Secondary Forest Detection in a Neotropical Dry Forest Landscape Using Landsat 7 ETM+ and IKONOS Imagery1

We integrate forest structure and remotely sensed data for four successional stages (pasture, early, intermediate, and late) of a tropical dry forest area located in the Sector Santa Rosa of the Guanacaste Conservation Area in northwestern Costa Rica. We used a combination of spectral vegetation indices derived from Landsat 7 ETM+ medium resolution and IKONOS high‐resolution imagery. The indices (using the red and near‐infrared bands) simple ratio and normalized difference vegetation index separated the successional stages well. Two other indices using mid‐infrared bands did not separate successional stages as well. In a comparison of the successional stages with chronological age, there was no separability in the spectral reflectance among different age classes. Successional stages, in contrast, showed distinct groups with minimal overlap. We also applied a simple validation in another dry forest located in the Palo Verde National Park in the province of Guanacaste, Costa Rica, with reasonably good results.     

Ecosystem classification and inventory maps as surrogates for ground beetle assemblages in boreal forest

Aims We compare performance of ecosystem classification maps and provincial forest inventory data derived from air photography in reflecting ground beetle (Coleoptera: Carabidae) biodiversity patterns that are related to the forest canopy mosaic. Our biodiversity surrogacy model based on remotely sensed tree canopy cover is validated against field-collected ground data.Methods We used a systematic sampling grid of 198 sites, covering 84 km 2 of boreal mixedwood forest in northwestern Alberta, Canada. For every site, we determined tree basal area, characterized the ground beetle assemblage and obtained corresponding provincial forest inventory and ecosystem classification information. We used variation partitioning, ordination and misclassification matrices to compare beetle biodiversity patterns explained by alternative databases and to determine model biases originating from air photo-interpretation.Important findings Ecosystem classification data performed better than canopy cover derived from forest inventory maps in describing ground beetle biodiversity patterns. The biodiversity surrogacy models based on provincial forest inventory maps and field survey generally detected similar patterns but inaccuracies in air photo-interpretation of relative canopy cover led to differences between the two models. Compared to field survey data, air photo-interpretation tended to confuse two Picea species and two Populus species present and homogenize stand mixtures. This generated divergence in models of ecological association used to predict the relationship between ground beetle assemblages and tree canopy cover. Combination of relative canopy cover from provincial inventory with other geo-referenced land variables to produce the ecosystem classification maps improved biodiversity predictive power. The association observed between uncommon surrogates and uncommon ground beetle species emphasizes the benefits of detecting these surrogates as a part of landscape management. In order to complement conservation efforts established in protected areas, accurate, high resolution, wide ranging and spatially explicit knowledge of landscapes under management is primordial in order to apply effective biodiversity conservation strategies at the stand level as required in the extensively harvested portion of the boreal forest. In development of these strategies, an in-depth understanding of vegetation is key.     

Effects of Season and Successional Stage on Leaf Area Index and Spectral Vegetation Indices in Three Mesoamerican Tropical Dry Forests1

We compared plant area index (PAI) and canopy openness for different successional stages in three tropical dry forest sites: Chamela, Mexico; Santa Rosa, Costa Rica; and Palo Verde, Costa Rica, in the wet and dry seasons. We also compared leaf area index (LAI) for the Costa Rican sites during the wet and dry seasons. In addition, we examined differences in canopy structure to ascertain the most influential factors on PAI/LAI. Subsequently, we explored relationships between spectral vegetation indices derived from Landsat 7 ETM+ satellite imagery and PAI/LAI to create maps of PAI/LAI for the wet season for the three sites. Specific forest structure characteristics with the greatest influence on PAI/LAI varied among the sites and were linked to climatic differences. The differences in PAI/LAI and canopy openness among the sites were explained by both the past land‐use history and forest management practices. For all sites, the best‐fit regression model between the spectral vegetation indices and PAI/LAI was a Lorentzian Cumulative Function. Overall, this study aimed to further research linkages between PAI/LAI and remotely sensed data while exploring unique challenges posed by this ecosystem.     

A Decade of Streamwater Nitrogen and Forest Dynamics after a Mountain Pine Beetle Outbreak at the Fraser Experimental Forest,Colorado

Forests of western North America are currently experiencing extensive tree mortality from a variety of bark beetle species, and insect outbreaks are projected to increase under warmer, drier climates. Unlike the abrupt biogeochemical changes typical after wildfire and timber harvesting, the outcomes of insect outbreaks are poorly understood. The mountain pine bark beetle (Dendroctonus ponderosae) began to attack lodgepole pine (Pinus contorta) at the Fraser Experimental Forest in 2002 and spread throughout the research area by 2007. We compared streamwater nitrogen (N) from 2003 through 2012 with data from the previous two decades in four watersheds with distinct forest management histories, stand structures, and responses to the beetle outbreak. Watersheds dominated by old-growth had larger trees and lost 85% of overstory pine and 44% of total basal area to bark beetles. In contrast, managed watersheds containing a mixture of second-growth (30–60 year old) and old-growth (250- to 350-year old) had higher density of subcanopy trees, smaller mean tree diameter, and lower bark beetle-induced mortality (~26% of total basal area). Streamwater nitrate concentrations were significantly higher in old-growth watersheds during the outbreak than pre-outbreak levels during snowmelt and base flow seasons. In mixed-age stands, streamwater nitrate concentrations were unaffected by the outbreak. Beetle outbreak elevated inorganic N export 43 and 74% in two old-growth watersheds though the amounts of N released in streamwater were low (0.04 and 0.15 kg N ha^?1) relative to atmospheric inputs (<2% of annual N deposition). Increased height, diameter, and foliar N of measured in residual live trees augmented demand for N, far in excess of the change in N export during the outbreak. Reallocation of soil resources released after pine mortality to overstory and understory vegetation helps explain high nutrient retention in watersheds affected by bark beetle outbreaks.     

What explains landscape patterns of tree mortality caused by bark beetle outbreaks in Greater Yellowstone?

Aim Bark beetle outbreaks have recently affected extensive areas of western North American forests, and factors explaining landscape patterns of tree mortality are poorly understood. The objective of this study was to determine the relative importance of stand structure, topography, soil characteristics, landscape context (the characteristics of the landscape surrounding the focal stand) and beetle pressure (the abundance of local beetle population eruptions around the focal stand a few years before the outbreak) to explain landscape patterns of tree mortality during outbreaks of three species: the mountain pine beetle, which attacks lodgepole pine and whitebark pine; the spruce beetle, which feeds on Engelmann spruce; and the Douglas‐fir beetle, which attacks Douglas‐fir. A second objective was to identify common variables that explain tree mortality among beetle–tree host pairings during outbreaks. Location Greater Yellowstone ecosystem, Wyoming, USA. Methods We used field surveys to quantify stand structure, soil characteristics and topography at the plot level in susceptible stands of each forest type showing different severities of infestation (0–98% mortality; n= 129 plots). We then used forest cover and beetle infestation maps derived from remote sensing to develop landscape context and beetle pressure metrics at different spatial scales. Plot‐level and landscape‐level variables were used to explain outbreak severity. Results Engelmann spruce and Douglas‐fir mortality were best predicted using landscape‐level variables alone. Lodgepole pine mortality was best predicted by both landscape‐level and plot‐level variables. Whitebark pine mortality was best – although poorly – predicted by plot‐level variables. Models including landscape context and beetle pressure were much better at predicting outbreak severity than models that only included plot‐level measures, except for whitebark pine. Main conclusions Landscape‐level variables, particularly beetle pressure, were the most consistent predictors of subsequent outbreak severity within susceptible stands of all four host species. These results may help forest managers identify vulnerable locations during ongoing outbreaks.     

Modeling above‐ground litterfall in eastern Mediterranean conifer forests using fractional tree cover,and remotely sensed and ground data

Question: How can we model above‐ground litterfall in Mediterranean conifer forests using remotely sensed and ground data, and geographic information systems (GIS)? Location: Eastern Mediterranean conifer forest of Turkey. Methods: Above‐ground litterfall from Mediterranean forest stands of Pinus nigra, Cedrus libani, Pinus brutia and Juniperus excelsa and mixed Abies cilicica, C. libani and P. nigra was modeled as a function of fractional tree cover using a regression tree algorithm, based on IKONOS and Landsat TM/ETM+data. Landsat TM/ETM+images for the study area were used to map actual stand patterns, based on a land‐cover map of species stands using a supervised classification. Results: Total amount of annual above‐ground litterfall for the entire study area (12 260 km²) was estimated at 417.2 Mg ha^?1 for P. brutia, 291.1 Mg ha^?1 for the mixed stand, 115.5 Mg ha^?1 for P. nigra, 54.6 Mg ha^?1 for J. excelsa and 45.9 Mg ha^?1 for C. libani. The maps generated indicate the distribution of the seasonal amount of total above‐ground litterfall for different species and the distribution of species stands in the study area. There was an increase in the amount of above‐ground litterfall for P. brutia stand in summer, for J. excelsa in autumn and for C. libani, P. nigra and the mixed stand of A. cilicica, P. nigra and C. libani in winter. Conclusion: Application of this model helps to improve the accuracy of estimated litterfall input to soil organic carbon pools in the Mediterranean conifer forests.     

Effects of Dwarf Mistletoe on Stand Structure of Lodgepole Pine Forests 21-28 Years Post-Mountain Pine Beetle Epidemic in Central Oregon

Lodgepole pine (Pinus contorta) forests are widely distributed throughout North America and are subject to mountain pine beetle (Dendroctonus ponderosae) epidemics, which have caused mortality over millions of hectares of mature trees in recent decades. Mountain pine beetle is known to influence stand structure, and has the ability to impact many forest processes. Dwarf mistletoe (Arceuthobium americanum) also influences stand structure and occurs frequently in post-mountain pine beetle epidemic lodgepole pine forests. Few studies have incorporated both disturbances simultaneously although they co-occur frequently on the landscape. The aim of this study is to investigate the stand structure of lodgepole pine forests 21–28 years after a mountain pine beetle epidemic with varying levels of dwarf mistletoe infection in the Deschutes National Forest in central Oregon. We compared stand density, stand basal area, canopy volume, proportion of the stand in dominant/codominant, intermediate, and suppressed cohorts, average height and average diameter of each cohort, across the range of dwarf mistletoe ratings to address differences in stand structure. We found strong evidence of a decrease in canopy volume, suppressed cohort height, and dominant/codominant cohort diameter with increasing stand-level dwarf mistletoe rating. There was strong evidence that as dwarf mistletoe rating increases, proportion of the stand in the dominant/codominant cohort decreases while proportion of the stand in the suppressed cohort increases. Structural differences associated with variable dwarf mistletoe severity create heterogeneity in this forest type and may have a significant influence on stand productivity and the resistance and resilience of these stands to future biotic and abiotic disturbances. Our findings show that it is imperative to incorporate dwarf mistletoe when studying stand productivity and ecosystem recovery processes in lodgepole pine forests because of its potential to influence stand structure.     

采用广义加法模型整合数字高程模型和遥感数据进行植被分布预测

为了采用广义加法模型整合数字高程模型和遥感数据进行植被分布的预测, 并探索耦合环境变量和遥感数据作为预测变量是否能够有效地提高植被分布预测的精度, 选择海拔、坡度、至黄河最近距离、至海岸线最近距离, 以及从SPOT5遥感影像中提取的光谱变量作为预测变量, 采用广义加法模型整合环境变量和光谱变量, 建立植被分布预测模型。研究设置3种建模情景(以环境变量作为预测变量, 以光谱变量作为预测变量, 综合使用环境变量与光谱变量作为预测变量)对黄河三角洲的优势植被类型的分布进行了预测, 并对预测结果采用偏差分析、受试者工作特征曲线和野外采样点对比等3种方法进行了验证。结果表明: (1)基于广义加法模型的植被分布预测方法具有一定的实用性, 可以较为准确地预测植被的分布; 盖度较高的植被类型预测精度较高, 盖度较低的植被类型预测精度较低, 植物群落结构的特点是出现这些差异的主要原因; 综合使用环境变量和光谱变量作为预测变量的模型, 预测精度高于单独以环境变量或者光谱变量作为预测变量的模型。(2)环境变量、光谱变量大多被选入模型, 二者均对植被分布预测有重要的作用; 同一预测变量在不同植被类型的预测模型中的贡献不同, 这与植被的光谱、环境特征差异有关; 同一预测变量在不同的建模情景下对模型的贡献不同, 环境变量与光谱变量的耦合效应可能是导致预测变量对模型的贡献出现变化的原因。     

Fine-scale genetic population structure of southern pine beetle (Coleoptera: Curculionidae) in Mississippi forests

The southern pine beetle, Dendroctonus frontalis Zimmerman, is the most destructive insect pest of pine forests in the southeastern United States, Mexico, and Central America. Southern pine beetle aggressively attacks pine trees, and when in epidemic stages, they are capable of killing even the most healthy pine trees in a short period of time. Despite the amount of destruction caused by the southern pine beetle and the amount of monetary loss faced by the timber industry and recreation, the population genetics of this species has been limited to comparisons among distant geographic locations. This study investigates the fine-scale genetic population structure of the southern pine beetle in Mississippi. Very little genetic differentiation was observed among samples. Bayesian assignment testing failed to detect multiple groups within all samples; estimates of genetic differentiation and genetic distance were very low in magnitude; and a Mantel test did not reveal a significant relationship between genetic distance and geographic distance. These results suggest that management of the southern pine beetle needs to consider the potential movements of individuals within and among national forests and should be focused on a large scale, at least as big as continuously forested areas and possibly even multiple forests. These results further suggest that removal of beetle-infested trees is important.     

多尺度遥感综合监测我国北方典型草原区植被盖度

利用多尺度遥感影像综合进行全球和区域尺度的土地利用/覆盖变化(LUCC)研究是最近全球变化研究的重要方向之一。本文综合利用野外群落样方、数字相机、ETM+影像、NOAA/AVHRR影像,在遥感、GIS和GPS支持下,对我国北方典型草原区植被盖度进行了综合监测、模拟与分析。结果表明:(1) 利用经处理后的数字相机影像测量盖度的结果准确性较高,可以作为植被盖度测量的标准结果,反映真实的覆盖特征,并用以验证利用其它方法测量结果的精度。(2) 利用野外1 m2样方网格法目视估测的植被盖度结果变化较大,不稳定。本次实验中,与数字相机测量结果相比,样方估测的盖度普遍偏高,平均偏差为9.92%;但两者相关性较好(r2=0.89)。(3) 采用Gutman模型ETM+影像、NOAA/AVHRR影像反演植被盖度的结果与数字相机测量结果偏差分别为7.03%、7.83%,ETM+像元分解NOAA像元后得到的植被盖度与数字相机测量结果偏差5.68%。三者与数字相机测量结果的相关系数r2分别为0.78、0.61和0.76。(4)利用野外实测植被盖度数据直接与NOAA-NDVI影像建立统计模型估算植被盖度的精度较低(r2=0.65),而通过空间分辨率介于两者之间的ETM+影像进行转换后,该精度得到一定的提高(r2=0.80)。利用像元分解的方法提高了大尺度植被盖度监测的精度,是利用遥感数据进行尺     

Leakiness: A new index for monitoring the health of arid and semiarid landscapes using remotely sensed vegetation cover and elevation data

The health of arid and semiarid lands needs to be monitored, particularly if they are used to produce food and fiber, and are prone to loss of vegetation cover and soil. Indicators of landscape health based on remotely sensed data could cost-effectively integrate structural and functional attributes of land surfaces across a range of scales. In this paper, we describe a new index for remotely monitoring changes in the health of land. The new index takes important aspects of landscape structure and function into account by focusing on the potential for landscapes to lose or ‘leak’ (not retain) soil sediments. We combined remotely sensed vegetation patchiness data with digital elevation model (DEM) data to derive a quantitative metric, the landscape leakiness index, LI. This index is strongly linked to landscape function by algorithms that reflect the way in which spatial configuration of vegetation cover and terrain affect soil loss. Linking LI to landscape function is an improvement on existing indicators that are based on qualitatively assessing remotely sensed changes in vegetation cover. Using archived Landsat imagery and Shuttle Radar Topography Mission DEMs, we found for example that LI indicated improvements in the condition or health of a rangeland paddock that was monitored from 1980 to 2002. This paddock is located in central Australia and its improved health is documented by photographs and field data. Although the full applicability of LI remains to be explored, we have demonstrated that it has the potential to serve as a useful ecological indicator for monitoring the health of arid and semiarid landscapes.     

Regional scale relationships between ecosystem structure and functioning: the case of the Patagonian steppes

Aims 1. To characterize ecosystem functioning by focusing on above‐ground net primary production (ANPP), and 2. to relate the spatial heterogeneity of both functional and structural attributes of vegetation to environmental factors and landscape structure. We discuss the relationship between vegetation structure and functioning found in Patagonia in terms of the capabilities of remote sensing techniques to monitor and assess desertification. Location Western portion of the Patagonian steppes in Argentina (39°30′ S to 45°27′ S). Methods We used remotely‐sensed data from Landsat TM and AVHRR/NOAA sensors to characterize vegetation structure (physiognomic units) and ecosystem functioning (ANPP and its seasonal and interannual variation). We combined the satellite information with floristic relevés and field estimates of ANPP. We built an empirical relationship between the Landsat TM‐derived normalized difference vegetation index (NDVI) and field ANPP. Using stepwise regressions we explored the relationship between ANPP and both environmental variables (precipitation and temperature surrogates) and structural attributes of the landscape (proportion and diversity of different physiognomic classes (PCs)). Results PCs were quite heterogeneous in floristic terms, probably reflecting degradation processes. Regional estimates of ANPP showed differences of one order of magnitude among physiognomic classes. Fifty percent of the spatial variance in ANPP was accounted for by longitude, reflecting the dependency of ANPP on precipitation. The proportion of prairies and semideserts, latitude and, to a lesser extent, the number of PCs within an 8 × 8 km cell accounted for an additional 33% of the ANPP variability. ANPP spatial heterogeneity (calculated from Landsat TM data) within an 8 × 8 km cell was positively associated with the mean AVHRR/NOAA NDVI and with the diversity of physiognomic classes. Main conclusions Our results suggest that the spatial and temporal patterns of ecosystem functioning described from ANPP result not only from water availability and thermal conditions but also from landscape structure (proportion and diversity of different PCs). The structural classification performed using remotely‐sensed data captured the spatial variability in physiognomy. Such capability will allow the use of spectral classifications to monitor desertification.     

An overview of the TAMBEETLE model of Dendroctonus frontalis population dynamics

Population dynamics of the southern pine beetle Dendroctonus frontalis has been the subject of intensive research in the USA for more than a decade. TAMBEETLE, an acronym for the mechanistic model of population dynamics of D. frontalis , was developed to abstract contemporary knowledge on the insect. This model was developed as a joint venture between the Biosystems Research Group of Industrial Engineering and the Department of Entomology at Texas A&M University. The approach used to develop the model and the structure of component submodels is described. Research leading to the development of the model involved a series of field and laboratory studies aimed at various aspects of the population system of the insect. This research is reviewed. Important areas needing further research are identified. Studies dealing with factors involved in initiation of infestions, biome-level epidemiology, host susceptibility, stand modeling, and dynamics of within-tree mortality were emphasized as important topics for further research.     

Coupling satellite data with in situ measurements and numerical modeling to study fine suspended-sediment transport: a study for the lagoon of New Caledonia

This paper investigates the potential of remotely sensed data to map turbidity in a coral reef lagoon and to calibrate a numerical model of fine suspended-sediment transport. Simultaneous measurements of turbidity depth-profile and above-water spectral reflectance integrated according Landsat 7 ETM+ band 2 spectral sensitivity provide a linear regression relationship for the southwest lagoon of New Caledonia (r²=0.95, n=40). This relationship is applied to an empirically atmospherically corrected Landsat ETM+ image of the lagoon acquired on October 23, 2002. A comparison between Landsat estimates of turbidity and concurrent measurements at 14 stations indicates that the mean standard error in the satellite-estimated turbidity is 17.5%. The numerical model introduced in Douillet et al. (2001) is used to simulate the transport of fine suspended sediments in the lagoon in October 2002. A calibration of the erosion rate coefficient required by the model is proposed using in situ turbidity profiles and the remotely sensed turbidity field. In situ data are used to tune locally the erosion rate coefficient, while satellite data are used to determine its spatial zonation. We discuss necessary improvements in coupled studies of fine-sediment transport in coastal zones, namely relationships between turbidity and sediment concentration, integration of wave influence in the model, and correction of bottom reflection in satellite data processing.     

Simulating the impacts of southern pine beetle and fire on the dynamics of xerophytic pine landscapes in the southern Appalachians

Question: Can fire be used to maintain Yellow pine (Pinus subgenus Diploxylon) stands disturbed by periodic outbreaks of southern pine beetle? Location: Southern Appalachian Mountains, USA. Methods: We used LANDIS to model vegetation disturbance and succession on four grids representative of xeric landscapes in the southern Appalachians. Forest dynamics of each landscape were simulated under three disturbance scenarios: southern pine beetle, fire, and southern pine beetle and fire, as well as a no disturbance scenario. We compared trends in the abundance of pine and hardwood functional types as well as individual species. Results: Yellow pine abundance and open woodland conditions were best maintained by a combination of fire and southern pine beetle disturbance on both low elevation sites as well as mid‐elevation ridges & peaks. On mid‐elevation SE‐W facing slopes, pine woodlands were best maintained by fire alone. Conclusions: Our simulations suggest that fire can help maintain open pine woodlands in stands affected by southern pine beetle outbreaks.     

Climate change and the outbreak ranges of two North American bark beetles

Abstract

• 1 One expected effect of global climate change on insect populations is a shift in geographical distributions toward higher latitudes and higher elevations. Southern pine beetle Dendroctonus frontalis and mountain pine beetle Dendroctonus ponderosae undergo regional outbreaks that result in large‐scale disturbances to pine forests in the south‐eastern and western United States, respectively.
• 2 Our objective was to investigate potential range shifts under climate change of outbreak areas for both bark beetle species and the areas of occurrence of the forest types susceptible to them.
• 3 To project range changes, we used discriminant function models that incorporated climatic variables. Models to project bark beetle ranges employed changed forest distributions as well as changes in climatic variables.
• 4 Projected outbreak areas for southern pine beetle increased with higher temperatures and generally shifted northward, as did the distributions of the southern pine forests.
• 5 Projected outbreak areas for mountain pine beetle decreased with increasing temperature and shifted toward higher elevation. That trend was mirrored in the projected distributions of pine forests in the region of the western U.S. encompassed by the study.
• 6 Projected outbreak areas for the two bark beetle species and the area of occurrence of western pine forests increased with more precipitation and decreased with less precipitation, whereas the area of occurrence of southern pine forests decreased slightly with increasing precipitation.
• 7 Predicted shifts of outbreak ranges for both bark beetle species followed general expectations for the effects of global climate change and reflected the underlying long‐term distributional shifts of their host forests.

     

多尺度遥感综合监测我国北方典型草原区植被盖度

利用多尺度遥感影像综合进行全球和区域尺度的土地利用/覆盖变化(LUCC)研究是最近全球变化研究的重要方向之一.本文综合利用野外群落样方、数字相机、ETM+影像、NOAA/AVHRR影像,在遥感、GIS和GPS支持下,对我国北方典型草原区植被盖度进行了综合监测、模拟与分析.结果表明:(1)利用经处理后的数字相机影像测量盖度的结果准确性较高,可以作为植被盖度测量的标准结果,反映真实的覆盖特征,并用以验证利用其它方法测量结果的精度.(2)利用野外1 m2样方网格法目视估测的植被盖度结果变化较大,不稳定.本次实验中,与数字相机测量结果相比,样方估测的盖度普遍偏高,平均偏差为9.92%;但两者相关性较好(r2=0.89).(3)采用Gutman模型ETM+影像、NOAA/AVHRR影像反演植被盖度的结果与数字相机测量结果偏差分别为7.03%、7.83%,ETM+像元分解NOAA像元后得到的植被盖度与数字相机测量结果偏差5.68%.三者与数字相机测量结果的相关系数r2分别为0.78、0.6l和0.76.(4)利用野外实测植被盖度数据直接与NOAA-NDVI影像建立统计模型估算植被盖度的精度较低(r2=0.65),而通过空间分辨率介于两者之间的ETM+影像进行转换后,该精度得到一定的提高(r2=0.80).利用像元分解的方法提高了大尺度植被盖度监测的精度,是利用遥感数据进行尺度转换研究的重要实践.多尺度遥感影像的综合对地观测对大区域上反演植被盖度有很好的促进作用.     

Laboratory study of conspecific avoidance by host-colonizingDendroctonus frontalis Zimm. (Coleoptera: Scolytidae)

Bark/phloem disk sandwiches (100 cm²) were colonized with one to six mating pairs of the southern pine beetle, Dendroctonus frontalis Zimm., to observe gallery construction and evaluate if avoidance behavior occurs between beetles. Frequencies of turn aways, touches, and crosses (three characteristics used to describe conspecific interaction) all increased significantly with beetle density. A threshold of three mating pairs within the 100- cm² phloem area was the density at which avoidance behavior became evident. At a threshold of five mating pairs the number of gallery crossings was significantly greater than at lower densities. Single and paired female beetles introduced into artificial galleries crossed empty neighboring galleries significantly more often than when neighboring galleries were occupied with other D. frontalis. The data suggest that D. frontalis females can regulate gallery spacing within the host through their ability to detect nearby beetles and their galleries. Possible spacing mechanisms are discussed.     

Object-oriented methods for habitat mapping at multiple scales – Case studies from Northern Germany and Wye Downs, UK

This paper presents an application of object-oriented techniques for habitat classification based on remotely sensed images and ancillary data. The study reports the results of habitat mapping at multiple scales using Earth Observation (EO) data at various spatial resolutions and multi temporal acquisition dates. We investigate the role of object texture and context in classification as well as the value of integrating knowledge from ancillary data sources. Habitat maps were produced at regional and local scales in two case studies; Schleswig-Holstein, Germany and Wye Downs, United Kingdom. At the regional scale, the main task was the development of a consistent object-oriented classification scheme that is transferable to satellite images for other years. This is demonstrated for a time series of Landsat TM/ETM+ scenes. At the local scale, investigations focus on the development of appropriate object-oriented rule networks for the detailed mapping of habitats, e.g. dry grasslands and wetlands using very high resolution satellite and airborne scanner images. The results are evaluated using statistical accuracy assessment and visual comparison with traditional field-based habitat maps. Whereas the application of traditional pixel-based classification result in a pixelised (salt and pepper) representation of land cover, the object-based classification technique result in solid habitat objects allowing easy integration into a vector-GIS for further analysis. The level of detail obtained at the local scale is comparable to that achieved by visual interpretation of aerial photographs or field-based mapping and also retains spatially explicit, fine scale information such as scrub encroachment or ecotone patterns within habitats.     

Temperature extremes, density dependence, and southern pine beetle (Coleoptera: Curculionidae) population dynamics in east Texas

Previous studies of the southern pine beetle, Dendroctonus frontalis Zimm., established that its population in east Texas responds to a delayed density-dependent process, whereas no clear role of climate has been determined. We tested two biological hypotheses for the influence of extreme temperatures on annual southern pine beetle population growth in the context of four alternative hypotheses for density-dependent population regulation. The significance of climate variables and their interaction with population regulation depended on the model of density dependence. The best model included both direct and delayed density dependence of a cubic rather than linear form. Population growth declined with the number of days exceeding 32 degrees C, temperatures previously reported to reduce brood survival. Density dependence also changed with the number of hot days. Growth was highest in years with average minimum winter temperatures. Severely cold winters may reduce survival, whereas warm winters may reduce the efficiency of spring infestation formation. Whereas most previous studies have incorporated climate as an additive effect on growth, we found that the form of delayed density dependence changed with the number of days >32 degrees C. The interaction between temperature and regulation, a potentially common phenomenon in ecology, may explain why southern pine beetle outbreaks do not occur at perfectly regular intervals. Factors other than climate, such as forest management and direct suppression, may have contributed significantly to the timing, severity, and eventual cessation of outbreaks since the mid-1950s.