tropical andes
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2022 ◽  
Vol 262 ◽  
pp. 107439
Author(s):  
Cristina Vásquez ◽  
Rolando Célleri ◽  
Mario Córdova ◽  
Galo Carrillo-Rojas

Hydrology ◽  
2021 ◽  
Vol 8 (4) ◽  
pp. 183
Author(s):  
Paul Muñoz ◽  
Johanna Orellana-Alvear ◽  
Jörg Bendix ◽  
Jan Feyen ◽  
Rolando Célleri

Worldwide, machine learning (ML) is increasingly being used for developing flood early warning systems (FEWSs). However, previous studies have not focused on establishing a methodology for determining the most efficient ML technique. We assessed FEWSs with three river states, No-alert, Pre-alert and Alert for flooding, for lead times between 1 to 12 h using the most common ML techniques, such as multi-layer perceptron (MLP), logistic regression (LR), K-nearest neighbors (KNN), naive Bayes (NB), and random forest (RF). The Tomebamba catchment in the tropical Andes of Ecuador was selected as a case study. For all lead times, MLP models achieve the highest performance followed by LR, with f1-macro (log-loss) scores of 0.82 (0.09) and 0.46 (0.20) for the 1 h and 12 h cases, respectively. The ranking was highly variable for the remaining ML techniques. According to the g-mean, LR models correctly forecast and show more stability at all states, while the MLP models perform better in the Pre-alert and Alert states. The proposed methodology for selecting the optimal ML technique for a FEWS can be extrapolated to other case studies. Future efforts are recommended to enhance the input data representation and develop communication applications to boost the awareness of society of floods.


2021 ◽  
pp. 1-10
Author(s):  
Estefania Quenta-Herrera ◽  
Verónica Crespo-Pérez ◽  
Bryan G Mark ◽  
Ana Lía Gonzales ◽  
Aino Kulonen

Summary Although protected areas (PAs) play an important role in ecosystem conservation and climate change adaptation, no systematic information is available on PA protection of high-elevation freshwater ecosystems (e.g., lakes and watersheds with glaciers), their biodiversity and their ecosystem services in the tropical Andes. We therefore combined a literature review and map analysis of PAs of International Union for Conservation of Nature (IUCN) and national systems of PAs and freshwater ecosystems. We found that seven national parks were created for water resources protection but were not designed for freshwater conservation (i.e., larger watersheds). High-value biodiversity sites have not been protected, and new local PAs were created due to water resource needs. We quantified 31 Ramsar sites and observed that PAs cover 12% of lakes, 31% of glacial lakes and 12% of the total stream length in the tropical Andes. Additionally, 120 watersheds (average area 631 km2) with glaciers and 40% of the total glacier surface area were covered by PAs. Future research into the role of PAs in ecosystem services provision and more detailed freshwater inventories within and around PAs, especially for those dependent on glacier runoff, will fill key knowledge gaps for freshwater conservation and climate change adaptation in the tropical Andes.


2021 ◽  
pp. 103722
Author(s):  
Adam Emmer ◽  
Joanne L. Wood ◽  
Simon J. Cook ◽  
Stephan Harrison ◽  
Ryan Wilson ◽  
...  

Zootaxa ◽  
2021 ◽  
Vol 5072 (3) ◽  
pp. 201-237
Author(s):  
OSCAR MAHECHA-J. ◽  
KLAUDIA FLORCZYK ◽  
KEITH WILLMOTT ◽  
JOSÉ CERDEÑA ◽  
ANNA ZUBEK ◽  
...  

The Huancabamba Deflection in the Andes of northern Peru and southern Ecuador is a pivotal area for Neotropical biogeography, where exceptional biodiversity coincides with high rates of endemism. These characteristics are well illustrated within the montane butterfly genus Manerebia Staudinger (Nymphalidae, Satyrinae). Here, six new, apparently endemic species, and two new subspecies, are described from this region: M. inducta Pyrcz & Willmott n. sp., M. ronda Pyrcz & Boyer, n. sp., M. ronda amplia Pyrcz & Boyer, n. ssp., M. punku Pyrcz & Farfán n. sp., M. huamanii Cerdeña & Pyrcz n. sp., M. placida Pyrcz & Willmott n. sp., M. granatus Willmott, Radford & Pyrcz n. sp. and M. prattorum udima Pyrcz & Boyer, n. ssp. A total of 22 species of Manerebia is reported from the study region, as much as half the total number of species in this genus distributed throughout the tropical Andes. The alpha-taxonomy of Manerebia is particularly demanding, as colour patterns have apparently converged among different species making identification virtually impossible in some cases without comparison of their genitalia, which prove taxonomically and phylogenetically highly valuable. On the other hand, several species differ markedly in wing colour patterns and occur at different elevations but have identical genitalia. Furthermore, our data show that DNA barcoding is only partly viable as an alpha-taxonomic tool, as some markedly different species of Manerebia, in terms of external morphology and ecological preferences, are genetically not separable using only COI markers. On the other hand, several species barely differing morphologically are identified based on barcode. Barcodes of 26 species, including 18 from the northern Andes, are studied here, showing strong differences within some taxa previously considered conspecific based on morphological characters, suggesting that their taxonomic status needs to be re-evaluated. In particular, M. trimaculata and the widely distributed polytypic M. inderena may be highly variable species or complexes of several species. A total of 16 species are found north of the Chamaya valley in southern Ecuador and extreme northern Peru, compared to 14 species south of it in northern Peru. The faunal (Jaccard) similarity coefficient of the two adjacent regions is low (0.3), reflecting the role of the Huancabamba Deflection as a biogeographical barrier.  


Author(s):  
Paul Muñoz ◽  
Johanna Orellana-Alvear ◽  
Jörg Bendix ◽  
Jan Feyen ◽  
Rolando Célleri

Flood Early Warning Systems (FEWSs) using Machine Learning (ML) has gained worldwide popularity. However, determining the most efficient ML technique is still a bottleneck. We assessed FEWSs with three river states, No-alert, Pre-alert, and Alert for flooding, for lead times between 1 to 12 hours using the most common ML techniques, such as Multi-Layer Perceptron (MLP), Logistic Regression (LR), K-Nearest Neighbors (KNN), Naive Bayes (NB), and Random Forest (RF). The Tomebamba catchment in the tropical Andes of Ecuador was selected as case study. For all lead times, MLP models achieve the highest performance followed by LR, with f1-macro (log-loss) scores of 0.82 (0.09) and 0.46 (0.20) for the 1- and 12-hour cases, respectively. The ranking was highly variable for the remaining ML techniques. According to the g-mean, LR models correctly forecast and show more stability at all states, while the MLP models perform better in the Pre-alert and Alert states. Future efforts are recommended to enhance the input data representation and develop communication applications to boost the awareness of the society for floods.


2021 ◽  
Author(s):  
Mónica Díaz‐Páez ◽  
Leland K. Werden ◽  
Rakan A. Zahawi ◽  
Julian Usuga ◽  
Jaime Polanía

2021 ◽  
Author(s):  
Adriana Paulina Guarderas ◽  
Franz Smith ◽  
Marc Dufrene

Tropical mountain ecosystems are threatened by land use pressures, reducing the capacity of ecosystems to provide a large diversity of benefits to people and to be able to achieve them in the long term. The analysis of land use pressures is often superficial and very general, although they are characterized by numerous interactions and strong differences in their local dynamics. We used a variety of freely available geospatial and temporal data and methods to assess and explain patterns of land use land cover (LULC) change, focusing on native ecosystem dynamics, in a sensitive region of the northern Ecuadorian Andes. Our results demonstrate a dynamic and clear geographical pattern of distinct LULC transitions through time, explained by different combination of socio-economic factors, pressure variables and environmental parameters, from which ecological context variables, such as slope and elevation, were the main drivers of change in this landscape. We found that deforestation of remnant native forest and agricultural expansion still occur in higher elevations located, while land conversion toward anthropic environments were observed in lower elevations to the east of the studied territory. Our findings also reveal an unexpected stability trend of paramo and a successional recovery of previous agricultural land to the west and center of the territory which could be explained by agricultural land abandonment. However, the very low probability of persistence of montane forests in most of the studied landscape, highlights the risk that the remnant montane forests will be permanently lost in a few years, posing a greater threat to the already vulnerable biodiversity and limiting the capacity ecosystem service provisioning. The dynamic patterns through space and time and their explanatory drivers, found in our study, could help improve sustainably resource land management in vulnerable landscapes such as the tropical Andes in northern Ecuador.


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