliage that are linked to disturbance-induced plant stress.

  • To understand how the chemical composition of mangrove foliage responds to deforestationinduced sediment increase, and shrimp farming effluents, i.e. separate from natural fluctuations in the environment.

  • To test early changes in disturbance-induced chemical composition of mangrove foliage as an indicator of system change.

The research project will focus on the detection of the sediment- and shrimp-farm-induced changes in canopy cover and leaf physiology in mangrove stands in the Mahakam delta (disturbed) and the results will be compared with other estuaries with less (Balikpapan bay) or no disturbance (Berau delta), supported by experiments in the field (Mahakam) and in the Netherlands. An important component will be the use of hyperspectral remote sensing together with artificial neural networks, which have recently been applied in the retrieval of canopy variables and for classification routines. Results will be crosslinked with peer projects in the research cluster.

4. Detailed description of the project
a. Scientific Background
Upland deforestation and local shrimp farming threaten the mangroves of East Kalimantan. Deforestation causes downstream accretion and eutrophication by washing out of nutrients and soils, while building of ponds for shrimp farming results in mangrove loss and fragmentation. Moreover, shrimp farms load the environment with high concentrations of ammonia and particulate organic matter which alter mangrove soil conditions and affect mangrove stand growth1. Eutrophication of coastal waters has led to increased primary production, and altered food chains and oxygen supplies2. Feedback mechanisms in mangroves provide system resilience while regulating the capacity to buffer disturbances3. However, transitions from a healthy to a degraded state are difficult to predict and show the hallmarks of an associated hysteresis effect; degraded states are undesirable also because they are very difficult to restore4,5.
The Convention on Biological Diversity calls for more studies on “surprises and sudden changes” in ecosystem functioning, and recognises non-linearity as one of the key problems of ecosystem management. In view of this it is important to develop indicators to detect early signs of degradation so that counter measures can be taken to prevent further degradation past the point of no return (Open Science Meeting Yogayakarta, September 2005). Searching for system indicators is a major task given to the scientific community by the Conference of Parties of the Convention on Biological Diversity, but also UNEP, FAO, ICCP and policy makers the world over are in desperate need of such indicators.
Recent studies6 suggest that vegetation attributes can form an early warning to state change. Cusp-fault systems with non-equilibrium dynamics typically change abruptly from one state to the other. Such abruptly changing state variables are not suitable as predictive indicators for upcoming change. More potential for early change detection exist with variables loosely coupled to and preceding the change of the variable which switches between alternative states.
In the present project, we propose to develop indicators which reflect the impact of environmental stress on mangrove systems. Leaf chemistry traces plant physiological responses, which, when indicative of stress, may precede more abrupt and irreversible changes. The first can be induced, chemically analysed, and tracked by hyperspectral analysis of leaves or trees, the latter change can be tracked by cheaper, more conventional remotely sensed imagery.
Development of such leaf chemical stress indicators requires sound ecological knowledge on the response of mangrove communities to changes in environmental conditions. Such knowledge is scarce which hampers our understanding7 and thereby the possibility to implement such indicators. The current project aims to fill this gap. It aims to analyse plant responses to eutrophication, salinity and sedimentation, to invert models derived from this and to explore the possibility to assess the spatial extent of disturbance related stress in mangrove communities. We will derive a set of hypotheses that we will test using a combination of field observations, laboratory experiments, and remote sensing. This will help develop system indicators at leaf, tree, and stand level that may eventually be used to warn against the risk of losing ecological functions of mangrove systems.

Mangrove ecology and physiology
Mangroves are dynamic systems, offering important services, like coastal protection, construction wood, or habitat for economically important resources, such as shrimps, benthic crabs and fishes8,9. Mangroves are able to trap sediment and nutrients and thereby function as important buffers for coastal seagrass beds and coral reefs, mitigating the effects of heavily loaded sediment inputs from river systems10. Embankment of shrimp ponds within a mangrove belt often results in impeded drainage and changes in soil aeration, soil pH and salinity, while wholesale removal of mangroves and subsequent abandonment of shrimp ponds leaves behind degraded soils that can be recolonized by mangroves only with difficulty or not at all11,12.
Mangroves are rich in metabolites such as polyphenols, and show marked responses to additional nutrient application7. They also show a marked degree of tolerance towards heavy metals7. We propose that this is linked to their carbon-based leaf physiology, and that the polluting metals are ‘caught’ in phenolic conjugates, making them immobile and physiologically inert. We further propose that both adult mangrove trees and seedlings are affected by different types of stress before a transition of states, but not causal to these transitions. We expect that, under stress, the biochemical signature of plant leaves alters12,13,14. We have shown elsewhere that through hyperspectral remote sensing we are able to not only discriminate among different mangrove species, but also discriminate between different chemical compounds, and measure concentrations of these15.
Controlled experiments will be used to gain understanding how eutrophication and silt accretion affect the spectral response of mangrove leaves and canopies. Such knowledge on spectral response could then be inverted to predict these variables from remote sensing data. Applying remote sensing to predicting the distribution of the impact of these stress factors to the world outside the laboratory is complicated however, when other stress factors have not been taken into account.
Salinity is considered the primary factor determining the distribution of mangrove species while influencing their growth and competitive ability. Salinity gradients like those along estuaries of the Mahakam delta likely relate to species distribution. However, salinity also influences the characteristics of mangrove leaves and canopies while it has impacts on leaf water potential and photosynthetic activity related metabolites and triggers the accumulation of osmoregulators such as proline, mannitol and betaglycine16. Together these will affect the leaf spectral signatures of mangrove species.
Enhanced knowledge about whether these environmental factors exert separately identifiable or compound impacts on leaf spectral characteristics is crucial before attempting to apply remote sensing techniques to assess disturbances such as eutrophication and silt accumulation.

We thus derive the following hypotheses:

  1. Stressed mangrove seedlings and trees can be discriminated from non-stressed ones

  2. Different (hyper)spectral reflection signatures can be ascribed to different types of stress such as sediment accretion and shrimp farm effluents, because of different biochemical pathways;

  3. The spectral reflection signatures ascribed to eutrophication and sediment accumulation can be separated from the spectral response caused by variation in salinity and other natural fluctuations in the environment.

  4. Stresses alluded to the above occur in spatial and temporal patterns that are indicative of changes in ecosystem functioning

We propose to develop indicators of plant stress based on hyperspectral analyses to test the idea that pending catastrophes can also be signalled using remote observations on plant constituents, in addition to vegetation patterning processes and biodiversity changes (WP7). Hyperspectral bands, measured with narrow range light sensors, have shown to provide information on leaf chemistry in grasses17,18 and woody plants19,20, including phenolic compounds, in terrestrial systems. We recently demonstrated that many mangrove species can be identified using this technique21. With airplane sensors an accuracy of 4x4 meters is possible, and with hand-held sensors, individual leaves can be measured. Stress-induced vegetation pattern changes may subsequently be identified through remotely sensed imagery like Landsat ETM+ or ASTER. The latter approach is complementary to WP2. Recent studies in our group demonstrated that we can use remotely sensed imagery not only for the detection of canopy changes, but also for sub-canopy detection of plant species22. This potentially enables the tracking of the growth of mangrove seedlings below the canopy of adult trees.

b. Specific Objective(s)

  • To detect wavebands sensitive to changes in chemical levels in mangrove foliage that are linked to disturbance-induced plant stress.

  • To understand how the chemical composition of mangrove foliage responds to sediment increase and shrimp farming effluents, i.e. separate from natural fluctuations in the environment.

  • To test early changes in disturbance-induced chemical composition of mangrove foliage as an indicator of imminent collapse.

  • To develop an algorithm for recognising hyperspectrally distinguishable indicators of pending mangrove system collapse in less costly Landsat ETM+ or Aster imagery.

c. Workplan
The research project will focus on the detection of the nutrient and sediment-induced change in leaf physiology in mangrove stands in the Mahakam delta (disturbed) and the results will be compared with other estuaries with less (Balikpapan bay) or no disturbance (Berau delta), supported by experiments in the field (Mahakam) and in the Netherlands.
The plant physiological responses to environmental stress will be studied in the field and under greenhouse conditions in order to control and compare the effect of varying salinity, sediment and nutrient treatments (i.e., N, and in particular NH4+ as shrimp farm-induced pollunant), on plant foliar chemistry, and full spectrum reflectance. Through field sampling of leaves, as well as in situ reflectance, we will upscale the laboratory results to the communities in the field. We will derive indices of environmental stress from changes observed in plant physiological responses to these treatments, as well as peer PhD projects in this programme (WP2, WP7).
We will collect field data in East Kalimantan in three estuaries with different stages of disturbance as well as data from greenhouse experiments performed in the Netherlands (the mangrove forest in Burgers Zoo), and Indonesia. We include a factorial experimental set-up where we independently test for the physiological responses of salinity, NH4+ and sediment loads on mangrove foliage. We measure changes in leaf amino acid and chlorophyll levels, to which we also apply hyperspectral measurements. With these data we will devise a method to predict chemical composition of mangrove foliage using hyperspectral remote sensing, following recently developed techniques18,20. An important methodological component will be the use of artificial neural networks.
Since we aim at identifying and tracking stress-induced physiological and morphological changes in mangroves, we need to separate these effects from inter-specific, seasonal, and zonation effects. We therefore focus our study on Rhizophora, Avicennia or Sonneratia species, which have clearly distinguishable leaf and root morphologies; the final choice for the study object will partly depend on availability of these species in the comparative study areas. We furthermore select sampling locations at similar strata to prevent or reduce zonal mixing. Furthermore, fieldwork will be synchronised to coincide with that of other projects in the cluster, taking care to sample different locations in similar seasons during which mangroves have reached leaf maturation.
By carrying out research in Mahakam and two other estuaries, having different stages of disturbance, by detecting and sampling the different stages of mangroves, and by conducting experiments to quantify the physiological response variables, we aim at analysing the differential effects of eutrophication and sedimentation. This contributes to developing an early-warning monitoring technique for mangroves in human-disturbed environments.

d. Scientific Relevance
Mangrove forests provide ecosystem services and economic values in many tropical coastlines. This coastal system is seriously threatened by both inland and coastal developments, particularly deforestation and shrimp farming. Many feedback mechanisms within mangrove systems function as buffers against dramatic changes in physiognomy for as long as the systems remain resilient to disturbance. Beyond the buffering capacity, however, the transition from a desired or apparently healthy to a degraded state can be sudden, and difficult to predict. Unpredictable and irreversible responses of ecosystems to human activities are a particular problem to managers of ecosystems all over the world. The challenge would be to predict future changes in an ecosystem, from early signals detected in specific parts of that ecosystem. We propose to develop indicators in the coastal ecosystem of East Kalimantan by studying changes in leaf chemistry with hyperspectral remote sensing. These ecosystems provide a challenging case for studying state transitions and underlying feedback processes and interactions between different parts of an ecosystem, in that we deal with woody, longlived mangroves. The quest for early-warning system changes indicators developed is embedded in a worldwide framework of the search for indicators that are able to predict climatic changes, desertification, El Nino events or coastal fisheries collapses. Our work will contribute to finding indicators for imminent state transition, which then will enable other researchers to pinpoint the exact locations where the transition can be expected.

5. Participation in a graduate School ('onderzoeksschool')
The PhD student will be registered in the CT de Wit Graduate School for Production Ecology and Resource Conservation (PE & RC)

6. Scientific performance of members of the research group(s)

  • Ferwerda JG, Skidmore AK & Stein A (2006) A bootstrap procedure to select hyperspectral wavebands related to tannin content. International journal of remote sensing, 27, 1413-1424.

  • Vaiphasa C, Ongsomwang S, Vaiphasa T & Skidmore AK (2005) Tropical mangrove species discrimination using hyperspectral data: A laboratory study. Estuarine Coastal and Shelf Science 65:371-379

  • Ferwerda JG, van Wieren SE, Skidmore AK & Prins HHT (2005) Inducing condensed tannin production in Colophospermum mopane: Absence of response to soil N and P fertility and physical damage. Plant and Soil 273:203-209

  • Mutanga O, Skidmore AK, Kumar L & Ferwerda J (2005) Estimating tropical pasture quality at canopy level using band depth analysis with continuum removal in the visible domain. International Journal of Remote Sensing 26:1093-1108

  • Schmidt KS, Skidmore AK, Kloosterman EH, Van Oosten H, Kumar L & Janssen JAM (2004). Mapping coastal vegetation using an expert system and hyperspectral imagery. Photogrammetric Engineering And Remote Sensing 70:703-715

  • Mayaka TB, Hendricks T, Wesseler J & Prins HHT (2005) Improving the benefits of wildlife harvesting in Northern Cameroon: a co-management perspective. Ecological Economics 54:67-80

  • Sankaran M, Hanan NP, Scholes RJ, Ludwig F, Prins HHT , et al. (2005). Determinants of woody cover in African savannas. Nature, 438, 846-849.

  • Mutanga O, Skidmore AK & Prins HHT (2004). Discriminating sodium concentration in a mixed grass species environment of the Kruger National Park using field spectrometry. International Journal of Remote Sensing 25:4191-4201

  • Ludwig F, Dawson TE, Prins HHT, Berendse F & de Kroon H (2004). Below-ground competition between trees and grasses may overwhelm the facilitative effects of hydraulic lift. Ecology Letters 7:623-631

  • Olff H, Ritchie ME & Prins HHT (2002) Global environmental controls of diversity in large herbivores. Nature 415:901-904

  • Leyequien E, J Verrelst, M Slot, G Schaepman-Strub, IMA Heitkönig. Capturing the fugitive: applying remote sensing to animal distribution and diversity. A review. International Journal of Applied Earth Observation and Geoinformation (in press)

  • Bommel FPJ van, IMA Heitkönig, GF Epema, S Ringrose & EM Veenendaal (2006). Remotely sensed habitat indicators for predicting distribution of impala Aepyceros melampus in the Okavango Delta, Botswana. Journal of Tropical Ecology, 22, 101-110

  • Nolet, Bart.A., L. Broftová, Ignas M.A. Heitkönig, Vlastimil Kostkan and Aleš Vorel (2006). Slow acclimatization to translocation in a beaver population due to a climatic shift in food quality? Oikos (in press)

  • Verweij R, J Verrelst, P Loth, IMA Heitkönig & AMH Brunsting (2006). Grazing lawns contribute to the subsistence of medium-sized herbivores in dystrophic savannas. Oikos, 114, 108-116

  • Blom A, R van Zalinge, E Mbea, IMA Heitkönig & HHT Prins (2004) Human impact on wildlife populations within a protected Central African forest. African Journal of Ecology 42: 23-31

  • Chudamani Joshi, Jan de Leeuw, Jelte van Andel, Andrew K. Skidmore, Hari Datt Lekhak, Iris C. van Duren and Nawang Norbu, 2006. Indirect remote sensing of a cryptic forest understorey invasive species. Forest Ecology and Management 225: 245-256.

  • De Leeuw, J., Jia, H., Yang, L., Liu, X., Schmidt, K. and Skidmore, A. K., 2006. Comparing accuracy assessments to infer superiority of image classification methods. International Journal Remote Sensing 27: 223-232.

  • Chudamani Joshi, Jan De Leeuw, Andrew K. Skidmore, Iris C. van Duren, Henk van Oosten. 2006. Remotely sensed estimation of forest canopy density: A comparison of the performance of four methods. International Journal of Applied Earth Observation and Geoinformation

  • Khaemba, W. M., Stein, A., Rasch, D., De Leeuw, J. & Georgiadis, N., 2001. Empirically simulated study to compare and validate sampling methods used in aerial surveys of wildlife populations. African Journal of Ecology 39 (4), 374-382.

  • De Leeuw, J., Waweru, M., Onyango, O., Maloba, M., Nguru, P., Said, M., Aligula, H.M., Reid, R., 2001. Distribution and diversity of wildlife in Northern Kenya in relation to livestock and permanent water points. Biological Conservation 100:297-306.

7. Literature references

  1. Robertson AI & Phillips MJ (1995) Mangroves as filters of shrimp pond effluent: predictions and biogeochemical research needs. Hydrobiologia, 295, 311-321

  2. Boesch DF (2002). Challenges and opportunities for science in reducing nutrient over-enrichment of coastal systems. Estuaries, 25, 886- 900

  3. Trott LA & Alongi DM (2000) The impact of shrimp pond effluent on water quality and phytoplankton biomass in a tropical mangrove estuary. Marine Pollution Bulletin, 40, 947-951

  4. Rietkerk M, Ketner P, Stroosnijder L, Prins HHT (1996). Sahelian rangeland development: a catastrophe? Journal of Range Management, 49, 512-519

  5. Scheffer M, Carpenter S, Foley JA, Folke C, Walker B (2001). Catastrophic shifts in ecosystems. Nature, 413, 591-596

  6. Rietkerk M, Dekker SC, De Ruiter PC, Van de Koppel J (2004). Self-organized patchiness and catastrophic shifts in ecosystems. Science, 305, 1926-1929

  7. Schaffelke B, Mellors J, Duke NC (2005). Water quality in the Great Barrier Reef region: responses of mangrove, seagrass and macroalgal communities. Marine Pollution Bulletin, 51, 279-296

  8. Valiela I, Bowen JL & York JK (2001) Mangrove forests: One of the world’s threatened major tropical environments. Bioscience, 51, 807–815

  9. Mumby PJ et al. (2004) Mangroves enhance the biomass of coral reef fish communities in the Caribbean Nature, 427, 533-536;

  10. Victor S, Golbuu Y, Wolanski E, Richmond RH (2004). Fine sediment trapping in two mangrove fringed estuaries exposed to contrasting land use intensity, Palau, Micronesia. Wetlands Ecology and Management, 12, 277-283

  11. Flaherty M & Karnjanakesorn C (1995) Marine shrimp aquaculture and natural resource degradation in Thailand. Environmental Management, 19, 27-37

  12. Stevenson NJ (1994) Disused Shrimp Ponds: Options for Redevelopment of Mangrove. Coastal Management, 25, 423-425

  13. Parida AK, Das AB, Mittra B (2003) Effects of NaCl stress on the structure, pigment complex composition, and photosynthetic activity of mangrove Bruguiera parviflora chloroplasts. Photosynthetica, 41, 191-200

  14. Parida AK, Das AB, Sanada Y, et al. (2004) Effects of salinity on biochemical components of the mangrove, Aegiceras corniculatum. Aquatic Botany, 80, 77-87

  15. Takemura T, Hanagata N, Sugihara K, et al. (2000) Physiological and biochemical responses to salt stress in the mangrove, Bruguiera gymnorrhiza. Aquatic Botany, 68, 15-28;

  16. Hibino, T. et al. 2001. Molecular cloning and functional characterization of two kinds of betaine aldehyde dehydrogenase in betaine accumulating mangrove Avicennia marina. Plant Molecular Biology 45: 353-363

  17. Mutanga O, Skidmore AK (2004). Integrating imaging spectroscopy and neural networks to map grass quality in the Kruger National Park, South Africa. Remote Sensing of Environment, 90, 104-115

  18. Mutanga O, Skidmore AK, Kumar L & Ferwerda J (2005). Estimating tropical pasture quality at canopy level using band depth analysis with continuum removal in the visible domain. International Journal of Remote Sensing, 26, 1093-1108

  19. Ferwerda JG (2005). Charting the quality of forage. Measuring and mapping the variation of chemical components in foliage with hyperspectral remote sensing. PhD Thesis. Wageningen University, The Netherlands

  20. Ferwerda JG, van Wieren SE, Skidmore AK & Prins HHT (2005) Inducing condensed tannin production in Colophospermum mopane: Absence of response to soil N and P fertility and physical damage. Plant and Soil, 273, 203-209

  21. Vaiphasa C, Ongsomwang S, Vaiphasa T & Skidmore AK (2005) Tropical mangrove species discrimination using hyperspectral data: A laboratory study. Estuarine Coastal and Shelf Science, 65, 371-379

  22. Joshi CM, de Leeuw J, Skidmore AK, van Duren IC and van Oosten HH (2006) Remotely sensed estimation of forest canopy density : a comparison of the performance of four methods. International journal of applied earth observation and geoinformation, 8, 84-95

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