Seeing through the clouds – Mapping desert fog oasis ecosystems using 20 years of MODIS imagery over Peru and Chile

Moat, Justin; Orellana-García, Alfonso; Tovar, Carolina; Arakaki, Mónica; Arana, César; Cano, Asunción; Faúndez, Luis; Gardner, Martin; Hechenleitner, Paulina; Hepp, Josefina; Lewis, Gwilym P.; Mamani, José-Manuel; Miyasiro, María; Whaley, Oliver Q.

doi:10.1016/j.jag.2021.102468

Cited by 36 publications

(64 citation statements)

References 23 publications

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“…In contrast, the highest percentage of shared species with sites in the desert and Andes of Chile were usually below 8% of the recorded species in Huancacasa and La Bolivar. Our results concur well with the pattern of distinct desert plant communities reported by Ruhm et al (2020) and reflect the high levels of endemism reported here and for the Atacama and Peruvian desert communities (Rundel et al 1991;Moat et al 2021).…”

Section: Changes In the Desert Flora Along The Elevation Gradientsupporting

confidence: 91%

“…There is extensive documentation on the floristic composition and plant diversity patterns of coastal deserts (e.g. Luebert 2011, and references therein), which harbor important levels of plant endemism (Rundel et al 1991;Moat et al 2021), and the arid Puna (e.g. Luebert and Gajardo 2000;López et al 2006;Montesinos et al 2012Montesinos et al , 2015a.…”

Section: Research Papermentioning

confidence: 99%

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Plant diversity and structure in desert communities of the Andean piedmont in Ica, Peru

Montenegro-Hoyos¹,

Vega²,

Linares-Palomino³

2022

VCS

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Aims: There is extensive documentation of the floristic composition and plant diversity patterns in the South American coastal deserts and the adjoining arid Puna. Surprisingly, the vegetation along the transition zone from these deserts in the coastal lowlands to the Puna highlands has been little studied. The main goal of this study was to characterize and compare the structure of plant communities in two localities in the Ica department, with the aim of contributing to the floristic knowledge of the desertic western Andean slopes along the lowlands to Andean transition zone. Study area: Huancacasa and La Bolivar localities located at approximately 740 and 3,000 m a.s.l. in the Ica department, Peru. Methods: We sampled 10 plots of 100 m × 60 m located between 740–1,600 m a.s.l. in La Bolivar and 15 modified Whittaker plots (MWPs) of 20 m × 5 m located between 2,800–3,000 m a.s.l. in Huancacasa and recorded species richness and abundance. We estimated alpha diversity, performed Non-Metric Multidimensional Scaling (NMDS) and one-way Similarity (ANOSIM) analyses and plotted rank-abundance curves. Results: We recorded 215 species and morphospecies with coastal and Andean distribution, including 43 species (21.3%) that are either considered endemic to Peru or have been considered under some form of threat by Peruvian or international standards. Both plant communities differed in terms of composition, species richness, abundance, and dominant growth form, with higher values in the communities located at higher elevations. We added 83 species as new records for the Ica department. Conclusions: Our research reinforced the need to increase exploration and documentation of the vegetation within the lowland to highland transition zone along the dry western slopes of the Andes. Our results from such a transition in Ica department in southern Peru, show that much of its plant diversity seems to be, as yet, largely unknown. Taxonomic reference: The Plant List (2013). Abbreviations: ANOSIM = one-way Analysis of Similarities; BMAP = Biodiversity Monitoring and Assessment Program; IUCN = International Union for Conservation of Nature; NMDS = Non-Metric Multidimensional Scaling; USM = Universidad Nacional Mayor de San Marcos (Herbarium).

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Section: Changes In the Desert Flora Along The Elevation Gradientsupporting

confidence: 91%

Section: Research Papermentioning

confidence: 99%

Plant diversity and structure in desert communities of the Andean piedmont in Ica, Peru

Montenegro-Hoyos¹,

Vega²,

Linares-Palomino³

2022

VCS

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“…The Paposo-Taltal section in the coast of Antofagasta, at the Atacama margin, is considered as one of the most outstanding plant species-rich fog oasis along 3000 km of the Perú-Chile coast [36]. The arthropod diversity reported here (173 species grouped into 118 genera and 57 families) is proportionally higher than other surveyed fog oases.…”

Section: Discussionmentioning

confidence: 64%

“…One of the most relevant biotic sections along the Atacama coast is the Paposo-Taltal coastal site, located between 24.5 • and 25.5 • lat S. This site has been long recognized as a remarkable vegetational and floristic spot of the coastal margin of the Antofagasta Region [32][33][34][35] and has been recently highlighted as one of the most plant species-rich fog oases along 3000 km of the Peru-Chile coastal belt [36]. A remarkable arthropod fauna is associated to this floristic richness, including several endemic bee species, like Liphanthus jenamro Mir Sharifi, Graham and Packer [37] and Neofidelia camanchaca Dumesh and Packer [38]; two scarabs [39]; six tenebrionids [33,[40][41][42][43][44]; four latridids [45]; a buprestid [46]; four spiders [47][48][49][50]; a monotypic genus of oribatid mite [51]; a freshwater amphipod [52]; three endemic scorpions [53,54].…”

Section: Introductionmentioning

confidence: 99%

A Fine-Scale Hotspot at the Edge: Epigean Arthropods from the Atacama Coast (Paposo-Taltal, Antofagasta Region, Chile)

Pizarro-Araya

Alfaro

Ojanguren‐Affilastro

et al. 2021

Insects

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The Atacama Desert at its margins harbors a unique biodiversity that is still very poorly known, especially in coastal fog oases spanning from Perú towards the Atacama coast. An outstanding species-rich fog oasis is the latitudinal fringe Paposo-Taltal, that is considered an iconic site of the Lomas formation. This contribution is the first to reveal the knowledge on arthropods of this emblematic coastal section. We used pitfall traps to study the taxonomic composition, richness, and abundance of terrestrial arthropods in 17 sample sites along a 100 km section of the coast between 24.5 and 25.5 southern latitude, in a variety of characteristic habitats. From a total of 9154 individuals, we were able to identify 173 arthropod species grouped into 118 genera and 57 families. The most diverse group were insects, with 146 species grouped in 97 genera and 43 families, while arachnids were represented by 27 species grouped into 21 genera and 14 families. Current conservation challenges on a global scale are driving the creation and evaluation of potential conservation sites in regions with few protected areas, such as the margins of the Atacama Desert. Better taxonomic, distributional, and population knowledge is urgently needed to perform concrete conservation actions in a biodiversity hotspot at a desert edge.

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“…Preferably such features should be based on data available in form of a spatial grids covering the entirety of the prediction area (in this case, Australia). Remote sensing data are a promising and potentially highly informative data source to fill up spatial gaps with increasingly detailed vegetation maps (Gholizadeh et al, 2020; Moat et al, 2021), and could be applied in future machine learning models for the task of diversity prediction.…”

Section: Discussionmentioning

confidence: 99%

Estimating alpha, beta, and gamma diversity through deep learning

Andermann

Antonelli

Barrett

et al. 2022

Preprint

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The reliable mapping of species richness is a crucial step for the identification of areas of high conservation priority, alongside other value considerations. This is commonly done by overlapping range maps of individual species, which requires dense availability of occurrence data or relies on assumptions about the presence of species in unsampled areas deemed suitable by environmental niche models. Here we present a deep learning approach that directly estimates species richness, skipping the step of estimating individual species ranges. We train a neural network model based on species lists from inventory plots, which provide ground truthing for supervised machine learning. The model learns to predict species richness based on spatially associated variables, including climatic and geographic predictors, as well as counts of available species records from online databases. We assess the empirical utility of our approach by producing independently verifiable maps of alpha, beta, and gamma plant diversity at high spatial resolutions for Australia, a continent with highly contrasting diversity patterns. Our deep learning framework provides a powerful and flexible new approach for estimating biodiversity patterns.

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Seeing through the clouds – Mapping desert fog oasis ecosystems using 20 years of MODIS imagery over Peru and Chile

Cited by 36 publications

References 23 publications

Plant diversity and structure in desert communities of the Andean piedmont in Ica, Peru

Plant diversity and structure in desert communities of the Andean piedmont in Ica, Peru

A Fine-Scale Hotspot at the Edge: Epigean Arthropods from the Atacama Coast (Paposo-Taltal, Antofagasta Region, Chile)

Estimating alpha, beta, and gamma diversity through deep learning

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