Challenges to Implementing Environmental-DNA Monitoring in Namibia

By identifying fragments of DNA in the environment, eDNA approaches present a promising tool for monitoring biodiversity in a cost-effective way. This is particularly pertinent for countries where traditional morphological monitoring has been sparse. The first step to realising the potential of eDNA is to develop methodologies that are adapted to local conditions. Here, we test field and laboratory eDNA protocols (aqueous and sediment samples) in a range of semi-arid ecosystems in Namibia. We successfully gathered eDNA data on a broad suite of organisms at multiple trophic levels (including algae, invertebrates and bacteria) but identified two key challenges to the implementation of eDNA methods in the region: 1) high turbidity requires a tailored sampling technique and 2) identification of taxa by eDNA methods is currently constrained by a lack of reference data. We hope this work will guide the deployment of eDNA biomonitoring in the arid ecosystems of Namibia and neighbouring countries.

Climate modulates grazing effects on primary productivity of arid ecosystems in Argentina

La introducción de fuentes de agua artificiales para uso ganadero en ecosistemas donde el agua ha estado ausente durante su evolución ha provocado cambios en la vegetación. Se ha demostrado que existe una atenuación radial del impacto del pastoreo con la distancia a la fuente de agua, favoreciendo la formación de piósferas. En Argentina, no existen estudios que evalúen cómo actúa el clima como modulador de los efectos del pastoreo en piósferas a lo largo de gradientes ambientales. El objetivo de este estudio fue evaluar y analizar el rol que juega el clima como modulador de los efectos que el pastoreo induce a escala local. Esto permitiría comprender como actúa el clima sobre los efectos del pastoreo. Para ello se seleccionaron 77 piósferas a lo largo de un gradiente climático y se analizó la variabilidad espacial de los valores de NDVI (Índice de Vegetación de la Diferencia Normalizada) en el gradiente de pastoreo y su relación con la precipitación media anual y la temperatura media anual. Se observaron dos patrones diferentes de respuesta del NDVI. El patrón 1 presentó un aumento del NDVI con la distancia al punto de agua, mientras que el patrón 2 manifestó un comportamiento inverso. Las piósferas de los patrones 1 y 2 se ubicaron por encima y por debajo de los 280 mm de precipitación anual y de los 14.5 °C de temperatura media anual, respectivamente. Estos resultados sugieren que existe un comportamiento diferencial de la vegetación frente al pastoreo que estaría modulado por variables climáticas.

Controlling factors of ecosystem and soil respiration in a xeric shrubland in the Chihuahuan Desert, Mexico

In the terrestrial carbon cycle is very relevant to identify the influence of soil in the CO2 released to the atmosphere, which is linked to multiple biotic and abiotic drivers. Arid ecosystems dominate the trend and interannual variability of the land CO2 sink. This pattern is mainly controlled by temperature, precipitation, and shortwave radiation. Thus, these environments are characterized by a wide variability of water availability, which causes the CO2 efflux to be highly variable in time, challenging our model capacities. This study aims to understand the ecosystem CO2 fluxes and their controlling mechanisms from the Chihuahuan Desert in Northeast Mexico. We explore the average contribution of the Rsoil (1.30 mmol m-2 s‑1) to Reco (1.76 mmol m-2 s‑1), while identifying the controlling mechanisms of both on an annual scale. The structural equation model constructed showed a good f it for the data, explaining 50% and 93% of the annual variance of Rsoil and Reco, respectively. According to this model, Rsoil was mainly controlled by the air temperature, and Reco by soil water content. Unexpectedly, vapor pressure def icit was the most weight variable with a direct negative effect on Reco, supporting the idea that the vegetation component has a crucial role in the CO2 efflux of this ecosystem. This study highlights the importance of include multiple factors in the models of the C cycle.

From isolation to application: a case study of arbuscular mycorrhizal fungi of the Arabian Peninsula

The vegetation in the Arabian Peninsula experiences drought, heat, soil salinity, and low fertility, mainly due to low phosphorus (P) availability. The beneficial mycorrhizal symbiosis between plants and arbuscular mycorrhizal fungi (AMF) is a key factor supporting plant growth under such environmental conditions. Therefore, AMF strains isolated from these soils might be useful as biotechnological tools for agriculture and revegetation practices in the region. Here we present a pioneering program to isolate, identify, and apply AMF isolated from rhizosphere soils of agricultural and natural habitats, namely date palm plantations and five native desert plants, respectively in the Southern Arabian Peninsula. We established taxonomically unique AMF species as single-spore cultures as part of an expanding collection of AMF strains adapted to arid ecosystems. Preliminary experiments were conducted to evaluate the abilities of these AMF strains to promote seedling growth of a main crop Phoenix dactylifera L. and a common plant Prosopis cineraria L. (Druce) in the Arabian Peninsula. The results showed that inoculation with certain AMF species enhanced the growth of both plants, highlighting the potential of these fungi as part of sustainable land use practices in this region.

Origin of Intra-annual Density Fluctuations in a Semi-arid Area of Northwestern China

Intra-annual density fluctuation (IADF) is a structural modification of the tree ring in response to fluctuations in the weather. The expected changes in monsoon flow would lead to heterogeneous moisture conditions during the growing season and increase the occurrence of IADF in trees of the arid ecosystems of continental Asia. To reveal the timings and physiological mechanisms behind IADF formation, we monitored cambial activity and wood formation in Chinese pine (Pinus tabuliformis) during 2017–2019 at three sites in semi-arid China. We compared the dynamics of xylem formation under a drought event, testing the hypothesis that drought affects the process of cell enlargement and thus induces the production of IADF. Wood microcores collected weekly from April to October were used for anatomical analyses to estimate the timings of cambial activity, and the phases of enlargement, wall thickening, and lignification of the xylem. The first cells started enlargement from late April to early May. The last latewood cells completed differentiation in mid-September. Trees produced IADF in 2018. During that year, a drought in June limited cell production in the cambium, only 36% of the xylem cells being formed in IADF trees, compared to 68% in normal tree rings. IADF cells enlarged under drought in early July and started wall thickening during the rainfall events of late July. The drought restricted cell enlargement and affected wall thickening, resulting in narrow cells with wide walls. Cambium and cell enlargement recovered from the abundant rainfall, producing a new layer with large earlywood tracheids. IADF is a specific adaptation of trees to cope with water deficit events occurring during xylem formation. Our findings confirmed the hypothesis that the June-July drought induces latewood-like IADFs by limiting the process of cell enlargement in the xylem. Our finding suggests a higher occurrence of IADF in trees of arid and semi-arid climates of continental Asia if the changes to monsoon flows result in more frequent drought events during the earlywood formation in June.

Airborne and Spaceborne Lidar Reveal Trends and Patterns of Functional Diversity in a Semi-Arid Ecosystem

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.

Diversification and post-glacial range expansion of giant North American camel spiders in genus Eremocosta (Solifugae: Eremobatidae)

Species of camel spiders in the family Eremobatidae are an important component of arthropod communities in arid ecosystems throughout North America. Recently, research demonstrated that the evolutionary history and biogeography of the family are poorly understood. Herein we explore the biogeographic history of this group of arachnids using genome-wide single nucleotide polymorphism (SNP) data, morphology, and distribution modelling to study the eremobatid genus Eremocosta, which contains exceptionally large species distributed throughout North American deserts. Relationships among sampled species were resolved with strong support and they appear to have diversified within distinct desert regions along an east-to-west progression beginning in the Chihuahuan Desert. The unexpected phylogenetic position of some samples suggests that the genus may contain additional, morphologically cryptic species. Geometric morphometric analyses reveal a largely conserved cheliceral morphology among Eremocosta spp. Phylogeographic analyses indicate that the distribution of E. titania was substantially reduced during the last glacial maximum and the species only recently colonized much of the Mojave Desert. Results from this study underscore the power of genome-wide data for unlocking the genetic potential of museum specimens, which is especially promising for organisms like camel spiders that are notoriously difficult to collect.

Impacts of a single fire event on large, old trees in a grass-invaded arid river system

Background Large old trees are keystone structures of terrestrial ecosystems that provide unique habitat resources for wildlife. Their widespread decline worldwide has serious implications for biodiversity and ecosystem integrity. In arid regions, large trees are relatively uncommon and often restricted to areas with elevated soil moisture and nutrients. Introduced grasses, now pervasive in many dryland environments, also thrive in such areas and are promoting more frequent and intense fire, potentially threatening the persistence of large trees. Here we report on the impact of a single wildfire on large river red gums (Eucalyptus camaldulensis Dehnh.) in arid riparian woodland invaded by buffel grass (Cenchrus ciliaris L.), a serious invader of desert ecosystems worldwide. In 2018, 266 trees with > 80 cm equivalent trunk diameter were mapped at six sites to provide a ‘pre-fire’ baseline. Within a year, the sites were impacted by a large, unprecedented wildfire that burnt an area of 660 km2 ha in 15 days. Sites were resurveyed in February 2019 to assess the fate of the trees. Reference to fire severity, calculated from remote-sensed imagery, is provided for additional context. Results In total, 67 trees, 27% of all large trees at the sites were destroyed. If trees in unburnt patches are excluded, 54% of trees exposed to the fire were destroyed and the remainder lost on average 79% of their canopy. Conclusions This severe detrimental effect of a single fire, on trees estimated to be centuries old, is indicative of tree-loss occurring across remote arid Australia in habitats where fire is now fuelled predominantly by invasive grasses. Large volumes of novel grass fuels along creeklines in combination with extreme weather events were major factors driving the spread, extent and impacts of the wildfire we report on and are causing a shift from relatively uncommon and predictable, rainfall-dependent large wildfires to large, severe fires that can occur anytime. We predict further decline in the abundance of large trees from similar fires will occur widely throughout arid Australia over the next decade with substantial long-term impacts on multiple species. New strategies are urgently required to manage fire in invaded arid ecosystems to better protect large trees and the critical resources they provide.

Ecological performance of local initiatives on water resources management in Timorese communities, Indonesia

Indonesia is one of the countries under the threat of a water crisis. A total of 106 districts from 16 provinces, including East Nusa Tenggara, experienced drought and clean water crisis of 1.50 billion m3 year−1. This involves ecological characteristics accumulation of semiarid regions, degradation of forest resources, and increased critical land. Mitigation research on a watershed scale provides an understanding of the strong relationship between land degradation and water crisis. However, specific information on biophysical spring sources in semi-arid ecosystems is still very limited. This study aimed to obtain ecological performance based on rainfall, critical land, and land cover from a community-based water resource management model on the Timor island. This study was conducted through field observations at 63 units of water sources and structured interviews. The results showed that the characteristics vary from rainfall distribution, land cover, critical land, and utilization pressure. Furthermore, water source units have a limited carrying capacity of rainfall, the land conditions are generally critical, including the threat of land fires and community use of springs. Meanwhile, the variations of these characteristics determine the management interventions undertaken by the community. Therefore, through various management models of community-based water sources, local initiatives need to get support to preserve water sources for the people’s livelihood.

Determining Actual Evapotranspiration Based on Machine Learning and Sinusoidal Approaches Applied to Thermal High-Resolution Remote Sensing Imagery in a Semi-Arid Ecosystem

Evapotranspiration (ET) is key to assess crop water balance and optimize water-use efficiency. To attain sustainability in cropping systems, especially in semi-arid ecosystems, it is necessary to improve methodologies of ET estimation. A method to predict ET is by using land surface temperature (LST) from remote sensing data and applying the Operational Simplified Surface Energy Balance Model (SSEBop). However, to date, LST information from Landsat-8 Thermal Infrared Sensor (TIRS) has a coarser resolution (100 m) and longer revisit time than Sentinel-2, which does not have a thermal infrared sensor, which compromises its use in ET models as SSEBop. Therefore, in the present study we set out to use Sentinel-2 data at a higher spatial-temporal resolution (10 m) to predict ET. Three models were trained using TIRS’ images as training data (100 m) and later used to predict LST at 10 m in the western section of the Copiapó Valley (Chile). The models were built on cubist (Cub) and random forest (RF) algorithms, and a sinusoidal model (Sin). The predicted LSTs were compared with three meteorological stations located in olives, vineyards, and pomegranate orchards. RMSE values for the prediction of LST at 10 m were 7.09 K, 3.91 K, and 3.4 K in Cub, RF, and Sin, respectively. ET estimation from LST in spatial-temporal relation showed that RF was the best overall performance (R2 = 0.710) when contrasted with Landsat, followed by the Sin model (R2 = 0.707). Nonetheless, the Sin model had the lowest RMSE (0.45 mm d−1) and showed the best performance at predicting orchards’ ET. In our discussion, we argue that a simplistic sinusoidal model built on NDVI presents advantages over RF and Cub, which are constrained to the spatial relation of predictors at different study areas. Our study shows how it is possible to downscale Landsat-8 TIRS’ images from 100 m to 10 m to predict ET.