Biology subjects

Guzman, L. M.

Publications and source records attributed to Guzman, L. M..

14 recordsLinked to original sources

bioRxiv2026

Large parks and city-wide tree cover boost butterfly diversity across 22 major U.S. cities

Accelerating global urbanization necessitates a better understanding of how to manage cities that promote biodiversity. However, we currently lack multi-year, multi-city studies, which limits a generalizable understanding of how both within and between city differences impact the spatial and temporal dynamics of urban biodiversity. Here, we tested hypotheses about the drivers of butterfly diversity within and across urban parks by applying Bayesian oc-cupancy models to five years of iNaturalist community science data from 2,550 parks in 22 major U.S. cities. We found that cities with bigger parks supported more species per park, including more disturbance- and edge-avoidant species. This was driven by a positive effect of park size on butterfly species colonization rates. We also found that attributes of habitat quality (plant diversity within parks and tree cover surrounding parks) contributed to butter-fly species occupancy. Park connectivity increased species persistence, but the overall effects on butterfly species occupancy varied across cities. Finally, we found that the total area of tree cover throughout a city, rather than the size or connectivity of individual parks, was the primary determinant of city-wide diversity: Increasing total tree canopy cover from below-average ([~] 6%) to above-average ([~] 22%) increased city-wide species richness by[~] 10%. These findings highlight the need for cities to maintain large parks while also increasing city-wide tree cover to support biodiversity across local to regional scales. By integrat-ing high-resolution community science data across the continental U.S., this study provides mechanistic insight into how cross-scale processes shape urban biodiversity dynamics and identifies generalizable recommendations for improving urban conservation management. Significance statementAdvancing urban sustainability hinges on better understanding how to promote biodiver-sity in urban landscapes. Yet, it is largely unclear how urban biodiversity is affected by both within- and between-city differences. Applying Bayesian occupancy models to 5 years of iNaturalist community science butterfly data from 22 U.S. cities, we found that cities with larger parks supported more species per park, including species of higher conservation concern. Simultaneously, increasing city-wide tree canopy cover area, including area both within and outside of parks, increased total city-wide butterfly diversity. Integrating biodi-versity conservation recommendations from this study into urban management planning will reinforce the benefits of participating in community science programs, thereby strengthening positive feedbacks between the health of people and nature.

ecology↗

bioRxiv2026

Local interaction networks reconstructed from global biodiversity data improve pollinator restoration decision making

Global pollinator declines threaten the health of ecosystems and food systems, underscoring the urgency of conservation actions such as habitat restoration. However, data gaps on plant use among pollinators continue to limit reliable design of restoration plant mixes. To address this, we present NECTAR (Network-Enhanced Conservation Tool for Analysis and Recommendation), a new modular framework that integrates multiple data modalities - including species distributions, phenological metrics, and phylogenetic data - to infer flower visitation and host plant interactions from spatial, temporal, and phylogenetic overlap, generating spatially explicit plant-insect interaction networks that guide planting recommendations for pollinator habitat restoration. We demonstrate the utility of NECTAR by generating a large plant-insect metaweb across California, comprising 2,473,729 spatially explicit interactions that included 3,792 pollinator species and 4,363 native plant species. NECTAR achieved high interaction recall across withheld interactions and independent datasets, substantially outperforming null models and matching or exceeding values reported in comparable studies. NECTAR's data-driven plant mix recommendations are predicted to support up to 2.4 times more pollinator species compared to existing resources and random selection of plants. This optimization facilitates the inclusion of multiple goals and constraints, and provides complementary decision-making information to existing resources. NECTAR offers a scalable, evidence-based framework for translating increasingly available global biodiversity data into locally actionable restoration guidance, with broad potential to improve pollinator habitat restoration worldwide.

ecology↗

bioRxiv2026

Winners and Losers Among European Arthropods over the Last Half Century of Global Change

Widespread concern over arthropod declines has raised questions about how global change is reshaping biodiversity, yet large-scale responses within the group remain poorly understood. Here, we analyse 50 years (1970-2019) of European arthropod occurrence data to quantify distributional changes across more than 700 species within 11 taxonomic groups. Using occupancy-detection models that account for imperfect detection, we compare time-only and environmentally mediated trends, including changes to temperature, precipitation, and agricultural and urban land cover. We find no universal signal of decline; responses are highly heterogeneous, revealing distinct winners and losers both within and among groups. Climate variables, particularly temperature and precipitation, are the strongest predictors of change, while agricultural intensification is broadly negative and urbanisation produces group-specific effects. Trait analyses indicate that warm- and dry-affiliated species and larger-bodied arthropods generally fare better. These results show that recent European arthropod change is dominated by redistribution rather than uniform collapse, with important implications for conservation and monitoring under ongoing global change.

ecology↗

bioRxiv2023

Risk assessments underestimate threat of pesticides to wild bees

Ecological risk assessments (ERA) are crucial when developing national strategies to manage adverse effects from pesticide exposure to natural populations. Yet, estimating risk with surrogate species in controlled laboratory studies jeopardizes the ERA process because natural populations exhibit intraspecific variation within and across species. Here, we investigate the extent to which the ERA process misestimates risk from pesticides on different species by conducting a meta-analysis of all records in the ECOTOX Knowledgebase for honey bees and wild bees exposed to neonicotinoids. We found the knowledgebase is largely populated by acute lethality data on the Western honey bee and exhibits within and across species variation in LD50 up to six orders of magnitude from neonicotinoid exposure. We challenge the reliability of surrogate species as predictors when extrapolating pesticide toxicity data to wild pollinators and recommend solutions to address the (a)biotic interactions occurring in nature that make such extrapolations unreliable in the ERA process. SynopsisEcological risk assessments misestimate pesticide threats to pollinators sixfold by overextending acute lethality data on surrogate species to natural populations.

ecology↗

bioRxiv2023

BeeDC: An R package and globally synthesised and flagged bee occurrence dataset

Species occurrence data are foundational for research, conservation, and science communication, but the limited availability and accessibility of reliable data represents a major obstacle, particularly for insects, which face mounting pressures. We present BeeBDC, a new R package, and a global bee occurrence dataset to address this issue. We combined >18.3 million bee occurrence records from multiple public repositories (GBIF, SCAN, iDigBio, USGS, ALA) and smaller datasets, then standardised, flagged, deduplicated, and cleaned the data using the reproducible BeeBDC R-workflow. Specifically, we harmonised species names (following established global taxonomy), country names, and collection dates and we added record-level flags for a series of potential quality issues. These data are provided in two formats, "cleaned" and "flagged-but-uncleaned". The BeeBDC package with online documentation provides end users the ability to modify filtering parameters to address their research questions. By publishing reproducible R workflows and globally cleaned datasets, we can increase the accessibility and reliability of downstream analyses. This workflow can be implemented for other taxa to support research and conservation.

ecology↗

bioRxiv2022

SOCS2 regulation of growth hormone signaling requires a canonical interaction with phosphotyrosine

Suppressor Of Cytokine Signaling (SOCS) 2 is the critical negative regulator of growth hormone (GH) and prolactin signaling. Mice lacking SOCS2 display gigantism with increased body weight and length, and an enhanced response to GH treatment. Here we characterized mice carrying a germ-line R96C mutation within the SOCS2-SH2 domain, which disrupts the ability of SOCS2 to interact with tyrosine phosphorylated targets. Socs2R96C/R96C mice displayed a similar increase in growth as previously observed in SOCS2 null (Socs2-/-) mice, with a proportional increase in body and organ weight, and bone length. Embryonic fibroblasts isolated from Socs2R96C/R96C and Socs2-/- mice also showed a comparable increase in phosphorylation of STAT5 following GH stimulation, indicating the critical role of phosphotyrosine binding in SOCS2 function.

cell biology↗

bioRxiv2022

Macroecological variation in movement profiles: body size does not explain it all

Animals couple habitats by three types of movement: dispersal, migration, and foraging, which dynamically link populations, communities, and ecosystems. Spatial distances of movement tend to correlate with each other, reflecting shared allometric scaling with body size, but may diverge due to biomechanical, phylogenetic, and ecological constraints. While these constraints have been investigated within specific taxa, the macroecological and macroevolutionary constraints on movement distances, and causes of those constraints, are still unknown. Here, we synthesized distances of all three movement types across 300+ vertebrate species, and investigated how the relationships between movement types and body size were modified by movement medium, taxonomy, and trophic guild (carnivore, herbivore, etc.). We found that the strength of relationships between movement types and body size varied among environments, taxa, and trophic guilds. Movement profiles interacted with physiological, taxonomic, and ecological traits to depart from expected body mass scaling. Overall, we find that there are systematic patterns to movement distances, and that movement types with very distinct ecological consequences (foraging, migration) can be correlated and subject to similar constraints. This implies that the scales of population dynamics in ecological communities are not entirely determined by the environment and likely reflect general biomechanical, evolutionary and metabolic constraints.

ecology↗

bioRxiv2021

Utilizing occupancy-detection models with museum specimen data: promise and pitfalls

Historical museum records provide potentially useful data for identifying drivers of change in species occupancy. However, because museum records are typically obtained via many collection methods, methodological developments are needed in order to enable robust inferences. Occupancy-detection models, a relatively new and powerful suite of methods, are a potentially promising avenue because they can account for changes in collection effort through space and time. Here we present a methodological road-map for using occupancy models to analyze historical museum records. We use simulated data-sets to identify how and when patterns in data and/or modelling decisions can bias inference. We focus primarily on the consequences of contrasting methodological approaches for dealing with species ranges and inferring species non-detections in both space and time. We find that not all data-sets are suitable for occupancy-detection analysis but, under the right conditions (namely, data-sets that span long durations and contain a high fraction of community-wide collections, or collection events that focus on communities of organisms), models can accurately estimate trends. Finally, we present a case-study on eastern North American odonates where we calculate long-term trends of occupancy by using our most robust workflow.

ecology↗

bioRxiv2020

Climate influences the response of community functional traits to local conditions

Functional traits determine an organisms performance in a given environment and as such determine which organisms will be found where. Species respond to local conditions, but also to larger scale gradients, such as climate. Trait ecology links these responses of species to community composition and species distributions. Yet, we often do not know which environmental gradients are most important in determining community trait composition at either local or biogeographical scales, or their interaction. Here we quantify the relative contribution of local and climatic conditions to the structure and composition of functional traits found within bromeliad invertebrate communities. We conclude that climate explains more variation in invertebrate trait composition within bromeliads than does local conditions. Importantly, climate mediated the response of traits to local conditions; for example, invertebrates with benthic life-history traits increased with bromeliad water volume only under certain precipitation regimes. Our ability to detect this and other patterns hinged on the compilation of multiple fine-grained datasets, allowing us to contrast the effect of climate vs. local conditions. We suggest that, in addition to sampling communities at local scales, we need to aggregate studies that span large ranges in climate variation in order to fully understand trait filtering at local, regional and global scales.

ecology↗

bioRxiv2020

Phenology and Robustness in plant-pollinator networks

Many metrics that describe the structure of mutualistic plant-pollinator networks have been found to be important for network stability and robustness. These metrics are impacted by a suite of variables, including species traits, species abundances, their spatial configuration, and their phylogenetic history. Here, we consider a specific trait, phenology, or the timing of life history events. We expect that timing and duration of activity of pollinators, or of flowering in plants, could greatly affect the structure of the networks in which they are embedded. Using plant-pollinator networks from 33 sites in southern British Columbia, Canada, we asked a) how phenological species traits, specifically timing of first appearance in the network and duration of activity in a network, were related to network structure, and b) how those traits affected network robustness to phenologically biased species loss. We found that long duration of activity increased connection within modules for both pollinators and plants and among modules for plants. We also found that date of first appearance was positively related to interaction strength asymmetry in plants but negatively related in pollinators. Networks were generally more robust to the loss of pollinators than plants, but robustness declined with loss of early-flying or long-duration pollinators. These pollinators tended to be among-module connectors. Our results show that changes in phenology have the potential to impact plant-pollinator networks, which may have conservation relevance in a time of changing climate.

ecology↗

bioRxiv2020

Closing the research-implementation gap using data science tools: a case study with pollinators of British Columbia

A challenge in conservation is the gap between knowledge generated by researchers and the information being used to inform conservation practice. This gap, widely known as the research-implementation gap, can limit the effectiveness of conservation practice. One way to address this is to design conservation tools that are easy for practitioners to use. Here, we implement data science methods to develop a tool to aid in conservation of pollinators in British Columbia. Specifically, in collaboration with Pollinator Partnership Canada, we jointly develop an interactive web app, the goal of which is two-fold: (i) to allow end users to easily find and interact with the data collected by researchers on pollinators in British Columbia (prior to development of this app, data were buried in supplements from individual research publications) and (ii) employ up to date statistical tools in order to analyse phenological coverage of a set of plants. Previously, these tools required high programming competency in order to access. Our app provides an example of one way that we can make the products of academic research more accessible to conservation practitioners. We also provide the source code to allow other developers to develop similar apps suitable for their data.

ecology↗

bioRxiv2020

Disentangling metacommunity processes using multiple metrics in space and time

Metacommunity ecology has focused on using observational and analytical approaches to disentangle the role of critical assembly processes, such as dispersal limitation and environmental filtering. Many methods have been proposed for this purpose, most notably multivariate analyses of species abundance and its association with variation in spatial and environmental conditions. These approaches tend to focus on few emergent properties of metacommunities and have largely ignored temporal community dynamics. By doing so, these are limited in their ability to differentiate metacommunity dynamics. Here, we develop a Virtual ecologist approach to evaluate critical metacommunity assembly processes based on a number of summary statistics of community structure across space and time. Specifically, we first simulate metacommunities emphasizing three main processes that underlie metacommunity dynamics (density-independent responses to abiotic conditions, density-dependent biotic interactions, and dispersal). We then calculate a number of commonly used summary statistics of community structure in space and time, and use random forests to evaluate their utility for understanding the strength of these three processes. We found that: (i) time series are necessary to disentangle metacommunity processes, (ii) each of the three studied processes is distinguished with different descriptors, (iii) each summary statistic is differently sensitive to temporal and spatial sampling effort. Some of the most useful statistics include the coefficient of variation of abundances through time and metrics that incorporate variation in the relative abundances (evenness) of species. Surprisingly, we found that when we only used a single snapshot of community variation in space, the most commonly used approaches based on variation partitioning were largely uninformative regarding assembly processes, particularly, variation in dispersal. We conclude that a combination of methods and summary statistics will be necessary to understand the processes that underlie metacommunity assembly through space and time.

ecology↗

bioRxiv2019

A process-based framework for metacommunity ecology

The metacommunity concept has the potential to integrate local and regional dynamics within a general community ecology framework. To this end, the concept must move beyond the discrete archetypes that have largely defined it (e.g. neutral vs. species sorting) and better incorporate local scale species interactions and coexistence mechanisms. Here, we present a fundamental reconception of the framework that explicitly links local coexistence theory to the spatial processes inherent to metacommunity theory, allowing for a continuous range of competitive community dynamics. These dynamics emerge from the three underlying processes that shape ecological communities: 1) density-independent responses to abiotic conditions, 2) density-dependent biotic interactions, and 3) dispersal. Stochasticity is incorporated in the demographic realization of each of these processes. We formalize this framework using a simulation model that explores a wide range of competitive metacommunity dynamics by varying the strength of the underlying processes. Using this model and framework, we show how existing theories, including the traditional metacommunity archetypes, are linked by this common set of processes. We then use the model to generate new hypotheses about how the three processes combine to interactively shape diversity, functioning, and stability within metacommunities. Statement of authorshipThis project was conceived at the sTURN working group, of which all authors are members. PLT developed the framework and model with input from all authors. PLT wrote the model code. PLT and LMG performed the simulations. PLT produced the figures and wrote the first draft with input from LMG and JMC. All authors provided feedback and edits on several versions of the manuscript. Data accessibilityAll code for running the simulation model and producing the figures is archived on Zenodo - https://doi.org/10.5281/zenodo.3833035.

ecology↗

bioRxiv2018

Food web networks shift across a precipitation gradient due to changes in community composition and species interactions.

Ecological networks change across spatial and environmental gradients due to (i) changes in species composition or (ii) changes in the frequency or strength of interactions. Here we use the communities of aquatic invertebrates inhabiting clusters of bromeliad phytotelms along the Brazilian coast as a model system for examining turnover in the properties of ecological networks. We first document the variation in the species pools of sites across a geographical climate gradient. Using the same sites, we also explored the geographic variation in species interaction strength using a newly developed Markov network approach. We found that community composition differed along a gradient of water volume within bromeliads due to the turnover of some species. From the Markov network analysis, we found that the top-down effects of certain predators differed geographically, which could also be explained by geographic differences in bromeliad water volumes. Overall, this study illustrates how a network can change across an environmental gradient through both changes in both species and their interactions.

ecology↗