Ecological restoration in the Central Monte Desert: Plant species perfomance an d biological soil crust recovery following eight years of revegetation
; Aranibar, Julieta Nelida ; Medero, Alejandra Veronica ; Giordano, Carla Valeria Otros responsables
Fecha
Publicador:
Consejo Nacional de Investigaciones Científicas y Técnicas
Fecha de depósito:
2/09/2026
Fecha de creación:
3/2026
Clasificación temática
Palabras clave
Resumen
Study site The research was conducted at the Telteca Natural Reserve (32° 24' 44"S 67° 54' 52"W), located in northeastern Mendoza Province, Argentina. The climate is arid with a mean annual temperature of 18 ºC (1991–2020), reaching absolute maximums of 48 ºC in summer and minimums of -10 ºC in winter (Meglioli et al. 2017). Precipitation averages 160 mm annually (1972–2014), occurring in pulses between October and March (spring-summer) (Cravero et al 2017; Morello et al. 2018). The landscape is a system of dunes and valleys that host distinct landscape units and plant communities. Open forests of Neltuma flexuosa inhabit inter-dune valleys, accessing the water table at depths of 6-15 m (Giordano et al. 2011; Jobbágy et al. 2011). In contrast, dunes are dominated by xerophytic shrubs and grasses with no groundwater access, while landscape depressions are dominated by phreatophytic species such as Geoffrea decorticans and N. alpataco (Álvarez et al. 2006).
Métodos
Plant measurements
Basal stem diameter: We recorded the diameter at the stem base (mm) with a digital caliper. We registered this variable through time: at transplanting (October 2018), at the end of the first growing season (October 2019; referred to as 1st year post-transplanting), in February 2023 (5th year) and March 2026 (8th year). Over time, stems became non-circular in cross-section, in which case we measured the largest diameter.
As the plants grew, canopy area and cover were measured in March 2023 (year 5th) and March 2026 (year 8th). Data from year 5th were published in Peña Cervera et al. (2026); however, canopy size data are presented again here to allow for clearer comparisons.
Canopy area: Canopy area (m2) was calculated from digital photographs of each plant taken from the zenith (Fig. S1a). To do this, we placed a black cloth on the ground (to generate contrast with the branches and leaves) and used a gazebo to shade the plant, thereby eliminating reflections caused by direct sunlight on the cloth. Images were captured with a Samsung S23 Ultra cell phone mounted on a tripod with a selfie stick extension, positioned at a height of 1.60 to 2.00 m and centred over the base of the plant; the zenith angle was verified using a level on the device. Photographs were taken with the 50 MP camera at a resolution of 8160 × 6120 pixels, using a 6.3 mm lens (f/1.7) with flash enabled, and saved in RAW format. A ruler was placed next to each plant to provide a scale reference. For plants whose canopy exceeded the camera's field of view, we took multiple overlapping photographs and stitched together using the Photomerge function in Adobe Photoshop 2026 (version 27.10.0, Adobe Inc., San Jose, CA, USA) to reconstruct the entire plant at the original scale. Canopy size was then calculated in ImageJ software (version 1.54f, free software, National Institutes of Health, Maryland, USA) as the area of the polygon formed by connecting the tips of the outermost branches of each plant (Fig. S1b).
Canopy cover: We quantified branch and leaf cover (%) within two concentric zones surrounding the base of each plant's stem. The zone closest to the stem was defined as a 50 cm diameter circle (proximal area; Fig. S1c), while the zone farthest from the stem was defined as a ring extending 25 cm beyond the outer edge of the proximal area (distal area; Fig. S1d). Using the zenithal photographs taken for canopy size measurements, we isolated each plant and removed the background with ImageJ software (version 1.54f, free software, National Institutes of Health, Maryland, USA). Images were first converted to 8-bit grayscale and then binarized by adjusting the threshold to distinguish the plant canopy from the background, with canopy pixels represented in white and the background in black. The spatial scale was calibrated using the reference ruler included in each photograph. Then, the project canopy area was quantified using the Measure function. Finally, the percentage cover for each area, proximal and distal, was calculated as the proportion of each predefined area occupied by the plant canopy area.
Plant survival: Plant survival was calculated as the number of live plants recorded in the plot in March 2026 (8th year) relative to the initial total of plants left in the plot after the first-year thinning (12 plants per species, 48 plants in total).
Canopy dieback: We determined the canopy dieback (%) by visually estimating the proportion of dry branches (gray, brown, brittle, and easily broken when bent) relative to the total number of branches on the plant.
Métodos
Microenvironment beneath plant canopies
We measured air temperature (oC) and relative humidity (RH, %) HOBO Data Logging Solutions Onset MX2301), near-surface soil temperature (at approximately 2 cm depth; TFA Dostmann 19.1006), photosynthetically active radiation [PAR: 400-700 nm (µmol m-2 s-1); Li-Cor-190SB quantum sensor; Li-Cor, Lincoln, USA], and ultraviolet-B radiation [UV-B: 280-315 nm (W m-2); Skye SKU 430 hemispherical sensor connected to a SpectroSense2; Skye Instruments Ltd, Powys, UK] beneath plant canopies and in adjacent exposed soil areas. Measurements beneath canopies were taken with sensors placed 25 cm apart from the base of the stem, on the southern side. For PAR measurements, we used a 1m sensor bar; for UV-B, we took three measurements per point with a point sensor and averaged them, using the mean as the final value. Paired under-canopy/open-area measurements were taken concurrently over time to allow for reliable comparisons. Measurements were conducted over a 2 hour-period around local solar noon at the end of summer (March 2026), as this period is most relevant for biological soil crusts (biocrusts) growth, which occurs during periods away from the extreme summer conditions (when surface soil temperature can reach 70°C, and the air temperature may exceed 50°C; Data from meteorological station at the Park Ranger area El Pichón and personal measurements).
Métodos
Study of biocrust
Biocrust occurrence beneath the canopies of transplanted plants within the experimental plot: Incipient biocrusts dominated by cyanobacteria in their early stages of development (LOD 1 according to Belnap et al. 2008) are characterized by thin, colorless layers that, when removed with a spade, reveal a cohesive structure and filaments at their base. We assessed the presence of these visual features within the experimental plot (Fig. S2), beneath the canopy of all plants (within a 50-cm-diameter circle around the stem base) and at adjacent bare-soil locations next to each plant. All samples showing these characteristics were collected, placed in Petri dishes for transport, and subsequently cultured in the biogeochemistry laboratory at Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales (IANIGLA-CONICET) in Mendoza city, Argentina (32º 53` 39.2424``S; 68º 52` 30.1908`W).
Once in the laboratory, biocrust samples were placed 10 cm below four 18-W full-spectrum T8 LED tubes, 230 V ~ 50 Hz (TBCin LT8-1218-W-ESGR). Samples were maintained under a 12 h light:12 h dark photoperiod at 25 °C, with a PAR of 200 µmol m⁻² s⁻¹ and were periodically moistened with sterile distilled water to keep them moist without saturation. We conducted periodic observations using a Nikon SMZ645 stereomicroscope at 10× magnification and an Olympus CX31 light microscope at 40–400× magnification. Photographs were taken using a Motic X WiFi camera coupled to the light microscope. After 60 days, visible filaments and moss plants were observed, allowing us to distinguish between organism types. We recorded the presence of diatoms, cyanobacteria, microalgae, mosses, and lichens. Cyanobacteria were categorized based on morphological structures such as the presence and size of heterocysts, sheets, trichomes, ramifications, and terminal cells. Although molecular studies are necessary for taxonomic identification, we mention probable genus, based on morphological features and previous reports in the same region (Corvalán Videla et al., 2018). Mosses were identified using the size, shape and characteristics of the leaves and the plant, because no sporophytes were present (Corvalán Videla, 2019). Because the biocrusts found were incipient, and organisms did not have all structures commonly used for identification, such as sporophytes and spores, we report the genus, based on the characteristics we could observe.
Biocrust occurrence in the disturbed area adjacent to the experimental plot, and in a control less-disturbed area: We recorded the occurrence of biocrusts in the disturbed area surrounding the experimental plot to detect the presence of an inoculum source toward the interior of the plot (which was established in a sector particularly devoid of vegetation, in accordance with the objective of evaluating the growth of transplanted plants with minimal interference from other large plants already present in the area). We also assessed the occurrence of biocrusts at the corresponding control site, located 2 km from the outpost (Biruk et al. 2025). At each site (disturbed and control) we established three transects. Along each transect, we placed 25 0.5 x 0.5 m grids at 2 m intervals. Each grid covered an area of 2.5 m² and was subdivided into 25 cells of 1 × 1 cm (5 × 5), resulting in a total of 625 cells evaluated per transect. Within each cell, we recorded the presence of biocrust types, allowing more than one category to be recorded within the same cell. Biocrusts were further classified according to the dominant morphological group as incipient cyanobacterial, advanced cyanobacterial, lichen or moss biocrusts (Belnap 2003; Ferrenberg et al. 2017). Lichens were identified based on the thallus, growth form, and reproductive structures, such as apothecia and isidia (Nash et al., 2002). Frequency of occurrence per transect was calculated as the proportion of cells in which the variable was present relative to the total number of cells evaluated per transect (n = 625).
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