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1. Scaling from microsite to landscape to resolve litter decomposition dynamics in globally extensive drylands

   https://doi.org/10.1111/1365-2435.70029  

   Throop, Heather L; Li, Jiwei; Moorhead, Daryl L; Reed, Sasha C; Todd‐Brown, Katherine EO; Besser, Alexi C; Bloom, Dellena Evelyn; Ingalls, Thomas C; Cueva, Alejandro (March 2025, Functional Ecology)

   Abstract Decomposition is the transformation of dead organic matter into its inorganic constituents. In most biomes, decomposition rates can be accurately predicted with simple mathematical models, but these models have long under‐predicted decomposition in globally extensive drylands.We posit that the exposed surface conditions characteristic of drylands make litter decomposition uniquely subject to microsite‐specific environmental controls and spatially variable microbial communities. As such, decomposition in dryland ecosystems—which are characterized by extremes in temporal heterogeneity of climate conditions and spatial heterogeneity of vegetation cover with corresponding microclimate variability—is a prime example of a macrosystems process that can be addressed by merging field data with new predictive process models operating across a hierarchical continuum of spatial scales and process resolutions.A macrosystems approach offers promise to reconcile model‐measurement discrepancies by integrating observations and experiments across multiple scales, from microsites (e.g. shrub sub‐canopy or intercanopy) to regions (e.g. across a 100s of km²study site with complex topography, precipitation and temperature) and ultimately to a continental perspective (e.g. North American drylands).Recent developments in technology and data availability position the scientific community to integrate laboratory, field, modelling and remote sensing approaches across a hierarchical range of scales to capture the spatiotemporal distribution of litter and environmental conditions needed to predict decay dynamics at the micro‐to‐macroscale. This multi‐scale approach promises a path forward to resolving a longstanding disconnect between measured data and modelled processes in dryland litter decomposition.Dryland litter decomposition presents an excellent case study for resolving spatially and temporally complex biogeochemical dynamics through a hierarchical, multidisciplinary macrosystems approach.We focus on dryland litter decomposition, but the hierarchical, multidisciplinary macrosystems approach we outline shows great potential for resolving other spatially and temporally complex biogeochemical processes across a wide range of ecosystems. Read the freePlain Language Summaryfor this article on the Journal blog. 

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2. Planktic diatom responses to spatiotemporal environmental variation in high‐mountain tropical lakes

   https://doi.org/10.1111/fwb.14218  

   Luethje, Melina; Mosquera, Pablo V; Hampel, Henrietta; Fritz, Sherilyn C; Benito, Xavier (March 2024, Freshwater Biology)

   Tropical lakes harbour high levels of biodiversity, but the temporal and spatial variability of biological communities are still inadequately characterised, making it difficult to predict the impact of accelerated rates of environmental change in these regions. Our goal was to identify the spatiotemporal dynamics of the planktic diatom community in the Cajas Massif in the tropical Andes.We analysed seasonal diatom and environmental data over a period of 1 year from 10 lakes located in geologically distinct basins and modelled community–environment relationships using multivariate ordination and variation partitioning techniques. Generalised additive models with a full‐subset information theoretic approach also were used to determine which environmental variables explain single‐species abundance.Although the lakes are monomictic and thus have variable thermal structure across the year, seasonal variability of water chemistry conditions was negligible, and seasonal differences in diatom community composition were small. Across space, diatom community composition was correlated primarily with ionic content (divalent cations and alkalinity), related to bedrock composition, and secondly with lake thermal structure and productivity. The ionic gradient overrode the effect of the thermal structure–productivity gradient at the diatom community level, whereas individual diatom species responded more sensitively to variables related to in‐lake and catchment productivity, including chlorophyll‐aand iron, and the proportion of wetlands in the catchment.Our results indicate that the spatiotemporal variability of Cajas lakes and their diatom communities is the result of multiple intertwined environmental factors. The emergence of the ionic and thermal structure–productivity gradients in a rather small tropical lake district suggests segregation of ecological niches for diatoms that also may be important in other high‐elevation lake regions. Future studies that track tropical Andean lakes under natural and anthropogenically mediated change, both in contemporary times and in palaeoenvironmental reconstructions, would benefit from the modelling approach (community and species levels) developed here. 

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3. A new flow path: eDNA connecting hydrology and biology

   https://doi.org/10.1002/wat2.1749  

   URycki, Dawn R; Kirtane, Anish A; Aronoff, Rachel; Avila, Colton C; Blackman, Rosetta C; Carraro, Luca; Evrard, Olivier; Good, Stephen P; Hoyos_J, Diana C; López‐Rodríguez, Nieves; et al (July 2024, WIREs Water)

   Abstract Environmental DNA (eDNA) has revolutionized ecological research, particularly for biodiversity assessment in various environments, most notably aquatic media. Environmental DNA analysis allows for non‐invasive and rapid species detection across multiple taxonomic groups within a single sample, making it especially useful for identifying rare or invasive species. Due to dynamic hydrological processes, eDNA samples from running waters may represent biodiversity from broad contributing areas, which is convenient from a biomonitoring perspective but also challenging, as hydrological knowledge is required for meaningful biological interpretation. Hydrologists could also benefit from eDNA to address unsolved questions, particularly concerning water movement through catchments. While naturally occurring abiotic tracers have advanced our understanding of water age distribution in catchments, for example, current geochemical tracers cannot fully elucidate the timing and flow paths of water through landscapes. Conversely, biological tracers, owing to their immense diversity and interactions with the environment, could offer more detailed information on the sources and flow paths of water to the stream. The informational capacity of eDNA as a tracer, however, is determined by the ability to interpret the complex biological heterogeneity at a study site, which arguably requires both biological and hydrological expertise. As eDNA data has become increasingly available as part of biomonitoring campaigns, we argue that accompanying eDNA surveys with hydrological observations could enhance our understanding of both biological and hydrological processes; we identify opportunities, challenges, and needs for further interdisciplinary collaboration; and we highlight eDNA's potential as a bridge between hydrology and biology, which could foster both domains. This article is categorized under:Science of Water > Hydrological ProcessesScience of Water > MethodsWater and Life > Nature of Freshwater Ecosystems 

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4. spAbundance: An R package for single‐species and multi‐species spatially explicit abundance models

   https://doi.org/10.1111/2041-210X.14332  

   Doser, Jeffrey W; Finley, Andrew O; Kéry, Marc; Zipkin, Elise F (June 2024, Methods in Ecology and Evolution)

   Abstract Numerous modelling techniques exist to estimate abundance of plant and animal populations. The most accurate methods account for multiple complexities found in ecological data, such as observational biases, spatial autocorrelation, and species correlations. There is, however, a lack of user‐friendly and computationally efficient software to implement the various models, particularly for large data sets.We developed thespAbundance Rpackage for fitting spatially explicit Bayesian single‐species and multi‐species hierarchical distance sampling models, N‐mixture models, and generalized linear mixed models. The models within the package can account for spatial autocorrelation using Nearest Neighbour Gaussian Processes and accommodate species correlations in multi‐species models using a latent factor approach, which enables model fitting for data sets with large numbers of sites and/or species.We provide three vignettes and three case studies that highlightspAbundancefunctionality. We used spatially explicit multi‐species distance sampling models to estimate density of 16 bird species in Florida, USA, an N‐mixture model to estimate black‐throated blue warbler (Setophaga caerulescens) abundance in New Hampshire, USA, and a spatial linear mixed model to estimate forest above‐ground biomass across the continental USA.spAbundanceprovides a user‐friendly, formula‐based interface to fit a variety of univariate and multivariate spatially explicit abundance models. The package serves as a useful tool for ecologists and conservation practitioners to generate improved inference and predictions on the spatial drivers of abundance in populations and communities. 

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5. A life‐history spectrum of population responses to simultaneous change in climate and land use

   https://doi.org/10.1111/1365-2656.13919  

   Buderman, Frances E; Devries, James H; Koons, David N (June 2023, Journal of Animal Ecology)

   Abstract Climate and land use change are two of the primary threats to global biodiversity; however, each species within a community may respond differently to these facets of global change. Although it is typically assumed that species use the habitat that is advantageous for survival and reproduction, anthropogenic changes to the environment can create ecological traps, making it critical to assess both habitat selection (e.g. where species congregate on the landscape) and the influence of selected habitats on the demographic processes that govern population dynamics.We used a long‐term (1958–2011), large‐scale, multi‐species dataset for waterfowl that spans the United States and Canada to estimate species‐specific responses to climate and land use variables in a landscape that has undergone significant environmental change across space and time. We first estimated the effects of change in climate and land use variables on habitat selection and population dynamics for nine species. We then hypothesized that species‐specific responses to environmental change would scale with life‐history traits, specifically: longevity, nesting phenology and female breeding site fidelity.We observed species‐level heterogeneity in the demographic and habitat selection responses to climate and land use change, which would complicate community‐level habitat management. Our work highlights the importance of multi‐species monitoring and community‐level analysis, even among closely related species.We detected several relationships between life‐history traits, particularly nesting phenology, and species' responses to environmental change. One species, the early‐nesting northern pintail (Anas acuta), was consistently at the extreme end of responses to land use and climate predictors and has been a species of conservation concern since their population began to decline in the 1980s. They, and the blue‐winged teal, also demonstrated a positive habitat selection response to the proportion of cropland on the landscape that simultaneously reduced abundance the following year, indicative of susceptibility to ecological traps.By distilling the diversity of species' responses to environmental change within a community, our methodological approach and findings will help improve predictions of community responses to global change and can inform multi‐species management and conservation plans in dynamic landscapes that are based on simple tenets of life‐history theory. 

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