Predicting spatial‐temporal patterns of diet quality and large herbivore performance using satellite time series

Jellyfish form associations with a diverse fauna including parasites and commensals, yet, ecological data on these associations, particularly time series, are rare. The present study examined temporal variation in the intensities and prevalences of two symbionts, namely, a sphaeromatid isopod (Cymodoce gaimardii) and a parasitic anemone (Anemonactis clavus) of the scyphozoan jellyfish Catostylus mosaicus over a 2-year period. Jellyfish were captured from Port Phillip Bay, Victoria, Australia, approximately every 6 weeks and inspected for symbionts. The isopod occurred on C. mosaicus on 16 of the 19 sampling occasions; prevalences ranged from 5 to 85%, and were highest in summer and autumn. Intensity ranged from one to five isopods per jellyfish. Juvenile, immature and mature isopods were present. The parasitic anemone A. clavus occurred only between May and September. Prevalences were lower than for the isopod (on 5–20% of jellyfish when present) as was maximum intensity (two anemones per jellyfish). Catostylus mosaicus appears to play an important role in the life history of a suite of symbionts, and the present study is the first to examine temporal changes in the association of the jellyfish with two of these symbionts.

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Temporal patterns in species zonation in a mangrove forest in the Mekong Delta, Vietnam, using a time series of Landsat imagery

Continental Shelf Research ◽

10.1016/j.csr.2017.07.007 ◽

2017 ◽

Vol 147 ◽

pp. 144-154 ◽

Cited By ~ 20

Author(s):

Eric L. Bullock ◽

Sergio Fagherazzi ◽

William Nardin ◽

Phuoc Vo-Luong ◽

Phong Nguyen ◽

...

Keyword(s):

Time Series ◽

Mangrove Forest ◽

Landsat Imagery ◽

Mekong Delta ◽

Temporal Patterns ◽

Species Zonation

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Spatial Distribution of Aedes aegypti Oviposition Temporal Patterns and Their Relationship with Environment and Dengue Incidence

Insects ◽

10.3390/insects12100919 ◽

2021 ◽

Vol 12 (10) ◽

pp. 919

Author(s):

Verónica Andreo ◽

Ximena Porcasi ◽

Claudio Guzman ◽

Laura Lopez ◽

Carlos M. Scavuzzo

Keyword(s):

Time Series ◽

Spatial Distribution ◽

Aedes Aegypti ◽

Urban Areas ◽

Mosquito Species ◽

Activity Patterns ◽

Positive Association ◽

Temporal Patterns ◽

Transmission Risk ◽

Machine Learning Classification

Aedes aegypti, the mosquito species transmitting dengue, zika, chikungunya and yellow fever viruses, is fully adapted to thrive in urban areas. The temporal activity of this mosquito, however, varies within urban areas which might imply different transmission risk. In this work, we hypothesize that temporal differences in mosquito activity patterns are determined by local environmental conditions. Hence, we explore the existence of groups of temporal patterns in weekly time series of Ae. aegypti ovitraps records (2017–2019) by means of time series clustering. Next, with the aim of predicting risk in places with no mosquito field data, we use machine learning classification tools to assess the association of temporal patterns with environmental variables derived from satellite imagery and predict temporal patterns over the city area to finally test the relationship with dengue incidence. We found three groups of temporal patterns that showed association with land cover diversity, variability in vegetation and humidity and, heterogeneity measured by texture indices estimated over buffer areas surrounding ovitraps. Dengue incidence on a neighborhood basis showed a weak but positive association with the percentage of pixels belonging to only one of the temporal patterns detected. The understanding of the spatial distribution of temporal patterns and their environmental determinants might then become highly relevant to guide the allocation of prevention and potential interventions. Further investigation is still needed though to incorporate other determinants not considered here.

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