Oleg Panferov

The role of canopy structure in the spectral variation of transmission and absorption of solar radiation in vegetation canopies

This paper presents empirical and theoretical analyses of spectral hemispherical reflectances and transmittances of individual leaves and the entire canopy sampled at two sites representative of equatorial rainforests and temperate coniferous forests. The empirical analysis indicates that some simple algebraic combinations of leaf and canopy spectral transmittances and reflectances eliminate their dependencies on wavelength through the specification of two canopy-specific wavelength-independent variables. These variables and leaf optical properties govern the energy conservation in vegetation canopies at any given wavelength of the solar spectrum. The presented theoretical development indicates these canopy-specific wavelength-independent variables characterize the capacity of the canopy to intercept and transmit solar radiation under two extreme situations, namely, when individual leaves 1) are completely absorptive and 2) totally reflect and/or transmit the incident radiation. The interactions of photons with the canopy at red and near-infrared (IR) spectral bands approximate these extreme situations well. One can treat the vegetation canopy as a dynamical system and the canopy spectral interception and transmission as dynamical variables. The system has two independent states: canopies with totally absorbing and totally scattering leaves. Intermediate states are a superposition of these pure states. Such an interpretation provides powerful means to accurately specify changes in canopy structure both from ground-based measurements and remotely sensed data. This concept underlies the operational algorithm of global leaf area index (LAI), and the fraction of photosynthetically active radiation absorbed by vegetation developed for the moderate resolution imaging spectroradiometer (MODIS) and multiangle imaging spectroradiometer (MISR) instruments of the Earth Observing System (EOS) Terra mission.

Spatial Patterns of NDVI Variation over Indonesia and Their Relationship to ENSO Warm Events during the Period 1982–2006

The present study is based on the assumption that vegetation in Indonesia is significantly affected by climate anomalies that are related to El Nino-Southern Oscillation (ENSO) warm phases (El Nino) during the past decades. The analysis builds upon a monthly time series from the normalized difference vegetation index (NDVI) gridded data from the Advanced Very High Resolution Radiometer (AVHRR) and two ENSO proxies, namely, sea surface temperature anomalies (SSTa) and Southern Oscillation index (SOI), and aims at the analysis of the spatially explicit dimension of ENSO impact on vegetation on the Indonesian archipelago. A time series correlation analysis between NDVI anomalies and ENSO proxies for the most recent ENSO warm events (1982-2006) showed that, in general, anomalies in vegetation productivity over Indonesia can be related to an anomalous increase of SST in the eastern equatorial Pacific and to decreases in SOI, respectively. The net effect of these variations is a significant decrease in NDVI values throughout the affected areas during the ENSO warm phases. The 1982/83 ENSO warm episode was rather short but—in terms of ENSO indices—the most extreme one within the study period. The 1997/98 El Nino lasted longer but was weaker. Both events had significant impact on vegetation in terms of negative NDVI anomalies. Compared to these two major warm events, the other investigated events (1987/88, 1991/92, 1994/95, and 2002/03) had no sig- nificant effect on vegetation in the investigated region. The land cover-type specific sensitivity of vegetation to ENSO anomalies revealed thresholds of vegetation response to ENSO warm events. The results for the 1997/98 ENSO warm event confirm the hypothesis that the vulnerability of vegetated tropical land surfaces to drought conditions is considerably affected by land use intensity. In particular, it could be shown that natural forest areas are more resistant to drought stress than degraded forest areas or cropland. Comparing the spatially explicit patterns of El Nino-related vegetation variation during the major El Nino phases, the spatial distribution of affected areas reveals distinct core regions of ENSO drought impact on vegetation for Indonesia that coincide with forest conversion and agricultural intensification hot spots.

Radiation and temperature responses to a small clear-cut in a spruce forest

Effects of a small clear-cutting on solar radiation, soil and air temperature regimes were investigated by continuous field measurements in a spruce forest in Solling, Central Germany, during vegetation period of 2005. Five meteorological stations, installed in central part of a small clear-cut area (2.5 ha) and close to edges of a surrounding forest, allowed to quantify the spatial variability of meteorological parameters within the clear-cut and to describe the impacts of the forest on clear-cut microclimate. The differences of microclimatic conditions between the clear-cut and the surrounding forest were derived using an additional station installed inside the forest about 150 m from the clear-cut. Results showed that clear-cutting leads to significant changes of spatial and temporal patterns of solar radiation and soil temperature. Solar radiation at the clear-cut was very heterogeneously distributed and about 5-11 times higher than inside the forest. It reached maximum at northeastern part and minimum at southwestern part of the clear-cut. The daily maximal soil temperature at 10 cm depth was measured at northern parts of the clear-cut and it was by up to 6°C higher than in the forest. Daily minimal soil temperature at the clear-cut was about 1-3°C higher than in the forest, too. The main factors influencing the soil temperature patterns were seasonally changed incoming solar radiation, ground vegetation and its phenology, as well as soil moisture. The mean daily maximal air temperature measured at the clear-cut was by up to 2.5°C higher and the mean daily minimal temperature by up to 0.5°C lower than in the surrounded forest.

Response of taiga ecosystems to extreme weather conditions and climate anomalies

The resistance of the biosphere to external impacts is the key problem of modern ecology and geography in view of a vague response of modern ecosystems to current and future climate changes and increasing anthropogenic load [5, 10]. Studies of climate changes clarify only possible delayed structural rearrangement of the modern vegetation cover, shift of vegetation zones, and changes in the productivity and reserves of the carbon pool for large regions. Various climate sce� narios are considered, which assume different rates of economic development and changes in the discharge of greenhouse gases to the atmosphere, as well as his� torical analogues of the current and future climate [5]. On the other hand, describing extreme weather phenomena (EWP) and climate anomalies (CAs) in different regions is becoming a topical issue of modern climate studies [4]. The attention of researchers is focused on studying floods, droughts, tornados, and periods of abnormally high summer temperatures— i.e., the phenomena having dramatic adverse conse� quences for the social and economic sphere. Unfortu� nately, the effect of EWP and CA on ecosystems in general is studied very poorly [4]. It should be taken into account that EWP usually are not considered in common climate scenarios and can be hardly pre� dicted by modern climate models. A priori, this means that

Challenges in Climate-Driven Decision Support Systems in Forestry

The history of Decision Support Systems in forestry is quite long as well as the list of created systems and reviews summarizing their merits and flaws. It is generally recognized that a modern decision support system (DSS) should address simultaneously as many economical and ecological issues as possible without becoming overly complex and still remain understandable for users (Reynolds et al., 2008). The ongoing global change including the climate change sets new boundary conditions for decision makers in the forestry sector. The changing growth conditions (Albert & Schmidt, 2010) and expected increasing number of weather extremes like storms force forest owners to make decisions on how to replace the damaged stands and/or how to mitigate the damages. This decision making process requires adequate information on the future climate as well as on complex climate-forest interactions which could be provided by an appropriate climate-driven decision support tool. Both the damage factors and the forest management (e.g. harvesting) result in changes of the structure of forest stands. The structural changes result in immediate changes of albedo and roughness of land surface as well as of microclimatological conditions within the stand and on the soil surface. The consequences are manifold. The changed stand density and leaf area index trigger energy and water balance changes which in turn increase or decrease the vulnerability of the remaining stand to abiotic and biotic damage factors like droughts or insect attacks. A change of the microclimatic conditions might strengthen the forest against drought, but at the same time reduce its resistance to windthrow. The sign and extent of vulnerability changes depend on complex interactions of the effective climatic agents, aboveand belowground forest structure, and soil. There are many DSS that are capable of assessing one or several risk factors; however there are few that are able to assess the additional increase or decrease of risks triggered by modification of forest structure resulting from previous damage or forest management activities. Disregarding these effects will inevitably lead user to either underor overestimation of the potential damages. The question arises whether these additional risks are significant enough to be considered in a DSS. In this chapter we present a new DSS developed according to the above mentioned requirements and capable to provide decision support taking into account economical and ecological considerations under the conditions of changing climate the Decision Support