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Projeto de investigação
Integração de dados de diferentes satelites para mapear combustiveis florestais: o papel da detecção remota para uma efectiva gestão dos combustiveis florestais
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Autores
Publicações
Vegetation canopy height shapes bats’ occupancy: a remote sensing approach
Publication . Martins, F. C.; Godinho, S.; Guiomar, N.; Medinas, D.; Rebelo, H.; Segurado, P.; Marques, J. T.
Anthropogenic activities have significantly altered land cover on a global scale. These changes often
have a negative effect on biodiversity limiting the distribution of species. The extent of the effect on
species’ distribution depends on the landscape composition and configuration at a local and landscape
level. To better understand this effect on a large scale, we evaluated how land cover and vegetation
structure shape bat species’ occurrence while considering species’ imperfect detection. We hypothesize
that intensification of anthropogenic activities in agriculture, for example, reduces heterogeneity of land
cover and vegetation structure, and thereby, limits bat occurrence. To investigate this, we conducted
acoustic bat sampling across 59 locations in southern Portugal, each with three spatial replicates. We
derived fine-scale vegetation structural metrics by combining spaceborne LiDAR (GEDI) and synthetic
aperture radar data (Sentinel-1 and ALOS/PALSAR-2). Additionally, we included land cover metrics and
high-resolution climate data from CHELSA. Our findings revealed an important relationship between bat
species’ occupancy and vegetation structure, particularly with vegetation canopy height. Moreover,
forest and shrubland proportions were the main land cover types influencing bat species responses. All
species’ best-ranking occupancy models included at least one climatic variable (temperature, humidity,
or potential evapotranspiration), demonstrating the importance of climate when predicting bat dis-
tribution. Our acoustic surveys had a species’ detection probability varying from 0.19 to 0.86, and it was
influenced by night conditions. These findings underscore the importance of modeling imperfect
detection, especially for highly vagile and elusive organisms like bats. Our results demonstrate the
effectiveness of using vegetation and landscape metrics derived from high-resolution remote sensing
data to model species distribution in the context of biodiversity monitoring and conservation.
High‑resolution species distribution modelling reveals spatio‑temporal variability of habitat suitability in a declining grassland bird
Publication . Crispim‑Mendes, Tiago; Valerio, Francesco; Marques, Ana Teresa; Pita, Ricardo; Godinho, Sérgio; Silva, João Paulo
Context Species distribution models (SDMs) may
provide accurate predictions of species occurrence
across space and time, being critical for effective con-
servation planning.
Objectives Focusing on the little bustard (Tetrax
tetrax), an endangered grassland bird, we aimed to:
(i) characterise the drivers of the species distribution
along its key phenological phases (winter, breeding,
and post-breeding); and (ii) quantify spatio-temporal
variation in habitat suitability across phenological
phases and over the years 2005–2021.
Methods Combining remotely sensed metrics at
high temporal resolution (MODIS) with long-term
(> 12 years) GPS telemetry data collected for 91 individuals at one of the species’ main strongholds
within the Iberian Peninsula, we built SDMs (250 m
resolution) for the species key phenological phases.
Results The use of both dynamic and static pre-
dictors unveiled previously unknown ecological
responses by little bustards, revealing a marked
change in the spatial distribution of suitable habitat
among phenological phases. Long-term habitat suita-
bility trends showed considerable fluctuations, mainly
in the breeding and post-breeding phases. Overall,
SDM projections into the past revealed that while
the species’ winter and post-breeding habitats appar-
ently increased since 2005, suitable habitat during the
species’ most critical phenological phase, breeding,
apparently reduced in area over time.
Conclusions Our findings show that matching
remotely sensed data with GPS tracking data results
in accurate habitat suitability predictions throughout the yearly cycle. Additionally, our findings stress the
importance of quantifying habitat loss and its poten-
tial impact on little bustard decline over nearly 20
years. Spatio-temporal variations in habitat suitability
are also identified in this work, which can help pri-
oritize conservation areas, particularly the breeding
areas that have remained stable over time, as this is a
key requirement for little bustard lek breeding system.
Unidades organizacionais
Descrição
Palavras-chave
Contribuidores
Financiadores
Entidade financiadora
Fundação para a Ciência e a Tecnologia
Programa de financiamento
Concurso de Projetos de Investigação Científica e Desenvolvimento Tecnológico no Âmbito da Prevenção e Combate a Incêndios Florestais - 2019
Número da atribuição
PCIF/GRF/0116/2019