1,721,143 research outputs found
Coastline Dune Vegetation Dynamics: Evidence of No Stability
No full textCoastal dune ecosystems are subjected to severe stress and disturbance factors that are particularly high in the beach-foredune environment and generally decrease with distance from the coast. The present study aimed to link plant species composition of coastal foredunes with the physical dynamical processes of the coastline in central Italy. A random hierarchical sampling design, based on two spatial scales (quadrant and parcel), was applied to estimate the variation in plant community composition. Permutational multivariate analysis of variance (PERMANOVA) revealed an approximately similar amount of variation with respect to both the coastal dynamic class and the parcel level. In addition, principal coordinate analyses showed that three taxa – Ammophila arenaria, Elymus farctus and Otanthus maritimus subsp. maritimus – were mainly linked to the coastal dynamics: A. arenaria increases its abundance where erosion of the shoreline is very high, while E. farctus and O. maritimus are more abundant in the prograding coast. Finally, similarity percentages analysis (SIMPER) highlighted that where the erosive processes were strongest, the number of the species contributing to the total similarity was the highest. This is likely to indicate instability and a strong disturbance of plant communities that results in an unstable equilibrium. These findings have important implications for management and conservation actions
How severe wildfires and climate change could drive post-fire recovery of low-elevation vegetation: data from the first field campaign of a monitoring survey in the Karts (North-East Iatly)
No full textWildfires are a major ecological factor shaping vegetation and landscape, and their impacts are projected to
escalate due to global warming: the intensity, frequency and extent of fires are increasing all over the world,
with dramatic consequences on habitats. In summer 2022, severe fires burnt over 4000 hectares of the
western Karst between Italy and Slovenia, a submediterranean low-hilly area near the coast. In spring 2023, we
started a survey to analyze the consequences of the 2022 fires on plant communities and to monitor post-fire
vegetation dynamics. This study aims to investigate the possible effects of interactions of severe fires, climate
change and alien species on the floristic composition of habitats and on the typical processes of post-fire
vegetation recovery in a low-elevated area.
The study was focused on 4 major habitats of the western Karst, 3 of which dynamically related: the
thermophilous karst grassland Centaureo cristatae-Chrysopogonetum grylli, the thermophilous shrubland
Pruno mahaleb-Paliuretum spina-christi, and the karst downy oak wood Aristolochio luteae-Quercetum
pubescentis. Black pine plantations were also included due to their large extent. Permanent plots were
installed in the most intensively burnt areas mapped by satellite remote sensing data using a stratified random
sampling, by placing 7 x 7 m2 squared-plots in the four major habitat types identified on the basis of available
habitat maps and photo-interpretation. In each plot the percent cover of total vegetation, bare soil and of all
species was recorded.
At the habitat level, the highest total species richness and the lowest one for alien species were both found
in the dry karst grassland, which also exhibited excellent quantitative and qualitative recovery, confirming itself
as a highly resilient habitat. Shrubland showed a strong recovery of native shrub species, a rather high number
of total species and alien species compared to the investigated habitats, however with alien species occurring
with low cover values. The downy oak woodland had similar species richness values to shrubland, but higher
abundance of alien species, esp. Robinia pseudoacacia and Ailanthus altissima, and of native ruderal species:
therefore strong modifications of the floristic structure with deviations from the typical secondary succession
are possible. Black pine plantations were found to be characterized by the lowest total species richness, the
highest number of native ruderal and alien species, poor recovery of native species and unclear dynamic
trajectories.
The study is meant to provide information i) to identify interventions to support and eventually correct the
post-fire recovery of habitats, ii) to support land management policies to enhance the resilience and resistance
of the Karst landscape to wildfires
Le specie aliene vegetali nel sistema di aree protette della Provincia di Siena: dati quantitativi per il loro monitoraggio
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Review of Invasive Plant Functional Traits and Management Using Remote Sensing in Sub-Saharan Africa
Full text linkBiodiversity and sustainable development in Sub-Saharan Africa (SSA) are considerably impacted by invasive alien plants (IAPs). Increasing plant invasions in SSA threaten agricultural productivity, biodiversity conservation, and other socioeconomic activities, which in turn put the United Nations Sustainable Development Goals (SDGs) in peril. In order to effectively combat IAPs, understanding their functional traits (morphological, physiological, and phenological traits) and integrating them into remote sensing (RS) is vital. While functional traits influence IAPs’ fitness to invade and establish in a new geographical range, RS aids in studying them remotely, delineating and mapping them, and predicting their potential invasions. The information on this study topic was gathered by reviewing various existing studies published between 2000 and 2024. Based on this review, it was deduced that the majority of IAPs are fast-growing (or acquisitive), with a shorter leaf lifespan, bigger leaves, and higher plant height, ultimately resulting in a higher resource acquisition ability. We established further that in SSA, there are limited studies on IAP functional traits and their integration in RS. Many studies conducted in the region focus mostly on IAP distribution. Evidence from prior studies revealed that functional trait remote sensing (FTRS)-based research not only improves detection and mapping but also predicts whether a certain alien plant can become invasive or expand its distribution range. Thus, using the FTRS approach could help IAP management in SSA, ultimately achieving the SDGs. Our review discusses IAP implications in SSA (e.g., Angola, Tanzania, Benin, Kenya, Uganda, Rwanda, Zambia, Burundi, Zimbabwe, Botswana, Malawi, etc.) and for the achievement of SDGs; functional traits and their impact on alien invasions; and the importance of incorporating functional traits into RS
The power of generalized entropy for biodiversity assessment by remote sensing: an open source approach
No full textLa stima della diversit ́ a specifica in aree estese rappresenta da sempre
una sfida per gli ecologi, a causa della intrinseca difficolt ́ a di giudicare la com-
pletezza degli inventari di specie basata su un campionamento appropriato. Dal
momento che la variabilit ́ a del segnale telerilevato relazionata alla diversit ́ a del
paesaggio, questa potrebbe essere utilizzata come surrogato della diversit ́ a a livello
di specie. La relazione tra diersit ́ a specifica e diversit ́ a del paesaggio misurata da
dati telerilevati o da mappe di uso del suolo varia con la scala. Mentre le misure
tradizionali rappresentano descrittori puntuali della diversit ́ a, l’entropia generaliz-
zata offre una continuit ́ a di possibili misure, che differiscono nella loro sensibilit ́ a
rispetto a valori spettrali abbondanti e rari. Lo scopo di questo studio quello di: i)
discutere la teoria ecologica alla base della misura della diversit ́ a tramite l’entropia
generalizzata e ii) testare un approccio basato su codice open source per il calcolo.
Ci attendiamo che l’argomento di questo articolo stimoli la discussione riguardo
le opportunit ́ a offerte da software con codice aperto per il calcolo degli indici di
diversit ́ a del paesaggio.The assessment of species diversity in relatively large areas has always
been a challenging task for ecologists, mainly because of the intrinsic difficulty to
judge the completeness of species lists and to undertake sufficient and appropriate
sampling. Since the variability of remotely sensed signal is expected to be related
to landscape diversity, it could be used as a good proxy of diversity at species level.
It has been demonstrated that the relation between species and landscape diversity
measured from remotely sensed data or land use maps varies with scale. While tra-
ditional metrics supply point descriptions of diversity, generalized entropy’s frame-
work offers a continuum of possible diversity measures, which differ in their sensi-
tivity to rare and abundant reflectance values In this paper, we aim at: i) discussing
the ecological background beyond the importance of measuring diversity based on
generalized entropy and ii) providing a test on an Open Source tool with its source
code for calculating it. We expect that the subject of this paper will stimulate discus-
sions on the opportunities offered by Free and Open Source Software to calculate
landscape diversity indices
Assessing the conservation value of farmland ponds: use of predictive techniques to identify surrogate groups
No full textUse of Remote Sensing Techniques to Estimate Plant Diversity within Ecological Networks: A Worked Example
Full text linkAs there is an urgent need to protect rapidly declining global diversity, it is important to identify methods to quickly estimate the diversity and heterogeneity of a region and effectively implement monitoring and conservation plans. The combination of remotely sensed and field-collected data, under the paradigm of the Spectral Variation Hypothesis (SVH), represents one of the most promising approaches to boost large-scale and reliable biodiversity monitoring practices. Here, the potential of SVH to capture information on plant diversity at a fine scale in an ecological network (EN) embedded in a complex landscape has been tested using two new and promising methodological approaches: the first estimates α and β spectral diversity and the latter ecosystem spectral heterogeneity expressed as Rao’s Quadratic heterogeneity measure (Rao’s Q). Both approaches are available thanks to two brand-new R packages: “biodivMapR” and “rasterdiv”. Our aims were to investigate if spectral diversity and heterogeneity provide reliable information to assess and monitor over time floristic diversity maintained in an EN selected as an example and located in northeast Italy. We analyzed and compared spectral and taxonomic α and β diversities and spectral and landscape heterogeneity, based on field-based plant data collection and remotely sensed data from Sentinel-2A, using different statistical approaches. We observed a positive relationship between taxonomic and spectral diversity and also between spectral heterogeneity, landscape heterogeneity, and the amount of alien species in relation to the native ones, reaching a value of R2 = 0.36 and R2 = 0.43, respectively. Our results confirmed the effectiveness of estimating and mapping α and β spectral diversity and ecosystem spectral heterogeneity using remotely sensed images. Moreover, we highlighted that spectral diversity values become more effective to identify biodiversity-rich areas, representing the most important diversity hotspots to be preserved. Finally, the spectral heterogeneity index in anthropogenic landscapes could be a powerful method to identify those areas most at risk of biological invasion
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