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            <gco:CharacterString>Monitoring of microclimates in Mediterranean mountain ecosystems of Sierra Nevada using dataloggers</gco:CharacterString>
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        <gco:CharacterString>The complex orography of the mountains generates a very heterogeneous mosaic of environmental conditions, which can help conserve the biodiversity and services provisioning of their ecosystems. Characterizing these microenvironments and linking them to the ecophysiological, behavioral and demographic responses of organisms is key to understanding their persistence capacity and their possible adaptation to new scenarios. In this monitoring, we present an instrumental proposal that we are implementing to characterize microclimates in the Sierra Nevada mountain ecosystems (SE Spain). This monitoring is based on sensor networks (dataloggers) installed in different habitats (oak forests, scrublands and pine plantations) and microhabitats (under leaf litter, under scrub, under stone or on bare soil). 

The sensors measure the following variables every 30 minutes: 
  -	Air temperature and air relative humidity (80-100 cm)
  -	Soil moisture and soil temperature (40 cm)
  -	Ground surface temperature (on bare soil)
  -	Ground surface temperature (under leaf litter, under scrub or under stone)

The technical characteristics of the “LW-GD-DL-001” dataloggers are:
  -	Communications capabilities: NB-IoT, LTE-M, GPRS, Bluetooth and LoRa.
  -	MCU and Communications: GPS/GLONASS/BeiDou/Galileo/QZSS.
  -	Supported sensor protocols: ADC, SDI-12, RS-485, RS-232, RS-422, I2C, Digital Counter.
  -	Inputs: 2 or 4 ADC with adjustable gain (by current or voltage) and 2 digital inputs.
  -	Storage: Micro SD Card with up to 64GB.
  -	Power: Solar charger, 13V to 60V Power Supply, 7.4V 5000mAh Battery.
  -	Working range: Temperature: -25°C ~ 85°C. Humidity: 5% ~ 95% (non-condensing).
  -	The dataloggers are fully managed from LifeWatch IoT Platform.

This work is part of the project “Thematic Center on Mountain Ecosystem &amp; Remote sensing, Deep learning-AI e-Services University of Granada-Sierra Nevada” (LifeWatch-2019-10-UGR-04), which has been co-funded by the Ministry of Science and Innovation through the ERDF funds from the Spanish Pluriregional Operational Program 2014-2020 (POPE), LifeWatch-ERIC action line.</gco:CharacterString>
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            <gco:CharacterString>Francisco Manuel Sánchez Cano</gco:CharacterString>
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