arid ecosystem
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2022 ◽  
Vol 49 ◽  
pp. 101730
Author(s):  
Wilgince Apollon ◽  
Luis L. Valera-Montero ◽  
Catarino Perales-Segovia ◽  
Víctor A. Maldonado-Ruelas ◽  
Raúl A. Ortiz-Medina ◽  
...  

2022 ◽  
Vol 170 ◽  
pp. 104296
Author(s):  
Wenjing Li ◽  
Yan Li ◽  
Jie Lv ◽  
Xuemin He ◽  
Jinlong Wang ◽  
...  

Ecosistemas ◽  
2021 ◽  
Vol 30 (3) ◽  
pp. 2236
Author(s):  
Yolanda Canton Castilla ◽  
Beatriz Roncero-Ramos ◽  
Raul Román Fernández ◽  
Emilio Rodríguez Caballero ◽  
Sonia Chamizo de la Piedra

Las biocostras son comunidades de organismos autótrofos y heterótrofos que viven en la superficie del 12% de los suelos de la Tierra, donde actúan como ingenieras del ecosistema. Son muy sensibles al cambio climático y a las alteraciones ocasionadas por diferentes actividades antrópicas. En este trabajo, revisamos los impactos de ambos tipos de perturbaciones, que afectan negativamente a los ciclos biogeoquímicos, al balance de agua y al de energía, aceleran los procesos erosivos y la emisión de polvo y reducen la biodiversidad disminuyendo la capacidad de los ecosistemas para proveer servicios. Exploramos la capacidad de estas comunidades para recuperarse naturalmente, que, en general, requiere mucho tiempo el establecimiento de las comunidades de etapas sucesionales más tardías. Por ello, han surgido nuevas biotecnologías para acelerar su restauración, basadas en la inoculación de organismos formadores de biocostra. Se revisan los principales resultados de dos grupos de estrategias atendiendo al origen de los propágulos de biocostras: a) la translocación de fragmentos de biocostras de un área donante en favor de una degradada. Se recomienda para alteraciones planificadas en las que se use la biocostra existente antes de la alteración; b) cultivo a gran escala de organismos formadores de biocostra (cianobacterias, líquenes, musgos o la comunidad completa) en laboratorio o vivero para ser inoculados, posteriormente, en áreas degradadas. Finalmente, se identifican los retos futuros para maximizar el éxito de la restauración y conservación de las biocostras.


Land ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 5
Author(s):  
Fernando Santos-Francés ◽  
Antonio Martínez-Graña ◽  
Carmelo Ávila-Zarza ◽  
Marco Criado ◽  
Yolanda Sánchez-Sánchez

In the last two decades, as the importance of soil has been recognized as a key component of any ecosystem, there has been an increased global demand to establish criteria for determining soil quality and to develop quantitative indices that can be used to classify and compare that quality in different places. The preliminary estimation of the attributes involved in soil quality was made taking into account the opinion of the experts and our own experience in a semi-arid ecosystem. In this study, 16 soil properties have been selected as potential indicators of soil quality, in a region between Campo de Montiel and Sierra de Alcaraz (Spain): sand and clay percentage, pH, electrical conductivity (EC), soil organic carbon (OC), extractables bases of change (Na, K, Ca and Mg), cationic exchange capacity (CEC), carbonate calcium equivalent (CCE), bulk density (BD), water retention at 33 kPa field capacity and 1500 kPa permanent wither point (GWC33 kPa and GWC1500 kPa), coefficient of linear extensibility (COLE) and factor of soil erodibility (K). The main objective has been to develop an adequate index to characterize the quality of the soils in a semi-arid Mediterranean ecosystem. The preliminary estimation of the attributes involved in soil quality was made considering the opinion of the experts and our own experience in semi-arid ecosystems. Two indicator selection approaches have been used to develop the Soil Quality Index (SQI) (total data set -TDS- and minimum data set -MDS-), scoring functions (linear -L- and nonlinear -NL-) and methods (additive -A-, additive weighted -W- and Nemoro -N-. The quality indices have been calculated, considering the properties of the soil control section (between 0 and 100 cm depth), using 185 samples, belonging to horizons A, B and C of 51 soil profiles. The results have shown that the election of the soil properties, both of the topsoil and subsoil, is an important help in establishing a good relationship between quality, soil functions and agricultural management. The Kriging method has been used to determinate the spatial distribution of the soil quality grades. The indices that best reflect the state of soil quality are the TDS-L-W and TDS-L-A should go as sub-indices, as they are the most accurate indices and provide the most consistent results. These indices are especially indicated when carrying out detailed or semi-detailed studies. However, the MDS-L-W and MDS-L-A should go as sub-indices, which use only a limited number of indicators, are best for large-scale studies. The indicators with the greatest influence on soil quality for different land uses and those developed on different rocks, using linear scoring functions, are the following: (Clay), (GWC1500 kPa) and (Ca). These results can also be expressed as follows: the best soils in this region are deep soils, with a clay texture, with high water retention and a neutral or slightly basic pH. However, the indicators with the greatest influence on soil quality, using nonlinear scoring functions, are: (OC Stock), (Ca) and (CaCO3). In other words, the most important indicator is the organic carbon content, which is not logical in the case of a region in which the soils have an excessively low SOC content (0.86%).


Ecosphere ◽  
2021 ◽  
Vol 12 (12) ◽  
Author(s):  
Reham F. El‐Barougy ◽  
Mohammed A. Dakhil ◽  
Ibrahim A. ElGamal ◽  
Sarah M. Gray ◽  
Abdel‐Hamid A. Khedr ◽  
...  

2021 ◽  
Vol 2 ◽  
Author(s):  
Nayani Ilangakoon ◽  
Nancy F. Glenn ◽  
Fabian D. Schneider ◽  
Hamid Dashti ◽  
Steven Hancock ◽  
...  

Assessing functional diversity and its abiotic controls at continuous spatial scales are crucial to understanding changes in ecosystem processes and services. Semi-arid ecosystems cover large portions of the global terrestrial surface and provide carbon cycling, habitat, and biodiversity, among other important ecosystem processes and services. Yet, the spatial trends and patterns of functional diversity in semi-arid ecosystems and their abiotic controls are unclear. The objectives of this study are two-fold. We evaluated the spatial pattern of functional diversity as estimated from small footprint airborne lidar (ALS) with respect to abiotic controls and fire in a semi-arid ecosystem. Secondly, we used our results to understand the capabilities of large footprint spaceborne lidar (GEDI) for future applications to semi-arid ecosystems. Overall, our findings revealed that functional diversity in this ecosystem is mainly governed by elevation, soil, and water availability. In burned areas, the ALS data show a trend of functional recovery with time since fire. With 16 months of data (April 2019-August 2020), GEDI predicted functional traits showed a moderate correlation (r = 41–61%) with the ALS predicted traits except for the plant area index (PAI) (r = 11%) of low height vegetation (<5 m). We found that the number of GEDI footprints relative to the size of the fire-disturbed areas (=< 2 km2) limited the ability to estimate the full effects of fire disturbance. However, the consistency of diversity trends between ALS and GEDI across our study area demonstrates GEDI’s potential of capturing functional diversity in similar semi-arid ecosystems. The capability of spaceborne lidar to map trends and patterns of functional diversity in this semi-arid ecosystem demonstrates its exciting potential to identify critical biophysical and ecological shifts. Furthermore, opportunities to fuse GEDI with complementary spaceborne data such as ICESat-2 or the upcoming NASA-ISRO Synthetic Aperture Radar (NISAR), and fine scale airborne data will allow us to fill gaps across space and time. For the first time, we have the potential to monitor carbon cycle dynamics, habitats and biodiversity across the globe in semi-arid ecosystems at fine vertical scales.


Author(s):  
Surendra Poonia ◽  
N.K. Jat ◽  
Priyabrata Santra ◽  
A.K. Singh ◽  
Dilip Jain ◽  
...  

2021 ◽  
pp. 235-248
Author(s):  
Dipak Kumar Gupta ◽  
Chandan Kumar Gupta ◽  
Kamla K. Choudhary ◽  
A Keerthika ◽  
M.B. Noor mohamed ◽  
...  

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