Dynamics of stored lipids in fall migratory monarch butterflies (Danaus plexippus): Nectaring in northern Mexico allows recovery from droughts at higher latitudes.

The eastern population of the North American monarch butterfly (Danaus plexippus) overwinters from November through March in the high-altitude (3000 m+) forests of central Mexico during which time they rely largely on stored lipids. These are acquired during larval development and the conversion of sugars from floral nectar by adults. We sampled fall migrant monarchs from southern Canada through the migratory route to two overwintering sites in 2019 (n = 10 locations), 2020 (n = 8 locations) and 2021 (n = 7 locations). Moderate to extreme droughts along the migratory route were expected to result in low lipid levels in overwintering monarchs but our analysis of lipid levels of monarchs collected at overwintering sites indicated that in all years most had high levels of lipids prior to winter. Clearly, a significant proportion of lipids were consistently acquired in Mexico during the last portion of the migration. Drought conditions in Oklahoma, Texas and northern Mexico in 2019 resulted in the lowest levels of lipid mass and wing loading observed in that year but with higher levels at locations southward in Mexico to the overwintering sites. Compared with 2019, lipid levels increased during the 2020 and 2021 fall migrations but were again higher during the Mexican portion of the migration than for Oklahoma and Texas samples, emphasizing a recovery of lipids as monarchs advanced toward the overwintering locations. In all 3 years, body water was highest during the Canada-USA phase of migration but then declined during the nectar foraging phase in Mexico before recovering again at the overwintering sites. The increase in mass and lipids from those in Texas to the overwintering sites in Mexico indicates that nectar availability in Mexico can compensate for poor conditions experienced further north. Our work emphasizes the need to maintain the floral and therefore nectar resources that fuel both the migration and storage of lipids throughout the entire migratory route.

Trait-based aerial dispersal of arbuscular mycorrhizal fungi.

Dispersal is a key process driving local-scale community assembly and global-scale biogeography of plant symbiotic arbuscular mycorrhizal (AM) fungal communities. A trait-based approach could improve predictions regarding how AM fungal aerial dispersal varies by species. We conducted month-long collections of aerial AM fungi for 12 consecutive months in an urban mesic environment at heights of 20 m. We measured morphological functional traits of collected spores and assessed aerial AM fungal community structure both morphologically and with high-throughput sequencing. Large numbers of AM fungal spores were present in the air over the course of one year and these spores exhibited traits that facilitate aerial dispersal. Measured aerial spores were smaller than average for Glomeromycotinan fungi. Trait-based predictions indicate that nearly 1/3 of described species from diverse genera demonstrate the potential for aerial dispersal. Diversity of aerial AM fungi was relatively high (20 spore species and 17 virtual taxa) and both spore abundance and community structure shifted temporally. The prevalence of aerial dispersal in AM fungi is perhaps greater than previously indicated and a hypothesized model of AM fungal aerial dispersal mechanisms is presented. Anthropogenic soil impacts may liberate AM fungal propagules initiating the dispersal of ruderal species.

The geography of spatial synchrony.

Spatial synchrony, defined as correlated temporal fluctuations among populations, is a fundamental feature of population dynamics, but many aspects of synchrony remain poorly understood. Few studies have examined detailed geographical patterns of synchrony; instead most focus on how synchrony declines with increasing linear distance between locations, making the simplifying assumption that distance decay is isotropic. By synthesising and extending prior work, we show how geography of synchrony, a term which we use to refer to detailed spatial variation in patterns of synchrony, can be leveraged to understand ecological processes including identification of drivers of synchrony, a long-standing challenge. We focus on three main objectives: (1) showing conceptually and theoretically four mechanisms that can generate geographies of synchrony; (2) documenting complex and pronounced geographies of synchrony in two important study systems; and (3) demonstrating a variety of methods capable of revealing the geography of synchrony and, through it, underlying organism ecology. For example, we introduce a new type of network, the synchrony network, the structure of which provides ecological insight. By documenting the importance of geographies of synchrony, advancing conceptual frameworks, and demonstrating powerful methods, we aim to help elevate the geography of synchrony into a mainstream area of study and application.

Soy moratorium impacts on soybean and deforestation dynamics in Mato Grosso, Brazil.

Previous research has established the usefulness of remotely sensed vegetation index (VI) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) to characterize the spatial dynamics of agriculture in the state of Mato Grosso (MT), Brazil. With these data it has become possible to track MT agriculture, which accounts for ~85% of Brazilian Amazon soy production, across periods of several years. Annual land cover (LC) maps support investigation of the spatiotemporal dynamics of agriculture as they relate to forest cover and governance and policy efforts to lower deforestation rates. We use a unique, spatially extensive 9-year (2005-2013) ground reference dataset to classify, with approximately 80% accuracy, MODIS VI data, merging the results with carefully processed annual forest and sugarcane coverages developed by Brazil's National Institute for Space Research to produce LC maps for MT for the 2001-2014 crop years. We apply the maps to an evaluation of forest and agricultural intensification dynamics before and after the Soy Moratorium (SoyM), a governance effort enacted in July 2006 to halt deforestation for the purpose of soy production in the Brazilian Amazon. We find the pre-SoyM deforestation rate to be more than five times the post-SoyM rate, while simultaneously observing the pre-SoyM forest-to-soy conversion rate to be more than twice the post-SoyM rate. These observations support the hypothesis that SoyM has played a role in reducing both deforestation and subsequent use for soy production. Additional analyses explore the land use tendencies of deforested areas and the conceptual framework of horizontal and vertical agricultural intensification, which distinguishes production increases attributable to cropland expansion into newly deforested areas as opposed to implementation of multi-cropping systems on existing cropland. During the 14-year study period, soy production was found to shift from predominantly single-crop systems to majority double-crop systems.

Automated riverine landscape characterization: GIS-based tools for watershed-scale research, assessment, and management.

River systems consist of hydrogeomorphic patches (HPs) that emerge at multiple spatiotemporal scales. Functional process zones (FPZs) are HPs that exist at the river valley scale and are important strata for framing whole-watershed research questions and management plans. Hierarchical classification procedures aid in HP identification by grouping sections of river based on their hydrogeomorphic character; however, collecting data required for such procedures with field-based methods is often impractical. We developed a set of GIS-based tools that facilitate rapid, low cost riverine landscape characterization and FPZ classification. Our tools, termed RESonate, consist of a custom toolbox designed for ESRI ArcGIS®. RESonate automatically extracts 13 hydrogeomorphic variables from readily available geospatial datasets and datasets derived from modeling procedures. An advanced 2D flood model, FLDPLN, designed for MATLAB® is used to determine valley morphology by systematically flooding river networks. When used in conjunction with other modeling procedures, RESonate and FLDPLN can assess the character of large river networks quickly and at very low costs. Here we describe tool and model functions in addition to their benefits, limitations, and applications.

Regional vegetation die-off in response to global-change-type drought.

Future drought is projected to occur under warmer temperature conditions as climate change progresses, referred to here as global-change-type drought, yet quantitative assessments of the triggers and potential extent of drought-induced vegetation die-off remain pivotal uncertainties in assessing climate-change impacts. Of particular concern is regional-scale mortality of overstory trees, which rapidly alters ecosystem type, associated ecosystem properties, and land surface conditions for decades. Here, we quantify regional-scale vegetation die-off across southwestern North American woodlands in 2002-2003 in response to drought and associated bark beetle infestations. At an intensively studied site within the region, we quantified that after 15 months of depleted soil water content, >90% of the dominant, overstory tree species (Pinus edulis, a piñon) died. The die-off was reflected in changes in a remotely sensed index of vegetation greenness (Normalized Difference Vegetation Index), not only at the intensively studied site but also across the region, extending over 12,000 km2 or more; aerial and field surveys confirmed the general extent of the die-off. Notably, the recent drought was warmer than the previous subcontinental drought of the 1950s. The limited, available observations suggest that die-off from the recent drought was more extensive than that from the previous drought, extending into wetter sites within the tree species' distribution. Our results quantify a trigger leading to rapid, drought-induced die-off of overstory woody plants at subcontinental scale and highlight the potential for such die-off to be more severe and extensive for future global-change-type drought under warmer conditions.