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Stivanello, S.

Publications and source records attributed to Stivanello, S..

2 recordsLinked to original sources

Discordant changes in foliar and reproductive phenology of tropical dry-forest trees under increasing temperature and decreasing wet-season rainfall

O_LIPlant phenology drives population dynamics and forest productivity; it is also impacted by shifting environmental cues under climate change such as more prevalent drought. It is imperative to better understand how species and community phenology respond to climate change in leaf turnover and reproduction, both of which are required to integrate phenology into full life-cycle assessments. C_LIO_LIHowever, relatively few studies to-date examined the quantity and timing of phenology simultaneously. We demonstrate that the simultaneous assessment of phenological quantity and timing across multiple organs reveals more nuanced and holistic insights into the consequences of climate change. C_LIO_LIExtending a regression approach based on Fourier series, we decomposed the long-term (2004-2020) monthly leaf shedding, leaf flush, flowering and fruiting of 617 trees across 94 taxa at a Nigerian seasonally dry tropical forest into three periodic components--mean intensity, amplitude and phase--which respectively represents the total quantity, pulse concentration and peak timing of phenology. We then related each periodic component to warming minimum temperature and drying wet-season rainfall. C_LIO_LIWe found that climate explained more variation in phenological amplitudes (14-66%) compared to mean intensity and timing (6-49%). In drier years, more species (18%) shed leaves earlier (changing timing) or in more concentrated pulses (changing amplitude), while only a few (2%) shed leaves in greater total amounts (changing mean intensity). This combined with the decreased mean intensity of leaf flush imply a lower primary productivity as trees deployed fewer leaves for a shorter period. Some species (30%) produced fewer fruits despite no change or even increase in flowering; in a few species this could be explained by a shortened flowering period that limited pollination. At the community level, reproduction became more synchronous, potentially creating periods of scarcity for consumers. C_LIO_LISynthesis: Our findings highlight several contrasting yet complementary phenology- climate insights, indicating that assessments of forests climate resilience necessitate multiple aspects of phenology rather than a single performance indicator. The decline of leaf and fruit productions, as well as the temporal mismatches in leaf turnover and reproduction, will have cascading impacts on trophic interactions and nutrient cycling. C_LI

ecology↗

Inferring macro-ecological patterns from local species’ occurrences

O_LIBiodiversity provides support for life, vital provisions, regulating services and has positive cultural impacts. It is therefore important to have accurate methods to measure biodiversity, in order to safeguard it when we discover it to be threatened. For practical reasons, biodiversity is usually measured at fine scales whereas diversity issues (e.g. conservation) interest regional or global scales. Moreover, biodiversity may change across spatial scales. It is therefore a key challenge to be able to translate local information on biodiversity into global patterns.\nC_LIO_LIMany databases give no information about the abundances of a species within an area, but only its occurrence in each of the surveyed plots. In this paper, we introduce an analytical framework to infer species richness and abundances at large spatial scales in biodiversity-rich ecosystems when species presence/absence information is available on various scattered samples (i.e. upscaling).\nC_LIO_LIThis framework is based on the scale-invariance property of the negative binomial. Our approach allows to infer and link within a unique framework important and well-known biodiversity patterns of ecological theory, such as the Species Accumulation Curve (SAC) and the Relative Species Abundance (RSA) as well as a new emergent pattern, which is the Relative Species Occupancy (RSO).\nC_LIO_LIOur estimates are robust and accurate, as confirmed by tests performed on both in silico-generated and real forests. We demonstrate the accuracy of our predictions using data from two well-studied forest stands. Moreover, we compared our results with other popular methods proposed in the literature to infer species richness from presence-absence data and we showed that our framework gives better estimates. It has thus important applications to biodiversity research and conservation practice.\nC_LI

ecology↗