Wildfires decrease the local-scale ecosystem spatial variability of Pinus canariensis forests during the first two decades post fire

The spatial variability (i.e. heterogeneity) of environmental variables determines a wide range of ecosystem features and plays a key role in regulating key ecosystem services. Wildfires are among the most significant natural disturbances that forests face, but our knowledge about their effect on ecosystem spatial variability is still limited. We used a 19-year fire chronosequence of natural, unmanaged Pinus canariensis C. Sm. ex DC forests to investigate how wildfires affect overall ecosystem spatial variability, as well as that of key faunal, plant and soil ecosystem attributes. The spatial variability of most soil variables and of the overall ecosystem tended to decrease after the fire and remain lower than the unburned plots even after 19 years. The spatial variability of plant-related variables, except for litter decomposition, as well as that of soil arthropods abundance, decreased more gradually than that of soil variables, reaching the lowest values in the plots burned 19 years before the survey. Our study provides evidence that wildfires are capable of significantly decreasing local-scale forest spatial heterogeneity through changes in the spatial variability of their different components, with likely yet unknown consequences for ecosystem functioning.

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Soil ecosystem functioning under climate change: plant species and community effects

Ecology ◽

10.1890/09-0135.1 ◽

2010 ◽

Vol 91 (3) ◽

pp. 767-781 ◽

Cited By ~ 206

Author(s):

Paul Kardol ◽

Melissa A. Cregger ◽

Courtney E. Campany ◽

Aimee T. Classen

Keyword(s):

Climate Change ◽

Plant Species ◽

Ecosystem Functioning ◽

Community Effects ◽

Soil Ecosystem

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Chemical composition of leaves of a mangrove tree (Sonneratia apetala Buch.-Ham.) and their correlation with some soil variables

Bangladesh Journal of Botany ◽

10.3329/bjb.v39i1.5528 ◽

1970 ◽

Vol 39 (1) ◽

pp. 61-69 ◽

Cited By ~ 8

Author(s):

Ashafaque Ahmed ◽

Mikael Ohlson ◽

Sirajul Hoque ◽

Md Golam Moula

Keyword(s):

Heavy Metals ◽

Chemical Composition ◽

Coastal Zone ◽

Organic Matter Content ◽

Matter Content ◽

Sonneratia Apetala ◽

Mangrove Tree ◽

Soil Variables ◽

Wide Range ◽

High Concentrations

Chemical composition of leaves of Sonneratia apetala Buch.-Ham. collected from three islands (chars) representing three hydrological regimes in a segment of the coastal zone of Bangladesh was studied. Their relations to some soil chemical and physical variables have also been investigated. The results showed that concentrations of B, C, Fe, Ga, Li, Mg, Mn, N, Na, P, Zn and Sr in leaves of S. apetala grown in different islands differed significantly. It was also revealed that some heavy metals, viz. Mn, Fe, Al, Sr and Ti showed wide range of concentrations. The leaves from one of the locations in Motherbunia island were characterized by exceptional high concentrations of heavy metals such as Al, As, Cu, Fe, Li, Ni, Pb that may be due to local contamination. Leaves sampled in the most seaward locations of the same island had highest concentrations of Ba, Ca, Cu, Mn and Na. High Mn concentration was found in the leaves of S. apetala of Motherbunia island. Correlations among soil and plant samples were generally very weak and organic matter content of soil did not appear to play a significant role in the nutrient supply of S. apetala. Key words: Coastal zone; tidal inundation; elemental concentration; Sonneratia apetala DOI: 10.3329/bjb.v39i1.5528Bangladesh J. Bot. 39(1): 61-69, 2010 (June)

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Spatial dynamics of soil moisture and temperature in a black spruce boreal chronosequence

Canadian Journal of Forest Research ◽

10.1139/x06-160 ◽

2006 ◽

Vol 36 (11) ◽

pp. 2794-2802 ◽

Cited By ~ 9

Author(s):

Ben Bond-Lamberty ◽

Karen M Brown ◽

Carol Goranson ◽

Stith T Gower

Keyword(s):

Soil Moisture ◽

Spatial Variability ◽

Sampling Design ◽

Black Spruce ◽

Structural Characteristics ◽

Spatial Dynamics ◽

Spherical Model ◽

Local Scale ◽

Spatial Dependencies ◽

The Mean

This study analyzed the spatial dependencies of soil moisture and temperature in a six-stand chronosequence of boreal black spruce (Picea mariana (Mill.) BSP) stands. Spatial variability of soil temperature (TSOIL) was evaluated twice during the growing season using four transects in each stand, employing a cyclic sampling design with measurements spaced 2–92 m apart. Soil moisture (θg) was measured on one occasion. A spherical model was used to analyze the geostatistical correlation structure; θg and TSOIL at the 7- and 21-year-old stands did not exhibit stable ranges or sills. The fits with stable ranges and sills modeled the spatial patterns in the older stands reasonably well, although unexplained variability was high. Calculated ranges varied from 3 to 150 m for these stands, lengths probably related to structural characteristics influential in local-scale energy transfer. Transect-to-transect variability was significant and typically 5%–15% of the mean for TSOIL and 10%–70% for θg. TSOIL and θg were negatively correlated for most stands and depths, with TSOIL dropping 0.5–0.9 °C for every 1% rise in θg. The results reported here provide initial data to assess the spatial variability of TSOIL and θg in a variety of boreal forest stand ages.

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Geographically weighted regression modelling of the spatial association between malaria cases and environmental factors in Cameroon.

10.21203/rs.2.13021/v3 ◽

2020 ◽

Author(s):

Marlvin Anemey Tewara ◽

Liu Yunxia ◽

Weiqiang Ling ◽

Binang Helen Barong ◽

Prisca Ngetemalah Mbah-Fongkimeh ◽

...

Keyword(s):

Environmental Factors ◽

Spatial Variability ◽

Geographically Weighted Regression ◽

Environmental Variables ◽

Vegetation Index ◽

Spatial Association ◽

Ordinary Least Squares ◽

Variable Coefficients ◽

Weighted Regression ◽

Gwr Model

Abstract Background: Studies have illustrated the association of malaria cases with environmental factors in Cameroon but limited in addressing how these factors vary in space for timely public health interventions. Thus, we want to find the spatial variability between malaria hotspot cases and environmental predictors using Geographically weighted regression (GWR) spatial modelling technique.Methods: The global Ordinary least squares (OLS) in the modelling spatial relationships tool in ArcGIS 10.3. was used to select candidate explanatory environmental variables for a properly specified GWR model. The local GWR model used the global OLS candidate variables to examine, predict and explore the spatial variability between environmental factors and malaria hotspot cases generated from Getis-Ord Gi* statistical analysis. Results: The OLS candidate environmental variable coefficients were statistically significant (adjusted R2 = 22.3% and p < 0.01) for a properly specified GWR model. The GWR model identified a strong spatial association between malaria cases and rainfall, vegetation index, population density, and drought episodes in most hotspot areas and a weak correlation with aridity and proximity to water with an overall model performance of 0.243 (adjusted R2= 24.3%).Conclusion: The generated GWR maps suggest that for policymakers to eliminate malaria in Cameroon, there should be the creation of malaria outreach programs and further investigations in areas where the environmental variables showed strong spatial associations with malaria hotspot cases.

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Deciphering Main Climate and Edaphic Components Driving Oat Adaptation to Mediterranean Environments

Frontiers in Plant Science ◽

10.3389/fpls.2021.780562 ◽

2021 ◽

Vol 12 ◽

Author(s):

Francisco J. Canales ◽

Gracia Montilla-Bascón ◽

Luis M. Gallego-Sánchez ◽

Fernando Flores ◽

Nicolas Rispail ◽

...

Keyword(s):

Environmental Variables ◽

Agronomic Traits ◽

Interaction Analysis ◽

Variation Partitioning ◽

Environment Interaction ◽

Edaphic Factors ◽

Mediterranean Environments ◽

Wide Range ◽

Northern Regions ◽

Edaphic Variables

Oat, Avena sativa, is an important crop traditionally grown in cool-temperate regions. However, its cultivated area in the Mediterranean rim steadily increased during the last 20 years due to its good adaptation to a wide range of soils. Nevertheless, under Mediterranean cultivation conditions, oats have to face high temperatures and drought episodes that reduce its yield as compared with northern regions. Therefore, oat crop needs to be improved for adaptation to Mediterranean environments. In this work, we investigated the influence of climatic and edaphic variables on a collection of 709 Mediterranean landraces and cultivars growing under Mediterranean conditions. We performed genotype–environment interaction analysis using heritability-adjusted genotype plus genotype–environment biplot analyses to determine the best performing accessions. Further, their local adaptation to different environmental variables and the partial contribution of climate and edaphic factors to the different agronomic traits was determined through canonical correspondence, redundancy analysis, and variation partitioning. Here, we show that northern bred elite cultivars were not among the best performing accessions in Mediterranean environments, with several landraces outyielding these. While all the best performing cultivars had early flowering, this was not the case for all the best performing landraces, which showed different patterns of adaption to Mediterranean agroclimatic conditions. Thus, higher yielding landraces showed adaptation to moderate to low levels of rain during pre- and post-flowering periods and moderate to high temperature and radiation during post-flowering period. This analysis also highlights landraces adapted to more extreme environmental conditions. The study allowed the selection of oat genotypes adapted to different climate and edaphic factors, reducing undesired effect of environmental variables on agronomic traits and highlights the usefulness of variation partitioning for selecting genotypes adapted to specific climate and edaphic conditions.

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NUKLEUS - User-relevant and applicable kilometer-scale climate information for Germany

10.5194/egusphere-egu21-12137 ◽

2021 ◽

Author(s):

Kevin Sieck ◽

Bente Tiedje ◽

Hendrik Feldmann ◽

Joaquim Pinto

Keyword(s):

Climate Models ◽

Local Scale ◽

Easy Access ◽

Climate Information ◽

Post Processing ◽

Last Mile ◽

Wide Range ◽

Impact Modelling ◽

The Impact ◽

Impact Models

<p>Given the current developments in climate science it becomes more a more feasible to provide climate information at the kilometer-scale from convection-permitting climate simulations. This progress will enable many users to directly feed high-resolution climate information into their impact-models for climate impact studies at the local scale. Examples include urban heat stress at street level or the design of drainage systems for future precipitation extremes. Within the RegIKlim (Regional information for action on climate change) consortium, the NUKLEUS (Actionable local climate information for Germany) project will not only provide climate information at the local scale, but also to co-develop interfaces between climate and impact models, in order to fulfil the needs of the impact modelling community as good as possible. Within the RegIKlim consortium, the impact modelling community is organised in six &#8220;model regions&#8221; across Germany, which cover a wide range of geographical and socio-economic conditions.</p><p>For the NUKLEUS project, the baseline will be the latest generation of EURO-CORDEX downscaled CMIP6 simulations, which will be further refined to roughly 3&#160;km horizontal resolution and 30-year time-slices for Germany with convection-permitting climate models (ICON CLM, COSMO-CLM, REMO-NH) and statistical-dynamical downscaling approaches. A detailed analysis on the performance of the multi-model mini-ensemble is planned to assess the quality of the provided data. At the interface to the users, we will follow three different approaches to provide usable climate information at the kilometer-scale. One is to provide easy-access to data and post-processing opportunities using the FREVA system. FREVA offers various access-levels from shell to web-based, which serves different levels of user-expertise. In addition, it provides a transparent way of post-processing data by workflow sharing mechanisms. The second one is to develop appropriate additional downscaling methods for the &#8220;last mile&#8221; where needed. For this &#8220;last mile&#8221;, we will apply dynamical and statistical methods such as urban climate models and/or weather generators. With the third approach we explicitly aim at integrating a collected user-feedback into the regional modelling systems used within NUKLEUS. Specifically, we intend to identify and incorporate data processing that is best done during the simulation permanently into the models. Examples are wind speeds at rotor heights of windmills or high frequency precipitation sums. NUKLEUS is a contribution to the German research program RegIKlim funded by the Federal Ministry of Education and Research (BMBF).</p>

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Climate Defined but Not Soil-restricted: The Distribution of a Neotropical tree through Space and Time

10.21203/rs.3.rs-333060/v1 ◽

2021 ◽

Author(s):

Facundo Alvarez ◽

Paulo S Morandi ◽

Ben Hur Marimon-Junior ◽

Reginal Exavier ◽

Igor Araújo ◽

...

Keyword(s):

Spatial Distribution ◽

Environmental Variables ◽

Distribution Patterns ◽

Distribution Models ◽

Climatic Fluctuations ◽

Space And Time ◽

Predictive Variables ◽

Soil Variables ◽

Neotropical Tree ◽

Edaphic Variables

Abstract AimsBrosimum rubescens, a tree species with a Neotropical distribution, can achieve local monodominance in Southern Amazonia forests. Understanding how and why this species varies across space and time is important because the monodominance of some species alters ecosystems complexity. Here we evaluate the fundamental ecological niche of B. rubescens by species distribution models (SDM), combining predictive environmental variables with occurrence points. We specifically aim to 1) determine how the spatial distribution patterns of B. rubescens vary with different environmental predictive variables, and 2) evaluate the temporal and spatial persistence of B. rubescens in the Neotropics. MethodsTo generate the SDMs, the predictive environmental variables were incorporated as main components of climatic, hydric and soil variables. ResultsAll algorithms show higher performance in spatial predictions for hydric variables and for the combination of climatic, hydric and edaphic variables. We identified that the potential niches of B. rubescens seem to be defined by climatic fluctuations, with the edaphic conditions being predictive variables that are not restrictive of their presence on the evaluated spatial scale. From the LMG (Last Glacial Maximum) to the present, the species seems to have increased its spatial amplitude; however, from the present to the future, predictions suggest that B. rubescens will experience a considerable loss of its range. ConclusionsOur findings show the independent and combined effects of different environmental variables, allowing us to identify which limit or facilitate the spatial distribution of B. rubescens. We corroborate the spatial persistence and geographical fidelity of the species' spatial patterns over time.

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