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Discrete time structured population projection models are an important tool for studying population dynamics. Within this field, Integral Projection Models (IPMs) have become a popular method for studying populations structured by continuously distributed traits (e.g. height, weight). Databases of discrete time, discrete state structured population models, for example DATLife (life tables) and COMPADRE & COMADRE (matrix population models), have made quantitative syntheses straightforward to implement. These efforts allow researchers to address questions in both basic and applied ecology and evolutionary biology. There are now over 300 peer-reviewed publications containing IPMs. We describe a novel framework to quickly reconstruct these models for subsequent analyses using Rpadrino R package, which serves as an interface to PADRINO, a new database of structured population models.We introduce an R package, Rpadrino, which enables users to download, subset, reconstruct, and extend published IPMs. Rpadrino makes use of recently created software, ipmr, to provide an engine to reconstruct a wide array of IPMs from their symbolic representations and conduct subsequent analyses. Rpadrino and ipmr are extensively documented to help users learn their usage.Rpadrino currently enables users to reconstruct 280 IPMs from 40 publications that describe the demography of 14 animal and 26 plant species. All of these IPMs are tested to ensure they reproduce published estimates. Rpadrino provides an interface to augment PADRINO with external data and modify parameter values, creating a platform to extend models beyond their original purpose while retaining full reproducibility.PADRINO and Rpadrino provide a toolbox for asking new questions and conducting syntheses with peer-reviewed published IPMs. Rpadrino provides a user-friendly interface so researchers do not need to worry about the database structure or syntax, and can focus on their research questions and analyses. Additionally, Rpadrino is thoroughly documented, and provides numerous examples of how to perform analyses which are not included in the package’s functionality.

Understanding the effects of climate on the vital rates (e.g., survival, development, reproduction) and dynamics of natural populations is a long-standing quest in ecology, with ever-increasing relevance in the face of climate change. However, linking climate drivers to demographic processes requires identifying the appropriate time windows during which climate influences vital rates. Researchers often do not have access to the long-term data required to test a large number of windows, and are thus forced to make a priori choices. In this study, we first synthesize the literature to assess current a priori choices employed in studies performed on 104 plant species that link climate drivers with demographic responses. Second, we use a sliding-window approach to investigate which combination of climate drivers and temporal window have the best predictive ability for vital rates of four perennial plant species that each have over a decade of demographic data (Helianthella quinquenervis, Frasera speciosa, Cylindriopuntia imbricata, and Cryptantha flava). Our literature review shows that most studies consider time windows in only the year preceding the measurement of the vital rate(s) of interest, and focus on annual or growing season temporal scales. In contrast, our sliding-window analysis shows that in only four out of 13 vital rates the selected climate drivers have time windows that align with, or are similar to, the growing season. For many vital rates, the best window lagged more than 1 year and up to 4 years before the measurement of the vital rate. Our results demonstrate that for the vital rates of these four species, climate drivers that are lagged or outside of the growing season are the norm. Our study suggests that considering climatic predictors that fall outside of the most recent growing season will improve our understanding of how climate affects population dynamics.

Understanding the responses of plant populations dynamics to climatic variability is frustrated by the need for long-term datasets that capture demographic responses to a range of climates. Here, we advocate for new studies that prioritize spatial over temporal replication, but without inferring the effect of temporal climatic gradients from spatial climatic gradients – as usually done in the so called “space-for-time substitutions”. Rather, we advocate to estimate the effects of climate by sampling replicate populations in locations with similar climate. We first use data analysis on spatial locations in the conterminous USA to assess how far apart spatial replicates should be from each other to minimize temporal correlations in climate. We find that spatial locations separated by 250 Km have moderate (0.5) correlations in annual precipitation. Second, we use simulations to demonstrate that spatial replication can lead to substantial gains in the range of climates sampled during a given set of years so long as the climate correlations between the populations are at low to moderate levels. Third, we use simulations to quantify how many spatial replicates would be necessary to achieve the same statistical power of a single-population, long-term data set under different strengths and directions of spatial correlations in climate between spatial replicates. Our results indicate that spatial replication is an untapped opportunity to study the effects of climate on demography and to rapidly fill important knowledge gaps in the field of population ecology.

Integral projection models (IPMs) are an important tool for studying the dynamics of populations structured by one or more continuous traits (e.g. size, height, color). Researchers use IPMs to investigate questions ranging from linking drivers to plant population dynamics, planning conservation and management strategies, and quantifying selective pressures in natural populations. The popularity of stage-structured population models has been supported by R scripts and packages (e.g.IPMpack, popbio, popdemo, lefko3) aimed at ecologists, which have introduced a broad repertoire of functionality and outputs. However, pressing ecological, evolutionary, and conservation biology topics require developing more complex IPMs, and considerably more expertise to implement them. Here, we introduce ipmr, a flexible R package for building, analyzing, and interpreting IPMs.The ipmr framework relies on the mathematical notation of the models to express them in code format. Additionally, this package decouples the model parameterization step from the model implementation step. The latter point substantially increases ipmr’s flexibility to model complex life cycles and demographic processes.ipmr can handle a wide variety of models, including density dependence, discretely and continuously varying stochastic environments, and multiple continuous and/or discrete traits. ipmr can accommodate models with individuals cross-classified by age and size. Furthermore, the package provides methods for demographic analyses (e.g. asymptotic and stochastic growth rates) and visualization (e.g. kernel plotting).ipmr is a flexible R package for integral projection models. The package substantially reduces the amount of time required to implement general IPMs. We also provide extensive documentation with six vignettes and help files, accessible from an R session and online.

The effects of floral species composition on offspring performance of solitary bees are rarely studied under conditions where foraging behaviour of mothers is allowed to play a role. In a semi-field experiment, we restricted foraging choices of the polylectic mason bee . Osmia bicornis L. to flower species belonging to plant families presumably used to different extent: . Borago officinalis L. (Boraginaceae), . Centaurea cyanus L. (Asteraceae) and . Brassica napus L. (Brassicaceae). We quantified the foraging behaviour and brood cell production by mother bees, and compared the quality of offspring in pure and mixed flower species stands. Offspring survival in pure stands was expected to reflect the mothers' foraging preferences in the mixed stand. Pure stands of . B. napus supported highest offspring survival, body mass and fraction of females produced. Offspring survival on . C. cyanus and . B. officinalis was very low. Larval mortality occurred earlier in brood cells provided with . B. officinalis pollen than in brood cells provided with . C. cyanus pollen suggesting different effects of pollen quality on early larval and later development. The time spent on different foraging activities correlated with lifetime reproductive output. However, in mixed stands, the proportion of time the bees were foraging on the different flower species did not differ significantly. Foraging behaviour may therefore not generally be a good proxy for the quality of floral resources for offspring production. Our results suggest that resources collected from one plant species may influence the usefulness of resources from another plant species. Bees may therefore overcome potentially deleterious effects of the suboptimal resources by mixing low- and high-quality resources. This may help generalist bees, such as . O. bicornis, to cope with an unpredictable environment. Die Effekte der Artenzusammensetzung von blühenden Pflanzen auf das Gedeihen der Nachkommen von solitären Bienen werden selten unter Bedingungen untersucht, die zulassen, dass das Sammelverhalten der Mütter eine Rolle spielt. In einem Semi-Freilandexperiment, beschränkten wir die Sammeloptionen der polylektischen Mauerbiene . Osmia bicornis L. auf Blütenarten aus vermutlich unterschiedlich stark genutzten Familien: . Borago officinalis L. (Boraginaceae), . Centaurea cyanus L. (Asteraceae) und . Brassica napus L. (Brassicaceae). Wir bestimmten das Sammelverhalten und die Brutzellenproduktion von Bienenweibchen und verglichen die Qualität der Nachkommen bei reinem und gemischtem Blütenangebot. Die Überlebensrate der Nachkommen bei Angebot von nur einer Blütenart sollte die Präferenz der Mütter in gemischten Blütenbeständen wiederspiegeln. Reine Bestände von . B. napus ergaben die höchste Überlebensrate, Körpermasse und den höchsten Weibchenanteil bei den Nachkommen. Bei . C. cyanus und . B. officinalis war die Überlebensrate sehr gering. Die Larvensterblichkeit setzte in mit . B. officinalis verproviantierten Brutzellen früher ein als in Brutzellen mit . C. cyanus als Proviant. Somit sollte es unterschiedliche Effekte der Pollenqualität auf die frühe larvale und die spätere Entwicklung geben. Die für die verschiedenen Sammelaktivitäten aufgewendete Zeit korrelierte mit der Gesamtproduktion an Nachkommen einer Mutterbiene. Indessen unterschieden sich die Zeitanteile, die bei gemischtem Angebot mit dem Sammeln an unterschiedlichen Blütenarten verbracht wurden, nicht signifikant voneinander. Das Sammelverhalten könnte deshalb kein guter Indikator für die Qualität von Blütenressourcen für die Produktion von Nachkommen sein. Unsere Ergebnisse legen nahe, dass Ressourcen, die von einer Pflanzenart gesammelt wurden, den Nutzen der Ressourcen von einer anderen Art beeinflussen könnten. Die Bienen könnten somit mögliche abträgliche Effekte einer suboptimalen Ressource durch das Mischen von qualitativ hoch- und minderwertigen Ressourcen kompensieren. Dies könnte Generalisten wie der Mauerbiene . O. bicornis helfen, mit einer nicht vorhersagbaren Umwelt zurechtzukommen.