scholarly journals Edge fires drive the shape and stability of tropical forests

2018 ◽  
Author(s):  
Laurent Hébert-Dufresne ◽  
Adam F. A. Pellegrini ◽  
Uttam Bhat ◽  
Sidney Redner ◽  
Stephen W. Pacala ◽  
...  
Keyword(s):  
Regional Scale ◽  
Remote Sensing Data ◽  
Fire Frequency ◽  
Propagation Model ◽  
Tree Cover ◽  
Long Distance ◽  
Forest Patches ◽  
Tropical Regions ◽  
Frequency Changes ◽  
The Stability

AbstractIn tropical regions, fires propagate readily in grasslands but typically consume only edges of forest patches. Thus forest patches grow due to tree propagation and shrink by fires in surrounding grasslands. The interplay between these competing edge effects is unknown, but critical in determining the shape and stability of individual forest patches, as well the landscape-level spatial distribution and stability of forests. We analyze high-resolution remote-sensing data from protected areas of the Brazilian Cerrado and find that forest shapes obey a robust perimeter-area scaling relation across climatic zones. We explain this scaling by introducing a heterogeneous fire propagation model for tropical forest-grassland ecotones. Deviations from this perimeter-area relation determine the stability of individual forest patches. At a larger scale, our model predicts that the relative rates of tree growth due to propagative expansion and long-distance seed dispersal determine whether collapse of regional-scale tree cover is continuous or discontinuous as fire frequency changes.

scholarly journals Resilience of the boreal forest in response to Holocene fire-frequency changes assessed by pollen diversity and population dynamics

2010 ◽  
Vol 19 (8) ◽  
pp. 1026 ◽  
Author(s):  
Christopher Carcaillet ◽  
Pierre J. H. Richard ◽  
Yves Bergeron ◽  
Bianca Fréchette ◽  
Adam A. Ali
Keyword(s):  
Boreal Forest ◽  
Boreal Forests ◽  
Frequency Control ◽  
Regional Scale ◽  
Fire Regimes ◽  
Fire Frequency ◽  
Frequency Changes ◽  
Fire Intervals ◽  
In Fire

The hypothesis that changes in fire frequency control the long-term dynamics of boreal forests is tested on the basis of paleodata. Sites with different wildfire histories at the regional scale should exhibit different vegetation trajectories. Mean fire intervals and vegetation reconstructions are based respectively on sedimentary charcoal and pollen from two small lakes, one in the Mixedwood boreal forests and the second in the Coniferous boreal forests. The pollen-inferred vegetation exhibits different trajectories of boreal forest dynamics after afforestation, whereas mean fire intervals have no significant or a delayed impact on the pollen data, either in terms of diversity or trajectories. These boreal forests appear resilient to changes in fire regimes, although subtle modifications can be highlighted. Vegetation compositions have converged during the last 1200 years with the decrease in mean fire intervals, owing to an increasing abundance of boreal species at the southern site (Mixedwood), whereas changes are less pronounced at the northern site (Coniferous). Although wildfire is a natural property of boreal ecosystems, this study does not support the hypothesis that changes in mean fire intervals are the key process controlling long-term vegetation transformation. Fluctuations in mean fire intervals alone do not explain the historical and current distribution of vegetation, but they may have accelerated the climatic process of borealisation, likely resulting from orbital forcing.

scholarly journals Assessing the Importance of Tree Cover Threshold for Forest Cover Mapping Derived from Global Forest Cover in Myanmar

Forests ◽  
2019 ◽  
Vol 10 (12) ◽  
pp. 1062 ◽  
Author(s):  
Kay Khaing Lwin ◽  
Tetsuji Ota ◽  
Katsuto Shimizu ◽  
Nobuya Mizoue
Keyword(s):  
Large Scale ◽  
Forest Cover ◽  
Remote Sensing Data ◽  
Tree Cover ◽  
Tropical Rainforests ◽  
Forest Change ◽  
Tropical Regions ◽  
Ecological Zones ◽  
Optimal Tree ◽  
Forest Cover Mapping

Comprehensive forest cover mapping is essential for making policy and management decisions. However, creating a forest cover map from raw remote sensing data is a barrier for many users. Here, we investigated the effects of different tree cover thresholds on the accuracy of forest cover maps derived from the Global Forest Change Dataset (GFCD) across different ecological zones in a country-scale evaluation of Myanmar. To understand the effect of different thresholds on map accuracy, nine forest cover maps having thresholds ranging from 10% to 90% were created from the GFCD. The accuracy of the forest cover maps within each ecological zone and at the national scale was assessed. The overall accuracies of ecological zones other than tropical rainforest were highest when the threshold for tree cover was less than 50%. The appropriate threshold for tropical rainforests was 80%. Therefore, different optimal tree cover thresholds were required to achieve the highest overall accuracy depending on ecological zones. However, in the unique case of Myanmar, we were able to determine the threshold across the whole country. We concluded that the threshold for tree cover for creating a forest cover map should be determined according to the areal ratio of ecological zones determined from large-scale monitoring. Our results are applicable to tropical regions having similar ecological zones.

scholarly journals Climate change and deforestation boost post-fire grass invasion of Amazonian forests

2019 ◽  
Author(s):  
Bruno L. De Faria ◽  
Arie Staal ◽  
Philip A. Martin ◽  
Prajjwal K. Panday ◽  
Andrea D. Castanho ◽  
...  
Keyword(s):  
Climate Change ◽  
Fire Frequency ◽  
Climatic Conditions ◽  
Tree Cover ◽  
Amazon Forest ◽  
Degraded Ecosystem ◽  
The Stability ◽  
Time Required ◽  
Amazonian Forests ◽  
Grass Invasion

ABSTRACTInteractions among climate change, deforestation and fires are changing the stability of the Amazon forest, and may promote transitions to degraded grassy ecosystem states. However, our ability to predict the locations in the Amazon that are most vulnerable to these transitions is limited. In this study we used a dynamic carbon model to evaluate how drought, climate change and deforestation could affect the probability of post-fire grass invasion across the Amazon, and identify where grass-fire feedbacks may promote the persistence of species-poor degraded forests with savanna-like structure. Our results suggest that, under current climatic conditions, post-fire grass invasion could affect 11% of the Amazon, with the south-eastern Amazon at highest risk of invasion. We forecast that under business as usual climate change, by the end of the century areas with a high probability of post-fire grass invasion will increase to 20% of the Amazon. In 10% of the Amazon fire return interval will be shorter than the time required for canopy recovery, implying high risk of irreversible shifts to a fire-maintained degraded ecosystem state. Although resilience in canopy regeneration is evident in areas with low fire frequency, increased fire frequency could inhibit regeneration even in forests where grass is currently excluded, and push the Amazon forests towards a tipping point causing large areas of forest to transition to low tree cover state.

scholarly journals Alternative Vegetation States in Tropical Forests and Savannas: The Search for Consistent Signals in Diverse Remote Sensing Data

2019 ◽  
Vol 11 (7) ◽  
pp. 815 ◽  
Author(s):  
Sanath Kumar ◽  
Niall Hanan ◽  
Lara Prihodko ◽  
Julius Anchang ◽  
C. Ross ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Data Streams ◽  
Land Surface ◽  
Regional Scale ◽  
Remote Sensing Data ◽  
Sub Saharan Africa ◽  
Tree Cover ◽  
Alternative States ◽  
Sensing Data ◽  
Edaphic Conditions

Globally, the spatial distribution of vegetation is governed primarily by climatological factors (rainfall and temperature, seasonality, and inter-annual variability). The local distribution of vegetation, however, depends on local edaphic conditions (soils and topography) and disturbances (fire, herbivory, and anthropogenic activities). Abrupt spatial or temporal changes in vegetation distribution can occur if there are positive (i.e., amplifying) feedbacks favoring certain vegetation states under otherwise similar climatic and edaphic conditions. Previous studies in the tropical savannas of Africa and other continents using the MODerate Resolution Imaging Spectroradiometer (MODIS) vegetation continuous fields (VCF) satellite data product have focused on discontinuities in the distribution of tree cover at different rainfall levels, with bimodal distributions (e.g., concentrations of high and low tree cover) interpreted as alternative vegetation states. Such observed bimodalities over large spatial extents may not be evidence for alternate states, as they may include regions that have different edaphic conditions and disturbance histories. In this study, we conduct a systematic multi-scale analysis of diverse MODIS data streams to quantify the presence and spatial consistency of alternative vegetation states in Sub-Saharan Africa. The analysis is based on the premise that major discontinuities in vegetation structure should also manifest as consistent spatial patterns in a range of remote sensing data streams, including, for example, albedo and land surface temperature (LST). Our results confirm previous observations of bimodal and multimodal distributions of estimated tree cover in the MODIS VCF. However, strong disagreements in the location of multimodality between VCF and other data streams were observed at 1 km scale. Results suggest that the observed distribution of VCF over vast spatial extents are multimodal, not because of local-scale feedbacks and emergent bifurcations (the definition of alternative states), but likely because of other factors including regional scale differences in woody dynamics associated with edaphic, disturbance, and/or anthropogenic processes. These results suggest the need for more in-depth consideration of bifurcation mechanisms and thus the likely spatial and temporal scales at which alternative states driven by different positive feedback processes should manifest.

scholarly journals Evaluating Forest Cover and Fragmentation in Costa Rica with a Corrected Global Tree Cover Map

2020 ◽  
Vol 12 (19) ◽  
pp. 3226
Author(s):  
Daniel Cunningham ◽  
Paul Cunningham ◽  
Matthew E. Fagan
Keyword(s):  
Costa Rica ◽  
Forest Cover ◽  
Agricultural Land ◽  
Forest Area ◽  
Tree Cover ◽  
Agricultural Crop ◽  
Forest Change ◽  
Alos Palsar ◽  
Tropical Regions ◽  
The Impact

Global tree cover products face challenges in accurately predicting tree cover across biophysical gradients, such as precipitation or agricultural cover. To generate a natural forest cover map for Costa Rica, biases in tree cover estimation in the most widely used tree cover product (the Global Forest Change product (GFC) were quantified and corrected, and the impact of map biases on estimates of forest cover and fragmentation was examined. First, a forest reference dataset was developed to examine how the difference between reference and GFC-predicted tree cover estimates varied along gradients of precipitation and elevation, and nonlinear statistical models were fit to predict the bias. Next, an agricultural land cover map was generated by classifying Landsat and ALOS PalSAR imagery (overall accuracy of 97%) to allow removing six common agricultural crops from estimates of tree cover. Finally, the GFC product was corrected through an integrated process using the nonlinear predictions of precipitation and elevation biases and the agricultural crop map as inputs. The accuracy of tree cover prediction increased by ≈29% over the original global forest change product (the R2 rose from 0.416 to 0.538). Using an optimized 89% tree cover threshold to create a forest/nonforest map, we found that fragmentation declined and core forest area and connectivity increased in the corrected forest cover map, especially in dry tropical forests, protected areas, and designated habitat corridors. By contrast, the core forest area decreased locally where agricultural fields were removed from estimates of natural tree cover. This research demonstrates a simple, transferable methodology to correct for observed biases in the Global Forest Change product. The use of uncorrected tree cover products may markedly over- or underestimate forest cover and fragmentation, especially in tropical regions with low precipitation, significant topography, and/or perennial agricultural production.

scholarly journals New Forest Aboveground Biomass Maps of China Integrating Multiple Datasets

2021 ◽  
Vol 13 (15) ◽  
pp. 2892
Author(s):  
Zhongbing Chang ◽  
Sanaa Hobeichi ◽  
Ying-Ping Wang ◽  
Xuli Tang ◽  
Gab Abramowitz ◽  
...  
Keyword(s):  
Carbon Emissions ◽  
Aboveground Biomass ◽  
Regional Scale ◽  
Remote Sensing Data ◽  
Field Measurements ◽  
Random Forest Regression ◽  
Multiple Datasets ◽  
Optimal Weighting ◽  
Two Hybrid ◽  
Forest Aboveground Biomass

Mapping the spatial variation of forest aboveground biomass (AGB) at the national or regional scale is important for estimating carbon emissions and removals and contributing to global stocktake and balancing the carbon budget. Recently, several gridded forest AGB products have been produced for China by integrating remote sensing data and field measurements, yet significant discrepancies remain among these products in their estimated AGB carbon, varying from 5.04 to 9.81 Pg C. To reduce this uncertainty, here, we first compiled independent, high-quality field measurements of AGB using a systematic and consistent protocol across China from 2011 to 2015. We applied two different approaches, an optimal weighting technique (WT) and a random forest regression method (RF), to develop two observationally constrained hybrid forest AGB products in China by integrating five existing AGB products. The WT method uses a linear combination of the five existing AGB products with weightings that minimize biases with respect to the field measurements, and the RF method uses decision trees to predict a hybrid AGB map by minimizing the bias and variance with respect to the field measurements. The forest AGB stock in China was 7.73 Pg C for the WT estimates and 8.13 Pg C for the RF estimates. Evaluation with the field measurements showed that the two hybrid AGB products had a lower RMSE (29.6 and 24.3 Mg/ha) and bias (−4.6 and −3.8 Mg/ha) than all five participating AGB datasets. Our study demonstrated both the WT and RF methods can be used to harmonize existing AGB maps with field measurements to improve the spatial variability and reduce the uncertainty of carbon stocks. The new spatial AGB maps of China can be used to improve estimates of carbon emissions and removals at the national and subnational scales.

Combining static and dynamic environmental factors at various scales to predict shallow landsliding in South Tyrol, Italy – The Proslide project

2021 ◽  
Author(s):  
Robin Kohrs ◽  
 Lotte de Vugt ◽  
Thomas Zieher ◽  
Alice Crespi ◽  
Mattia Rossi ◽  
...  
Keyword(s):  
Regional Scale ◽  
Remote Sensing Data ◽  
Predisposing Factors ◽  
Physical Models ◽  
Data Driven ◽  
Catchment Scale ◽  
Heterogeneous Model ◽  
South Tyrol ◽  
Daily Precipitation Data ◽  
Spatio Temporal

<p>Shallow landslides in alpine environments can constitute a serious threat to the exposed elements. The spatio-temporal occurrence of such slope movements is controlled by a combination of predisposing factors (e.g. topography), preparatory factors (e.g. wet periods, snow melting) and landslide triggers (e.g. heavy precipitation events).  </p><p>For large study areas, landslide assessments frequently focus either on the static predisposing factors to estimate landslide susceptibility using data-driven procedures, or exclusively on the triggering events to derive empirical rainfall thresholds. For smaller areas, dynamic physical models can reasonably be parameterized to simultaneously account for static and dynamic landslide controls.  </p><p>The recently accepted Proslide project aims to develop and test methods with the potential to improve the predictability of landslides for the Italian province of South Tyrol. It is envisaged to account for a variety of innovative input data at multiple spatio-temporal scales. In this context, we seek to exploit remote sensing data for the spatio-temporal description of landslide controlling factors (e.g. precipitation RADAR; satellite soil moisture) and to develop models that allow an integration of heterogeneous model inputs using both, data-driven approaches (regional scale) and physically-based models (catchment scale). This contribution presents the core ideas and methodical framework behind the Proslide project and its very first results (e.g. relationships between landslide observations and gridded daily precipitation data at regional scale). </p>

scholarly journals Dynamical Analysis of a Viral Infection Model with Delays in Computer Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-15 ◽  
Author(s):  
Zizhen Zhang ◽  
Huizhong Yang
Keyword(s):  
Hopf Bifurcation ◽  
Propagation Model ◽  
Dynamical Analysis ◽  
Infection Model ◽  
Virus Propagation ◽  
Normal Form Theory ◽  
Center Manifold Theorem ◽  
Form Theory ◽  
Two Delays ◽  
The Stability

This paper is devoted to the study of an SIRS computer virus propagation model with two delays and multistate antivirus measures. We demonstrate that the system loses its stability and a Hopf bifurcation occurs when the delay passes through the corresponding critical value by choosing the possible combination of the two delays as the bifurcation parameter. Moreover, the direction of the Hopf bifurcation and the stability of the bifurcating periodic solutions are determined by means of the center manifold theorem and the normal form theory. Finally, some numerical simulations are performed to illustrate the obtained results.

scholarly journals Study on the Surveillance System of Water Stage Used the Resonator Pressure Transducer and Wireless Connectivity

2018 ◽  
Vol 228 ◽  
pp. 02001
Author(s):  
Bing Han ◽  
Qiang Fu
Keyword(s):  
Surveillance System ◽  
Pressure Transducer ◽  
Oil And Gas ◽  
Low Cost ◽  
Regional Scale ◽  
Time Data ◽  
Long Distance ◽  
Hydrogeological Parameters ◽  
Water Stage ◽  
Wireless Connectivity

For the sake of ameliorating the faultiness of low precision for conventional surveillance methods of water stage, and realize the goal of real time data collection, automated actions and long-distance conveying, we have designed a novel surveillance system of water stage with the resonator pressure transducer and wireless connectivity technologies. The surveillance system of water stage has come into service in a field experiment project of a certain oil and gas pipeline engineering. By analyzing and comparing the results of experiments, the system has the merits of high agility, reliability, instantaneity and accuracy, low cost, capacity of resisting disturbance, which making it ideal for use in unattended supervising of water stage for multi-spots observation based on regional scale. The surveillance system can well satisfy the actual demand of auto hydrogeological parameters monitoring for geotechnical engineering.

scholarly journals Use of Global Reanalysis Data in the Study of the Aridity Index in the Magdalena-Cauca Macro-Basin, Colombia

10.29007/92l9 ◽  
2018 ◽  
Author(s):  
Carolina Vega-Viviescas ◽  
David A. Zamora ◽  
Erasmo A. Rodríguez
Keyword(s):  
Southern Oscillation ◽  
Pearson Correlation ◽  
Regional Scale ◽  
Correlation Coefficients ◽  
Aridity Index ◽  
Remote Sensing Data ◽  
Reanalysis Data ◽  
In Situ Data ◽  
Global Reanalysis

The Magdalena-Cauca macro-basin (MCMB) in Colombia, by its tropical location, annually experiences the effects of movement of the Intertropical Convergence Zone, and it is highly affected by interannual macro-climatic phenomena, such as El Niño– Southern Oscillation (ENSO). With the aim of increasing the use of global reanalysis and remote sensing data for supporting water management decisions at the watershed scale and within the framework of the eartH2Observe research project, the aridity index (AI) was calculated with three different data sources. Precipitation products and AI results were compared with their corresponding in-situ national official data. The comparison shows high correlations between the AI derived from observed data and AI obtained from the reanalysis, with Pearson correlation coefficients above 0.8 for two of the products investigated. This shows the importance of using global reanalysis data in water availability studies on a regional scale for the MCMB and the potential of this information in others macrobasins in Colombia including the Orinoquia and Amazon regions, where in-situ data is scarce.

Sign in / Sign up

Export Citation Format

Share Document