Search for: All records

Datasets that monitor biodiversity capture information differently depending on their design, which influences observer behavior and can lead to biases across observations and species. Combining different datasets can improve our ability to identify and understand threats to biodiversity, but this requires an understanding of the observation bias in each. Two datasets widely used to monitor bird populations exemplify these general concerns: eBird is a citizen science project with high spatiotemporal resolution but variation in distribution, effort, and observers, whereas the Breeding Bird Survey (BBS) is a structured survey of specific locations over time. Analyses using these two datasets can identify contradictory population trends. To understand these discrepancies and facilitate data fusion, we quantify species‐level reporting differences across eBird and the BBS in three regions across the United States by jointly modeling bird abundances using data from both datasets. First, we fit a joint Species Distribution Model that accounts for environmental conditions and effort to identify reporting differences across the datasets. We then examine how these differences in reporting are related to species traits. Finally, we analyze species reported to one dataset but not the other and determine whether traits differ between reported and unreported species. We find that most species are reported more in the BBS than eBird. Specifically, we find that compared to eBird, BBS observers tend to report higher counts of common species and species that are usually detected by sound. We also find that species associated with water are reported less in the BBS. Species typically identified by sound are reported more at sunrise than later in the morning. Our results quantify reporting differences in eBird and the BBS to enhance our understanding of how each captures information and how they should be used. The reporting rates we identify can also be incorporated into observation models through detectability or effort to improve analyses across species and datasets. The method demonstrated here can be used to compare reporting rates across any two or more datasets to examine biases.

 

Observational studies have not yet shown that environmental variables can explain pervasive nonlinear patterns of species abundance, because those patterns could result from (indirect) interactions with other species (e.g., competition), and models only estimate direct responses. The experiments that could extract these indirect effects at regional to continental scales are not feasible. Here, a biophysical approach quantifies environment– species interactions (ESI) that govern community change from field data. Just as species interactions depend on population abundances, so too do the effects of environment, as when drought is amplified by competition. By embedding dynamic ESI within framework that admits data gathered on different scales, we quantify responses that are induced indirectly through other species, including probabilistic uncertainty in parameters, model specification, and data. Simulation demonstrates that ESI are needed for accurate interpretation. Analysis demonstrates how nonlinear responses arise even when their direct responses to environment are linear. Applications to experimental lakes and the Breeding Bird Survey (BBS) yield contrasting estimates of ESI. In closed lakes, interactions involving phytoplankton and their zooplankton grazers play a large role. By contrast, ESI are weak in BBS, as expected where year-to-year movement degrades the link between local population growth and species interactions. In both cases, nonlinear responses to environmental gradients are induced by interactions between species. Stability analysis indicates stability in the closed-system lakes and instability in BBS. The probabilistic framework has direct application to conservation planning that must weigh risk assessments for entire habitats and communities against competing interests.

 

Tree fecundity and recruitment have not yet been quantified at scales needed to anticipate biogeographic shifts in response to climate change. By separating their responses, this study shows coherence across species and communities, offering the strongest support to date that migration is in progress with regional limitations on rates. The southeastern continent emerges as a fecundity hotspot, but it is situated south of population centers where high seed production could contribute to poleward population spread. By contrast, seedling success is highest in the West and North, serving to partially offset limited seed production near poleward frontiers. The evidence of fecundity and recruitment control on tree migration can inform conservation planning for the expected long-term disequilibrium between climate and forest distribution. 

Abstract The relationships that control seed production in trees are fundamental to understanding the evolution of forest species and their capacity to recover from increasing losses to drought, fire, and harvest. A synthesis of fecundity data from 714 species worldwide allowed us to examine hypotheses that are central to quantifying reproduction, a foundation for assessing fitness in forest trees. Four major findings emerged. First, seed production is not constrained by a strict trade-off between seed size and numbers. Instead, seed numbers vary over ten orders of magnitude, with species that invest in large seeds producing more seeds than expected from the 1:1 trade-off. Second, gymnosperms have lower seed production than angiosperms, potentially due to their extra investments in protective woody cones. Third, nutrient-demanding species, indicated by high foliar phosphorus concentrations, have low seed production. Finally, sensitivity of individual species to soil fertility varies widely, limiting the response of community seed production to fertility gradients. In combination, these findings can inform models of forest response that need to incorporate reproductive potential. 

Measuring plant productivity is critical to understanding complex community interactions. Many traditional methods for estimating productivity, such as direct measurements of biomass and cover, are resource intensive, and remote sensing techniques are emerging as viable alternatives.

We explore drone‐based remote sensing tools to estimate productivity in a tallgrass prairie restoration experiment and evaluate their ability to predict direct measures of productivity. We apply these various productivity measures to trace the evolution of plant productivity and the traits underlying it.

The correlation between remote sensing data and direct measurements of productivity varies depending on vegetation diversity, but the volume of vegetation estimated from drone‐based photogrammetry is among the best predictors of biomass and cover regardless of community composition. The commonly used normalized difference vegetation index (NDVI) is a less accurate predictor of biomass and cover than other equally accessible vegetation indices. We found that the traits most strongly correlated with productivity have lower phylogenetic signal, reflecting the fact that high productivity is convergent across the phylogeny of prairie species. This history of trait convergence connects phylogenetic diversity to plant community assembly and succession.

Our study demonstrates (1) the importance of considering phylogenetic diversity when setting management goals in a threatened North American grassland ecosystem and (2) the utility of remote sensing as a complement to ground measurements of grassland productivity for both applied and fundamental questions.

 

Despite its importance for forest regeneration, food webs, and human economies, changes in tree fecundity with tree size and age remain largely unknown. The allometric increase with tree diameter assumed in ecological models would substantially overestimate seed contributions from large trees if fecundity eventually declines with size. Current estimates are dominated by overrepresentation of small trees in regression models. We combined global fecundity data, including a substantial representation of large trees. We compared size–fecundity relationships against traditional allometric scaling with diameter and two models based on crown architecture. All allometric models fail to describe the declining rate of increase in fecundity with diameter found for 80% of 597 species in our analysis. The strong evidence of declining fecundity, beyond what can be explained by crown architectural change, is consistent with physiological decline. A downward revision of projected fecundity of large trees can improve the next generation of forest dynamic models.

 

Effective insect pollination requires appropriate responses to internal and external environmental cues in both the plant and the pollinator.Helianthus annuus, a highly outcrossing species, is marked for its uniform eastward orientation of mature pseudanthia, or capitula. Here we investigate how this orientation affects floral microclimate and the consequent effects on plant and pollinator interactions and reproductive fitness.

We artificially manipulated sunflower capitulum orientation and temperature in both field and controlled conditions and assessed flower physiology, pollinator visits, seed traits and siring success.

East‐facing capitula were found to have earlier style elongation, pollen presentation and pollinator visits compared with capitula manipulated to face west. East‐facing capitula also sired more offspring than west‐facing capitula and under some conditions produced heavier and better‐filled seeds. Local ambient temperature change on the capitulum was found to be a key factor regulating the timing of style elongation, pollen emergence and pollinator visits.

These results indicate that eastward capitulum orientation helps to control daily rhythms in floral temperature, with direct consequences on the timing of style elongation and pollen emergence, pollinator visitation, and plant fitness.