Minnesota Department of Natural Resources

The capacity of nutrient-limited forests to enhance carbon (C) sequestration under elevated CO2 (eCO2) remains a critical uncertainty in C cycle modeling. While existing evidence suggests that low phosphorus (P) bioavailability may constrain CO2 fertilization effects on plant growth, the extent to which this limitation modulates ecosystem responses to eCO2 in forests adapted to P-deficient soils remains poorly understood. Here, using eight P-enabled models, we simulated the magnitudes and mechanisms through which P bioavailability interacts with eCO2, emulating an ecosystem-scale P enrichment experiment at a P-limited Eucalyptus forest undergoing long-term Free-Air CO2 Enrichment. While models predicted pronounced P effects on tree growth, P enrichment unexpectedly did not increase the CO2 effects on tree growth and ecosystem C sequestration. Models prioritized either CO2-driven or P-driven growth, but rarely both. This tradeoff emerged due to model-specific assumptions on 1) partitioning of the extra P in soil labile versus nonlabile pools; 2) plant photosynthetic acclimation to P deficiency; 3) C and nutrient use strategies regulating plant size and allocation; and 4) microbial-driven soil decomposition processes. By generating divergent yet biologically plausible outcomes, these predictions establish critical testable hypotheses for empirical research and highlight multiple P-related pathways that may influence the future land C sink.

The goldfish, a member of the Cyprinidae (minnow family) is an important and relevant model for understanding how fish function and reproduce and can be better managed. Here, we review recent studies of this species and its strengths as a model system. First, we review current understanding of how its neuroendocrine system regulates gonadotropin release, and then steroidogenesis and finally gonadal maturation in both males and females. Endocrine determinants of gender and sexual plasticity are described. Effects of the fish androgen, 11-ketotestosterone, on sexual and spawning behavior of males and females are reviewed. We also describe how several hormones (androstenedione, 17,20β-dihydroxy-4-pregen-3-one, prostaglandin F2α) and their metabolites function as "hormonal pheromones" to synchronize male-female spawning behavior and physiology. Insight provided by the goldfish has enhanced understanding of the neurobiology, toxicology, and comparative physiology of other fishes and provided lessons applicable to the culture of commercial carp and the control of invasive species, as well as conservation.

Earthworms play a dual role in the global carbon cycle: they accelerate organic matter decomposition yet are often associated with greater soil organic carbon (SOC) storage. However, uncertainty regarding the mechanisms and magnitudes through which earthworms concurrently influence SOC mineralization and stabilization has limited the integration of soil fauna into carbon models. Here, we synthesize 696 paired observations from 122 studies worldwide to resolve this uncertainty. On average, earthworms increase SOC by 5.4% (95% CI: 2.2%-9.1%), with effects strengthening over time under sustained plant-derived carbon inputs. Earthworms enhance mineral-associated organic carbon (MAOC) by 21.2%, while particulate organic carbon (POC) remains unchanged. These patterns suggest that earthworm activity promotes a transition from short-term carbon mineralization to long-term stabilization, likely mediated by the coupling of microbial processing and physical protection. Specifically, epigeic earthworms boost microbial biomass carbon, whereas endogeic species enhance macroaggregate formation, facilitating the incorporation of microbial necromass into MAOC. The magnitude and direction of these effects depend on sustained carbon inputs and earthworm functional type. Collectively, these results reconcile decades of conflicting evidence and provide the first quantitative global synthesis showing that earthworms increased soil carbon over time under sustained plant carbon inputs. This microbial-mineral formation pathway has direct implications for climate-smart land management, soil biodiversity conservation, and the representation of earthworm bioturbation in global carbon models.

Abstract Detecting infectious disease in wildlife is critical for conservation, management of reintroduction programmes, and to reduce the risk of spillover into livestock and humans. However, collecting diagnostic samples from free‐ranging animals is logistically difficult and costly. Many pathogens alter host behaviour, including reductions in movement, suggesting that animal tracking data could offer a way to infer infection status. We develop a modelling framework that links animal movement to disease processes using hidden Markov models (HMMs). Infection status is treated as a hidden (unobserved) state, while movement patterns, such as step lengths and turning angles, serve as state‐dependent observations. This structure is similar to epidemiological compartmental models (‘Susceptible‐Infected‐Recovered; SIR’), allowing movement data to be formally connected to disease progression. We test multiple model formulations, including (1) constrained state transition probabilities to preclude or include recovery, (2) covariate effects to test whether ecological factors influence infection risk and (3) hierarchically structured HMMs (HHMMs) to distinguish movement responses at short and long temporal scales. We apply this framework to GPS movement data from 84 reintroduced scimitar‐horned oryx ( Oryx dammah ) in Chad. During the study period, 38 individuals were confirmed dead and 6 were sampled for pathogens (e.g. Rift Valley Fever, Peste des Petits Ruminants, Babesiosis). Models that included biologically realistic constraints on transitions among infection states successfully detected disease‐associated reductions in movement and aligned with veterinary necropsy and diagnostic reports. Unconstrained models performed poorly, misclassifying individuals and failing to detect disease progression. Simulation results provided further evidence that constrained HMMs can infer susceptible, infected and recovered states under appropriate model specifications. Synthesis and applications . We demonstrate how (H)HMMs can be tailored to different epidemiological scenarios and provide a template workflow for developing and selecting Hidden Markov models to infer disease status from animal movement data. Identifying infection before mortality occurs offers a valuable early‐warning tool for population managers, reduces reliance on difficult and costly field testing and improves surveillance strategies for vulnerable and reintroduced populations.

Professionals working in biological conservation seek to understand, manage, and restore populations of native organisms using many techniques. A common approach for this discipline is using long-term data collections to inform decision making. However, several quantitative issues complicate statistical analysis of monitoring datasets and can reduce the utility of results for conservation decision making. Integrating results from multiple analyses applied to the same dataset (i.e., approaching the same biological problem using different techniques) is one way to address concerns related to field data that violate statistical assumptions. This process allows data analysts, researchers, and managers to assemble insights based on the weight of evidence. Here we tested whether three different statistical techniques [(1) multiple logistic regression on original data, (2) multiple logistic regression on standardized data (i.e., mean of 0 and standard deviation of 1), and (3) random forest analysis] identified a similar hierarchy for selecting natural and anthropogenic habitat regressors. Our examination of how environmental variables affected Plains Minnow (Hybognathus placitus), a state-threatened fish, is relevant to other taxa and locations. We gained useful information from redundancies (i.e., agreements across analyses). New directions also emerged by addressing ambiguities (i.e., disagreements among results across analyses). When multiple analyses were integrated into one ecological story, a clearer interpretation emerged. Viewing different statistical tests as facilitators that provide mutual advantages can advance the understanding and application of statistical analyses applied to non-experimental field datasets.

Soil protists significantly influence ecosystem multifunctionality (EMF) through their roles in microbial predation, parasitism, and organic matter decomposition. However, the multifaceted contributions of protist diversity, along with its interactions with other microbial groups and plant diversity, to EMF-especially under climate-induced stresses such as drought-remain poorly understood. To address this knowledge gap, we conducted a factorial microcosm experiment, manipulating microbial diversity (protists, bacteria and fungi), plant species richness, and drought stress. In total, 203 microcosms were established, generating 812 soil samples and 2436 amplicon sequencing libraries. Using structural equation modelling (SEM) and multiple regression analyses, we found that protist diversity was positively correlated with EMF, carbon sequestration, soil organic matter (SOM) decomposition, and nutrient cycling. Furthermore, protist communities exhibited distinct, phylum-specific relationships with these ecosystem functions. Under drought conditions, microbial interaction networks experienced significant restructuring, with protists emerging as keystone taxa-enhancing protist connectivity and highlighting their central role in ecosystem resilience, especially in relation to leaf carbon dynamics. Our findings provide novel empirical evidence that protists act as multitrophic integrators in soil ecosystems and highlight their role in buffering ecosystems against global environmental change.

Abstract Floral and nesting resources are two major components of habitat specialization that drive patterns of bee distribution. However, nesting resources are largely understudied in comparison to floral resources. For nesting, bees are generally thought to prefer nesting in sandy soils, and numerous species are considered sand specialists. With little empirical evidence to date, we aimed to test how soil sand content and floral resource availability interact to affect patterns of bee distribution and whether sand specialist bees predominantly occur in sandy habitats. We set up a carefully designed observational study in Minnesota, USA, across three classes of soil sand content ( N = 28 plots) using a focal prairie plant species ( Dalea purpurea ) that attracts a wide range of bee species and can grow in different soil types. We identified three key results: (1) soil sand content, not floral resource availability, affected patterns of bee distribution; (2) contrary to expectations, sandier sites did not host the highest diversity of bee species; and (3) there was clear evidence of sand specialization for select bee species, but sand specialists were associated with both moderate and high amounts of sand rather than extremely sandy areas. Our findings highlight that soil properties, specifically soil sand content, can be important in driving patterns of bee distribution, specifically sand specialists. Therefore, not factoring soil properties into bee conservation and restoration decisions may limit our effectiveness and ability to support habitat specialists and rarer bee communities.

Culture, as the filter through which people view the world and a key determinant of human behaviour, is central to the practice of natural resource management and conservation. Conservation is intended to moderate the impacts of human cultural modification of the environment, exists as an endeavour because it is culturally valued, and acts largely through policies to encourage or discourage targeted human behaviours. However, culture is not static; as organisms and ecologies evolve, so too does culture exist as a dynamic, interconnected, coevolving element of the social-ecological systems in which management action is situated and implemented. Cultural evolution (CE) offers a valuable theoretical contribution to the scientific understanding of culture, cultural diversity and culture change and has the potential to be harnessed in the applied research and practice of conservation social science. We illustrate the essential principles necessary to grow an applied science of CE for natural resource management and conservation, and identify opportunities for CE to provide valuable information for science-based decision making and help conservation institutions and organizations adapt to the ongoing challenges posed by culture change. This transdisciplinary integration can contribute to improved outcomes across conservation objectives and build more resilient, sustainable social-ecological systems. This article is part of the theme issue 'Transforming cultural evolution research and its application to global futures'.