State changes: insights from the U.S. Long Term Ecological Research Network

Heat and desiccation tolerances predict bee abundance under climate change

Climate change could pose an urgent threat to pollinators, with critical ecological and economic consequences. However, for most insect pollinator species, we lack the long-term data and mechanistic evidence that are necessary to identify climate-driven declines and predict future trends. Here we document 16 years of abundance patterns for a hyper-diverse bee assemblage1 in a warming and drying region2, link bee declines with experimentally determined heat and desiccation tolerances, and use climate sensitivity models to project bee communities into the future. Aridity strongly predicted bee abundance for 71% of 665 bee populations (species × ecosystem combinations). Bee taxa that best tolerated heat and desiccation increased the most over time. Models forecasted declines for 46% of species and predicted more homogeneous communities dominated by drought-tolerant taxa, even while total bee abundance may remain unchanged. Such community reordering could reduce pollination services, because diverse bee assemblages typically maximize pollination for plant communities3. Larger-bodied bees also dominated under intermediate to high aridity, identifying body size as a valuable trait for understanding how climate-driven shifts in bee communities influence pollination4. We provide evidence that climate change directly threatens bee diversity, indicating that bee conservation efforts should account for the stress of aridity on bee physiology.

Quantifying ecosystem states and state transitions of the Upper Mississippi River System using topological data analysis

Aquatic systems worldwide can exist in multiple ecosystem states (i.e., a recurring collection of biological and chemical attributes), and effectively characterizing multidimensionality will aid protection of desirable states and guide rehabilitation. The Upper Mississippi River System is composed of a large floodplain river system spanning 2200 km and multiple federal, state, tribal and local governmental units. Multiple ecosystem states may occur within the system, and characterization of the variables that define these ecosystem states could guide river rehabilitation. We coupled a long-term (30-year) highly dimensional water quality monitoring dataset with multiple topological data analysis (TDA) techniques to classify ecosystem states, identify state variables, and detect state transitions over 30 years in the river to guide conservation. Across the entire system, TDA identified five ecosystem states. State 1 was characterized by exceptionally clear, clean, and cold-water conditions typical of winter (i.e., a clear-water state); State 2 had the greatest range of environmental conditions and contained most the data (i.e., a status-quo state); and States 3, 4, and 5 had extremely high concentrations of suspended solids (i.e., turbid states, with State 5 as the most turbid). The TDA mapped clear patterns of the ecosystem states across several riverine navigation reaches and seasons that furthered ecological understanding. State variables were identified as suspended solids, chlorophyll a, and total phosphorus, which are also state variables of shallow lakes worldwide. The TDA change detection function showed short-term state transitions based on seasonality and episodic events, and provided evidence of gradual, long-term changes due to water quality improvements over three decades. These results can inform decision making and guide actions for regulatory and restoration agencies by assessing the status and trends of this important river and provide quantitative targets for state variables. The TDA change detection function may serve as a new tool for predicting the vulnerability to undesirable state transitions in this system and other ecosystems with sufficient data. Coupling ecosystem state concepts and TDA tools can be transferred to any ecosystem with large data to help classify states and understand their vulnerability to state transitions.

Persistent decadal differences in plant communities assembled under contrasting climate conditions

Plant community assembly outcomes can be contingent upon establishment year (year effects) due to variations in the environment. Stochastic events such as interannual variability in climate, particularly in the first year of community assembly, contribute to unpredictable community outcomes over the short term, but less is known about whether year effects produce transient or persistent states on a decadal timescale. To test for short-term (5-year) and persistent (decadal) effects of establishment year climate on community assembly outcomes, we restored prairie in an agricultural field using the same methods in four different years (2010, 2012, 2014, and 2016) that captured a wide range of initial (planting) year climate conditions. Species composition was measured for 5 years in all four restored prairies and for 9 and 11 years in the two oldest restored prairies established under average precipitation and extreme drought conditions. The composition of the four assembled communities showed large and significant differences in the first year of restoration, followed by dynamic change over time along a similar trajectory due to a temporary flush of annual volunteer species. Sown perennial species eventually came to dominate all communities, but communities remained distinct from each other in year five. Precipitation in June and July of the establishment year explained short-term coarse community metrics (i.e., species richness and grass/forb cover), with wet establishment years resulting in a higher cover of grasses and dry establishment years resulting in a higher cover of forbs in restored communities. Short-term differences in community composition, species richness, and grass/forb cover in restorations established under average precipitation and drought conditions persisted for 9-11 years, with low interannual variability in the composition of each prairie over the long term, indicating persistently different states on a decadal timescale. Thus, year effects resulting from stochastic variation in climate can have decadal effects on community assembly outcomes.