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A degree of functional nonfulfillment has a noticeable effect on a planned or defined process, further this is called disturbance. In common there occurrence is possible, but actually there is no chance to forecast the time of occurrence. The task for disturbance management is to provide a structure in which disturbance can be managed controlled, providing an applicable solution according to the situation area and the time of appearance of the disturbance.

Communication: reliability and structure 2. Knowledge: measurability and applicability 3. Technology: exchangeability and application. In response to an unfamiliar disturbance situation the operator has to consider several possible strategic response types; Compensate disturbance, Compensate consequences of the disturbance, Shut —Down, Repair.

Implementing natural disturbance-based management in the boreal forest

The choice of a specific strategy should be derived on the basis of an overall assessment of the situation. Typically such an assessment will have to consider aspects such as: The kind of disturbance, Its possible consequences in relation to overall system goals, The available actions and time resources. It cannot be assumed that the information needed to carry out proper assessment and therefore result will be more losses due to break down and consequence effect.

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At the technical stage, landscape preparation is carried out filling up of ditches, trenches, pits, depressions, ground gaps, leveling off, and terracing of industrial waste banks , hydraulic and reclamation facilities are constructed, toxic waste is buried, fertile soil layer is applied. As a result, land reclamation is provided. At the biological stage, land treatment works are carried out to improve soil properties. Directions of land recultivation Depending on the purposes set, they distinguish between the following directions of land recultivation: nature conservation; for recreational purpose; for agricultural purpose; plant growing; grassland development; forestry; for hydroeconomic purpose.

Plants used at land recultivation Among the plants used to improve land quality were first herbaceous plants of legume family that can fix air nitrogen. For example, for recultivation of the territories of coal mines in Australia ternate clitoria Clitoria ternatea is used. Another plant regularly used for land recultivation is black poplar Populus nigra. Recultivation period can last ten years and more.

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Lodgepole pine Pinus contorta dominates much of the subalpine, with subalpine fir Abies lasiocarpa and Engelmann spruce Picea engelmannii as the late seral species, and whitebark pine Pinus albicaulis dominating at higher elevations. Mid-elevation mixed conifer forests consisting of predominately Douglas-fir Pseudotsuga menziesii , with lodgepole pine, aspen Populus tremuloides , and limber pine Pinus flexilis , are characterized by a boreal warm summer climate and mixed-severity fire regimes, with infrequent high- and low-severity fires Schoennagel and others Lower-elevation sagebrush steppe and shrublands are characterized by an arid cold climate with fire-return intervals ranging from decades to centuries Whisenant ; Bukowski and Baker Analysis of gridded climate datasets for the GYE indicates annual temperatures have already increased by 0.

Despite annual precipitation increasing 0. Leppi and others explain this paradox by suggesting air temperatures and evapotranspiration rates were stronger drivers of summer stream discharge than precipitation implying increased plant water stress via increases in VPD.

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Future climate change is expected to shift vegetation growth in northern latitude forests from being temperature to precipitation limited and drastically increase fire severity, fire occurrence, and area burned Westerling and others ; Williams and others All analyses were carried out using the R statistical program version 3. The U. Disturbance, meteorological, and land cover datasets were considered as potential covariates in both filtering the NDVI dataset for spatial analysis and statistical modeling of NDVI trends Appendix D: Table D1 lists all variables considered.

Only three different disturbance agents were considered: fire, insect, and human, because of a lack of comprehensive datasets for other disturbance types. MTBS data has complete coverage of all public and private lands using consistent methodology Dennison and Brewer Geological Survey. Data on insect disturbance came from the U. ADS polygons were combined from USFS Regions 1, 2, and 4 and transformed into a m resolution raster, re-projected, and masked to forested areas.

The Vegetation Change Tracker forest change analysis algorithm analyzes each Landsat image to create spectral indices and track the spectral trajectory for each pixel to produce a forest disturbance map Huang and others Fire, bark beetle, and human disturbance 1-km resolution raster layers were then used to mask NDVI trends.

For the empirical modeling, the three disturbance datasets were combined to create three explanatory variables: if disturbed, years since disturbance since , and percent of 1-km pixel disturbed. Land cover-type data layers were used to filter NDVI trends to limit spatial analysis to only natural vegetation. The Mann—Kendall trend test corrected for autocorrelation is commonly used for analyzing meteorological time series as an alternative to linear regression tests because Mann—Kendall does not require a normal distribution of the data and accounts for temporal autocorrelation Hamed and Ramachandra Rao ; de Beurs and Henebry , Linear regression models were fit using a suite of environmental variables to explain maximum annual NDVI trend slopes.

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Each explanatory variable was standardized by subtracting their mean from each value and then dividing by their standard deviation. Due to the short growing season within the GYE and the susceptibility of volcanic soils to summer drying, summer abiotic factors heavily influence plant growth and were thereby the focus of presented analysis, with summer considered as the months of June, July, and August JJA.

Both continuous variables were included in the models paired with the if disturbed binary, so for example the years since disturbance component was only used to estimate the response for pixels that were disturbed during the time period analyzed. All seasonal and annual meteorological variables were considered, and the variable with the highest explanatory power was selected for use in the analysis for example, mean summer precipitation for precipitation.

In addition, models of combinations of explanatory variables were fit and compared to determine the model that explained the highest percentage of the variance in NDVI slope based on adjusted R -squared values. A semivariogram was created from the residuals of the fitted selected model to check for remaining spatial autocorrelation. Impact of removing pixels affected by fire, insect, and human disturbances on detected mean trends in maximum annual NDVI.

Annual maximum NDVI variance was 0. Removing human and insect disturbed areas reduced the fraction of greening pixels by another 1. Removing human disturbed areas reduced greening areas west of the parks and removing insect disturbed areas reduced browning areas to the east. Coefficient estimates of standardized explanatory variables on NDVI trends from separate model fits. Meteorological data are Daymet V3. MA mean annual.

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Coefficient estimates of standardized explanatory variables on NDVI trends from the top explanatory model. Higher mean annual temperature and higher change in mean annual temperature had a negative association with NDVI slopes. Significant greening and browning trends were limited in their spatial extent to only The fine-grained spatial pattern of productivity is consistent with previous research in Yellowstone National Park Turner and others , Comparison of NDVI trends between different vegetation types based on NLCD categories indicated different responses by vegetation type, although the range in responses within each category varied widely.

Evergreen forests showed a mean greening response and comprised the areas of strongest detected greening trends in the GYE. The broad NLCD categories limit inference can be made from this analysis.

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Although comparison of NDVI responses at the species level is beyond the scope of this paper, it remains an important area of research for illuminating the underlying mechanism of changes in plant productivity. Recently disturbed pixels were associated with negative NDVI slopes or browning trends. These results are consistent with studies of rapid post-disturbance recovery in the GYE Turner and others , ; Kashian and others , ; Zhao and others and changes in productivity in northern latitude forests in Alaska and Canada Ju and Masek ; Sulla-Menashe and others and reinforce the need for considering landscape history in analysis of plant productivity trends.

As previously mentioned, recovery of NDVI values post-disturbance is sensitive to herbaceous plant recovery, including potential opportunistic exotic species for example, Canada thistle Cirsium arvense and prickly lettuce Lactuca serriola Turner and others Thereby, positive NDVI trends do not indicate whether or not the forest canopy has regenerated specifically nor indicate the composition of native vs.

While statistical modeling supported the importance of disturbance in explaining greening and browning trends in the GYE, it also provided some evidence for the influence of meteorological variables on NDVI trends. Summer precipitation and annual temperature emerged as the meteorological factors with the strongest influence on NDVI trends. The importance of the interaction between mean summer JJA precipitation and change in JJA precipitation demonstrates the importance of the bioclimatic context of climate change.

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Increases in summer precipitation benefitted areas that were relatively dry. It follows that vegetation in the wetter areas were not water limited and thereby did not benefit from increased summer precipitation. The linear model fit instead suggests reductions in summer precipitation benefitted wetter areas, yet precipitation type snow vs.

Increased temperatures in boreal climate regions can facilitate plant growth through an elongated growing season without precipitation limitation Boisvenue and Running , and this is supported by the location of detected greening trends primarily in forests in the boreal climate of western and central GYE. Indeed, process-based model simulations also indicate that warming temperatures will favor positive growth responses for lodgepole pine dominated forests in Yellowstone National Park Smithwick and others Yet, the coolest areas in the GYE, the Absaroka Mountain Range and the Wind River Range are also areas that experienced the greatest increase in mean annual temperatures and high-severity mortality due to mountain pine beetle MacFarlane and others and were associated with browning trends.

Climate warming benefits mountain pine beetles by increasing overwinter survival leading to increased outbreak populations Bentz and others MacFarlane and others used an alternative aerial survey method and found whitebark pine mortality caused by mountain pine beetle to be more widespread than as reported in the Aerial Detection Survey data. Thereby, these detections of browning trends may be interpreted as signals of mountain pine beetle mortality that were not captured in the Aerial Detection Survey data.

Recent studies suggest the decoupling of northern latitude forest growth and warming temperatures, with other factors such as fire disturbance, insect and disease outbreaks, and water stress driving detected trends in forest productivity Goetz and others Our results provide further evidence of the important effects of disturbance on productivity trends and the importance of precipitation during the growing season for tree growth.

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This may suggest that the greening trends previously detected and attributed to warming temperatures and lengthening of the growing season are not spatially consistent across boreal climate zones, nor are these relationships expected to continue under future climate projections. For undisturbed forests during their study period, Sulla-Menashe and others found that the direct effects of climate change showed minimal influence on NDVI trends overall, but with varying effects based on local bioclimatic differences.

Similarly, we show that the effects of precipitation and temperature changes on forest productivity are highly dependent on the local bioclimatic context, driving the sign and magnitude of detected NDVI trends. Global studies suggest that multiple factors drive productivity trends in northern latitudes Nemani and others ; Zhu and others Beyond the climatic and disturbance factors explored in this paper, other possible mechanisms for detected increases in NDVI include a fertilization effect from increases in atmospheric carbon dioxide or nitrogen deposition.

Increases in atmospheric carbon dioxide are expected to increase plant growth. Global ecosystem modeling simulations suggest carbon dioxide fertilization effects may explain more of the observed greening trends in satellite data than climate Piao and others ; Zhu and others Although accounting for carbon dioxide fertilization effects was outside the scope of this paper, it remains a potentially important driver of detected NDVI trends.

Process-based ecosystem modeling offers an opportunity for testing and quantifying the relative effects of carbon dioxide increases and climate change on plant productivity in the GYE. Increases in nitrogen deposition can also stimulate plant growth. Soils vary within the GYE from nutrient-poor rhyolitic soils of the Yellowstone Caldera to andesitic soils of higher-elevation forests that are higher in nutrients and water holding capacity Despain The productivity of lodgepole pine forests on rhyolitic soils is generally considered nitrogen limited Fahey and others ; thereby, increased nitrogen availability could act as a fertilizer.

Furthermore, increased annual temperatures and precipitation could stimulate plant growth indirectly through increased soil temperature and moisture facilitating nutrient and water uptake Reddell and others Finally, it is worth noting that the inferences in this study are limited by the temporal extent and quality of the disturbance data.