709 research outputs found
Linking the Conservation of Culture and Nature: A Case Study of Sacred Forests in Zimbabwe
This paper examines the role of traditional religious beliefs and traditional leaders in conserving remnant patches of a unique type of dry forest in the Zambezi Valley of northern Zimbabwe. We examined aerial photographs spanning more than three decades, interviewed and surveyed local residents, and met with communities to learn about the environmental history of the forests and the factors that have affected land use in the area. Our results show that forest loss is dramatically less in forests that are now considered sacred, or were in the past connected to sacred forests. This supports our hypothesis that traditional spiritual values have influenced human behavior affecting the forests, and have played a role in protecting them until now. We also found that rates of forest loss have been much higher in an area where traditional leaders are relatively disempowered within the post-independence political system compared to an area where traditional leaders have more power. These findings lead us to conclude that a strategy that links the conservation of culture and nature is likely to be more effective in conserving forests than a strategy that ignores traditional beliefs, values, and institutions
Geographic variability in lidar predictions of forest stand structure in the Pacific Northwest
Estimation of the amount of carbon stored in forests is a key challenge for understanding the global carbon cycle, one which remote sensing is expected to help address. However, carbon storage in moderate to high biomass forests is difficult to estimate with conventional optical or radar sensors. Lidar (light detection and ranging) instruments measure the vertical structure of forests and thus hold great promise for remotely sensing the quantity and spatial organization of forest biomass. In this study, we compare the relationships between lidar measured canopy structure and coincident field measurements of forest stand structure at five locations in the Pacific Northwest of the U.S.A. with contrasting composition. Coefficient of determination values (r2) ranged between 41% and 96%. Correlations for two important variables, LAI (81%) and above ground biomass (92%), were noteworthy, as was the fact that neither variable showed an asymptotic response.
Of the 17 stand structure variables considered in this study, we were able to develop eight equations that were valid for all sites, including equations for two variables generally considered to be highly important (aboveground biomass and leaf area index). The other six equations that were valid for all sites were either related to height (which is most directly measured by lidar) or diameter at breast height (which should be closely related to height). Four additional equations (a total of 12) were applicable to all sites where either Douglas-fir (Pseudotsuga menziesii), western hemlock (Tsuga heterophylla) or Sitka spruce (Picea sitchensi) were dominant. Stand structure variables in sites dominated by true firs (Abies sp.) or ponderosa pine (Pinus ponderosa) had biases when predicted by these four additional equations. Productivity-related variables describing the edaphic, climatic and topographic environment of the sites where available for every regression, but only two of the 17 equations (maximum diameter at breast height, stem density) incorporated them. Given the wide range of these environmental conditions sampled, we conclude that the prediction of stand structure is largely independent of environmental conditions in this study area.
Most studies of lidar remote sensing for predicting stand structure have depended on intensive data collections within a relatively small study area. This study indicates that the relationships between many stand structure indices and lidar measured canopy structure have generality at the regional scale. This finding, if replicated in other regions, would suggest that mapping of stand structure using lidar may be accomplished by distributing field sites extensively over a region, thus reducing the overall inventory effort required
Evaluation of the MODIS LAI product using independent lidar-derived LAI: A case study in mixed conifer forest
This study presents an alternative assessment of the MODIS LAI product for a 58,000 ha evergreen needleleaf forest located in the western Rocky Mountain range in northern Idaho by using lidar data to model (R2=0.86, RMSE=0.76) and map LAI at higher resolution across a large number of MODIS pixels in their entirety. Moderate resolution (30 m) lidar-based LAI estimates were aggregated to the resolution of the 1-km MODIS LAI product and compared to temporally-coincident MODIS retrievals. Differences in the MODIS and lidar-derived values of LAI were grouped and analyzed by several different factors, including MODIS retrieval algorithm, sun/sensor geometry, and sub-pixel heterogeneity in both vegetation and terrain characteristics. Of particular interest is the disparity in the results when MODIS LAI was analyzed according to algorithm retrieval class. We observed relatively good agreement between lidar-derived and MODIS LAI values for pixels retrieved with the main RT algorithm without saturation for LAI LAI≤4. Moreover, for the entire range of LAI values, considerable overestimation of LAI (relative to lidar-derived LAI) occurred when either the main RT with saturation or back-up algorithm retrievals were used to populate the composite product regardless of sub-pixel vegetation structural complexity or sun/sensor geometry. These results are significant because algorithm retrievals based on the main radiative transfer algorithm with or without saturation are characterized as suitable for validation and subsequent ecosystem modeling, yet the magnitude of difference appears to be specific to retrieval quality class and vegetation structural characteristics
Extracting ecological and biophysical information from AVHRR optical data: An integrated algorithm based on inverse modeling
Satellite remote sensing provides the only means of directly observing the entire surface of the Earth at regular spatial and temporal intervals
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Lidar-derived canopy architecture predicts brown creeper occupancy of two western coniferous forests
In western conifer-dominated forests where the abundance of old-growth stands is decreasing, species
such as the Brown Creeper (Certhia americana) may be useful as indicator species for monitoring the health
of old-growth systems because they are strongly associated with habitat characteristics associated with old growth
and are especially sensitive to forest management. Light detection and ranging (lidar) is useful for acquiring
fine-resolution, three-dimensional data on vegetation structure across broad areas. We evaluated Brown Creeper
occupancy of forested landscapes by using lidar-derived canopy metrics in two coniferous forests in Idaho. Density
of the upper canopy was the most important variable for predicting Brown Creeper occupancy, although mean
height and height variability were also included in the top models. The upper canopy was twice as dense and the
mean height was almost 50% higher at occupied than at unoccupied sites. Previous studies have found indicators of
canopy density to be important factors for Brown Creeper habitat; however, this represents the first time that lidar
data have been used to examine this relationship empirically through the mapping of the upper canopy density that
cannot be continuously quantified by field-based methods or passive remote sensing. Our model’s performance
was classified as “good” by multiple criteria. We were able to map probabilities of Brown Creeper occupancy in
~50 000 ha of forest, probabilities that can be used at the local, forest-stand, and landscape scales, and illustrate the
potential utility of lidar-derived data for studies of avian distributions in forested landscapes.En los bosques dominados por coníferas del oeste, donde está disminuyendo la abundancia de
rodales maduros, las especies como Certhia americana pueden ser útiles como especies indicadoras para monitorear
la salud de los sistemas maduros debido a que están fuertemente asociadas con las características del hábitat
vinculadas con el bosque maduro y son especialmente sensibles al manejo del bosque. El sistema de detección
y alcance de luz (denominado lidar, un acrónimo del inglés “light detection and ranging”) es útil para adquirir
datos tridimensionales de alta resolución de la estructura de la vegetación a través de grandes áreas. Evaluamos
la ocupación de C. americana de paisajes boscosos usando métricas del dosel derivadas de lidar en dos bosques
de coníferas en Idaho. La densidad del dosel alto fue la variable más importante para predecir la ocupación de
C. americana, aunque la altura media y la variabilidad de la altura también fueron incluidas en los mejores modelos.
El dosel alto fue dos veces más denso y la altura media fue casi 50% más alta en los sitios ocupados que en
los sitios desocupados. Estudios previos han encontrado que los indicadores de densidad del dosel son factores
importantes del hábitat de C. americana; sin embargo, esto representa la primera vez que datos de lidar han sido
usados para examinar esta relación de modo empírico a través del mapeo de la densidad del dosel alto, de un modo
continuo que no puede ser cuantificado por métodos basados en trabajo de campo o muestreo remoto pasivo. El
desempeño de nuestro modelo fue clasificado como “bueno” por múltiples criterios. Fuimos capaces de mapear las
probabilidades de ocupación de C. americana en ~50 000 ha de bosque, probabilidades que pueden ser usadas a
las escalas local, de rodal de bosque y de paisaje, y que ilustran la utilidad potencial de los datos derivados de lidar
para estudios de distribución de aves en paisajes boscosos.Keywords: Brown Creeper,
Certhia americana,
mapping,
habitat,
forest,
occupancy,
lida
Extracting ecological and biophysical information from AVHRR optical data: An integrated algorithm based on inverse modeling
Satellite remote sensing provides the only means of directly observing the entire surface of the Earth at regular spatial and temporal intervals
A Discriminative Distance Learning–Based CBIR Framework for Characterization of Indeterminate Liver Lesions
The remote monad design pattern
Remote Procedure Calls are expensive. This paper demonstrates how to reduce the cost of calling remote procedures from Haskell by using the remote monad design pattern, which amortizes the cost of remote calls. This gives the Haskell community access to remote capabilities that are not directly supported, at a surprisingly
inexpensive cost.
We explore the remote monad design pattern through six models of remote execution patterns, using a simulated Internet of Things toaster as a running example. We consider the expressiveness and optimizations enabled by each remote execution model, and assess the feasibility of our approach. We then present a full-scale case
study: a Haskell library that provides a Foreign Function Interface to the JavaScript Canvas API. Finally, we discuss existing instances of the remote monad design pattern found in Haskell libraries
Terrestrial laser scanning and low magnetic field digitization yield similar architectural coarse root traits for 32-year-old Pinus ponderosa trees
Background Understanding how trees develop their root systems is crucial for the comprehension of how wildland and urban forest ecosystems plastically respond to disturbances such as harvest, fire, and climate change. The interplay between the endogenously determined root traits and the response to environmental stimuli results in
tree adaptations to biotic and abiotic factors, influencing stability, carbon allocation, and nutrient uptake. Combining the three-dimensional structure of the root system, with root morphological trait information promotes a robust understanding of root function and adaptation plasticity. Low Magnetic Field Digitization coupled with AMAPmod
(botAnique et Modelisation de l’Architecture des Plantes) software has been the best-performing method for describing root system architecture and providing reliable measurements of coarse root traits, but the pace and scale of data collection remain difficult. Instrumentation and applications related to Terrestrial Laser Scanning (TLS) have
advanced appreciably, and when coupled with Quantitative Structure Models (QSM), have shown some potential toward robust measurements of tree root systems. Here we compare, we believe for the first time, these two methodologies by analyzing the root system of 32-year-old Pinus ponderosa trees
Results In general, at the total root system level and by root-order class, both methods yielded comparable values for the root traits volume, length, and number. QSM for each root trait was highly sensitive to the root size (i.e., input parameter PatchDiam) and models were optimized when discrete PatchDiam ranges were specified for each trait.
When examining roots in the four cardinal direction sectors, we observed differences between methodologies for length and number depending on root order but not volume.
Conclusions We believe that TLS and QSM could facilitate rapid data collection, perhaps in situ, while providing quantitative accuracy, especially at the total root system level. If more detailed measures of root system architecture are desired, a TLS method would benefit from additional cans at differing perspectives, avoiding gravitational displacement to the extent possible, while subsampling roots by hand to calibrate and validate QSM models. Despite
some unresolved logistical challenges, our results suggest that future use of TLS may hold promise for quantifying tree root system architecture in a rapid, replicable manner
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How much does the time lag between wildlife field-data collection and LiDAR-data acquisition matter for studies of animal distributions? A case study using bird communities
Vegetation structure quantified by light detection and ranging (LiDAR) can improve understanding of wildlife occupancy and species-richness patterns. However, there is often a time lag between the collection of LiDAR data and wildlife data. We investigated whether a time lag between the LiDAR acquisition and field-data acquisition affected mapped wildlife distributions ranging from an individual species distribution to total avian species richness in a conifer forest. We collected bird and LiDAR data in 2009 across a 20,000 ha forest in northern Idaho. Using the 2009 LiDAR data, we modelled the probability of occurrence for the brown creeper (Certhia americana). Using the same 2009 LiDAR data, we additionally modelled total avian species richness and richness of three different bird nesting guilds (ground/understory, mid/upper canopy and cavity). We mapped brown creeper occupancy probability and species richness using the 2009 models, and then compared these maps with maps based on the same models applied to a 2003-LiDAR dataset. A prior study identified areas harvested between 2003 and 2009. There was on average a 5% absolute decrease in mapped probabilities of brown creeper occurrence in non-harvest areas between 2003 and 2009. Species richness changed by less than one species in all cases within non-harvest areas between the 2003 and 2009 maps. Although these comparisons were statistically significant at the p < 0.0001 level, it is likely that the high number of map cells (~480,000) influenced this result. Similar patterns between our 2003 and 2009 maps in non-harvest areas for this suite of avian responses suggests that a 6-year difference between field-data collection and LiDAR-data collection has a minimal effect on mapped avian patterns in an undisturbed coniferous forest. However, because this is one case study in one ecosystem, additional work examining the effect of temporal lags between LiDAR and field-data collection on mapping wildlife distributions is warranted in additional ecosystems
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