David A. Lytle

HYDROLOGIC REGIMES AND RIPARIAN FORESTS: A STRUCTURED POPULATION MODEL FOR COTTONWOOD

Riparian cottonwood (Populus deltoides) forests form the one of the most extensive deciduous forest ecosystems in arid regions of the western United States. However, cottonwood populations are threatened by flow alteration and channel degradation caused by dams, water diversions, and groundwater pumping. We developed a stochastic, density- dependent, population model to (1) consolidate information concerning cottonwood pop- ulation dynamics in a conceptual and analytical framework, (2) determine whether complex forest stand dynamics can be predicted from basic cottonwood vital rates and river hy- drology, and (3) aid in planning prescribed floods by projecting how altered flow regimes might affect populations. The model describes how annual variation in the hydrograph affects cottonwood mortality (via floods and droughts) and recruitment (via scouring of new habitat and seedling establishment). Using parameter values for the undammed Yampa River in Colorado, we found that abundances of seedlings and younger trees followed a boom-bust cycle driven by high flood mortalities while reproductive adult abundance fol- lowed a less erratic 5-15-yr periodicity driven by multiyear sequences of flows favorable to stand recruitment. Conversely, chance occurrences of multiple drought years eliminated cottonwood from up to 50% of available habitat, providing opportunities for competing plant species to establish. By simulating flow alterations on the Yampa ranging from chan- nelization (many floods/droughts) to damming (few floods/droughts), the model suggested that mature cottonwood forest should be most abundant near the observed natural flow regime. Model analysis also suggested that flow regimes with high flood frequencies result in stable (albeit small) population sizes, while stable flows result in highly variable pop- ulation sizes prone to local extinction.

VARIATION IN MAYFLY SIZE AT METAMORPHOSIS AS A DEVELOPMENTAL RESPONSE TO RISK OF PREDATION

Animals with complex life cycles often show large variation in the size and timing of metamorphosis in response to environmental variability. If fecundity increases with body size and large individuals are more vulnerable to predation, then organisms may not be able to optimize simultaneously size and timing of metamorphosis. The goals of this study were to measure and explain large-scale spatial and temporal patterns of phe- notypic variation in size at metamorphosis of the mayfly, Baetis bicaudatus (Baetidae), from habitats with variable levels of predation risk. Within a single high-elevation watershed in western Colorado, USA, from 1994 to 1996 we measured dry masses of mature larvae of the overwintering and summer generations of Baetis at 28 site-years in streams with and without predatory fish (trout). We also estimated larval growth rates and development times at 16 site-years. Patterns of spatial variation in mayfly size could not be explained by resource (algae) standing stock, competitor densities, or physical-chemical variables. However, size at metamorphosis of males and females of summer generation Baetis was smaller in fish streams than in fishless streams and decreased as densities of predatory stoneflies increased. Furthermore, overwintering individuals matured at larger sizes than summer generation Baetis, and the size of emerging Baetis declined over the summer, but predominantly in trout streams. Theoretical consideration of the effect of predation risk on size and timing of metamorphosis accurately predicted the observed temporal variation in size and timing of mayflies at emergence in fish and fishless streams. Baetis populations had similar growth rates but followed different developmental trajectories in high and low risk environments. In risky environments larval development was accelerated, resulting in metamorphosis of younger and smaller individuals, minimizing exposure of larvae to risk of mortality from trout predation, but at the cost of future reproduction. In safe environ- ments, larvae extended their development, resulting in larger, more fecund adults. Thus, we propose that large-scale patterns of variation in size and timing of metamorphosis represent adaptive phenotypic plasticity, whereby mayflies respond to variation in risk of predation, thereby maximizing their fitness in variable environments.

Disturbance Regimes and Life‐History Evolution

Disturbance regimes are ecologically important, but many of their evolutionary consequences are poorly understood. A model is developed here that combines the within‐ and among‐season dynamics of disturbances with evolutionary life‐history theory. “Disturbance regime” is defined in terms of disturbance timing, frequency, predictability, and severity. The model predicts the optimal body size and time at which organisms should abandon a disturbance‐prone growth habitat by maturing and moving to a disturbance‐free, nongrowth habitat. The effects of both coarse‐grained (those affecting the entire population synchronously) and fine‐grained disturbances (those occurring in a patch dynamics setting) are explored. Several predictions are congruent with previous theory. Infrequent or temporally unpredictable disturbances should have little effect on the evolution of life‐history strategies, even though they may cause high mortality. Similar to seasonal time constraints on reproduction, disturbance regimes can synchronize metamorphosis within a population, resulting in a seasonal decline in body size at maturity. Other model predictions are novel. When disturbances cause high mortality, coarse‐grained disturbances have a much stronger effect on life‐history strategies than fine‐grained disturbances, suggesting that population structure (relative to the scale of disturbance) plays a critical evolutionary role when disturbances are severe. When within‐population variance in juvenile body size is high, two consecutive seasonal declines in body size at maturity can occur, the first associated with disturbance regime and the second associated with seasonal time constraints.

CONSTRAINTS ON PRIMARY PRODUCER N:P STOICHIOMETRY ALONG N:P SUPPLY RATIO GRADIENTS

A current principle of ecological stoichiometry states that the nitrogen to phosphorus ratio (N:P) of primary producers should closely match that from environmental nutrient supplies. This hypothesis was tested using data from ponds in Michigan, USA, a freshwater mesocosm experiment, a synthesis of studies from diverse systems (cultures, lakes, streams, and marine and terrestrial environments), and simple dynamic models of producer growth and nutrient content. Unlike prior laboratory studies, the N:P stoichiometry of phytoplankton in Michigan ponds clustered around and below the Redfield ratio (7.2:1 by mass), despite wide variation in N:P supply ratios (2:1-63:1 by mass) and the presence of grazers. In a mesocosm experiment, the N:P stoichiometry of phytoplankton cells again deviated from a nearly 1:1 relationship with N:P supply. Phytoplankton seston exhibited lower N:P content than expected at high N:P supply ratios, and often higher N:P content than anticipated at low N:P supply ratios, regardless of herbivore presence. Similar devi- ations consistently occur in the N:P stoichiometry of algae and plants in the other diverse systems. The models predicted that both high loss rates (sinking, grazing) and physiological limits to nutrient storage capacity could attenuate producer stoichiometry. In the future, research should evaluate how limits to elemental plasticity of producers can influence the role of stoichiometry in structuring communities and ecosystem processes.

Large-scale Flow Experiments for Managing River Systems

Experimental manipulations of streamflow have been used globally in recent decades to mitigate the impacts of dam operations on river systems. Rivers are challenging subjects for experimentation, because they are open systems that cannot be isolated from their social context. We identify principles to address the challenges of conducting effective large-scale flow experiments. Flow experiments have both scientific and social value when they help to resolve specific questions about the ecological action of flow with a clear nexus to water policies and decisions. Water managers must integrate new information into operating policies for large-scale experiments to be effective. Modeling and monitoring can be integrated with experiments to analyze long-term ecological responses. Experimental design should include spatially extensive observations and well-defined, repeated treatments. Large-scale flow manipulations are only a part of dam operations that affect river systems. Scientists can ensure that experimental manipulations continue to be a valuable approach for the scientifically based management of river systems.

Are large-scale flow experiments informing the science and management of freshwater ecosystems?

Greater scientific knowledge, changing societal values, and legislative mandates have emphasized the importance of implementing large-scale flow experiments (FEs) downstream of dams. We provide the first global assessment of FEs to evaluate their success in advancing science and informing management decisions. Systematic review of 113 FEs across 20 countries revealed that clear articulation of experimental objectives, while not universally practiced, was crucial for achieving management outcomes and changing dam-operating policies. Furthermore, changes to dam operations were three times less likely when FEs were conducted primarily for scientific purposes. Despite the recognized importance of riverine flow regimes, four-fifths of FEs involved only discrete flow events. Over three-quarters of FEs documented both abiotic and biotic outcomes, but only one-third examined multiple taxonomic responses, thus limiting how FE results can inform holistic dam management. Future FEs will present new opportunities to advance scientifically credible water policies.

FLASH FLOODS AND AQUATIC INSECT LIFE‐HISTORY EVOLUTION: EVALUATION OF MULTIPLE MODELS

In disturbance ecology there is a tension between ecological and evolutionary viewpoints, because while disturbances often cause mortality in populations (an ecological effect), populations may also evolve mechanisms that ameliorate mortality risk (an evolutionary effect). Flash floods cause high mortality in the juvenile aquatic stage of desert stream insects, but these ecological effects may be mitigated by the evolution of life-history strategies that allow the terrestrial adult stage to avoid floods. Life-history theory predicts that, to balance trade-offs between juvenile growth and mortality risk from floods, (1) most individuals should emerge before the peak of the flood season, (2) optimal body size at emergence should decline as flood probability increases, and (3) a second decline in body size at emergence should occur as the reproductive season ends. These predictions were tested with data on body mass at and timing of emergence of the caddisfly Phylloicus aeneus measured in three montane Chihuahuan Desert (Arizona, USA) streams over two years. P. aeneus that had not reached the adult stage were eliminated from site-years that experienced flash floods, suggesting that timing of emergence is an important fitness component. On average 86% of emergence occurred before the long-term (∼100 yr) mean arrival date of the first seasonal flood, supporting prediction 1. The presence of two consecutive declines in body mass at emergence in most site-years was congruent with predictions 2 and 3. To test whether the two declines were associated with increasing flood probability and end of the reproductive season, respectively, maximum-likelihood methods were used to compare five body-size models: a null model that contains no parameters related to flood regime or reproductive season, a seasonal model that incorporates a reproductive time constraint, and three disturbance models that incorporate both reproductive time constraints and flood dynamics. The disturbance models outperformed the other models, suggesting that at least some of the body-mass pattern was influenced by flood dynamics. The timing of the first flood of the season was the most important determinant of observed emergence patterns. Overall, this study demonstrates that aquatic insects can compensate for flash floods by using state-dependent emergence strategies that are synchronized with long-term flood dynamics.

Automated insect identification through concatenated histograms of local appearance features: feature vector generation and region detection for deformable objects

This paper describes a computer vision approach to automated rapid-throughput taxonomic identification of stonefly larvae. The long-term objective of this research is to develop a cost-effective method for environmental monitoring based on automated identification of indicator species. Recognition of stonefly larvae is challenging because they are highly articulated, they exhibit a high degree of intraspecies variation in size and color, and some species are difficult to distinguish visually, despite prominent dorsal patterning. The stoneflies are imaged via an apparatus that manipulates the specimens into the field of view of a microscope so that images are obtained under highly repeatable conditions. The images are then classified through a process that involves (a) identification of regions of interest, (b) representation of those regions as SIFT vectors (Lowe, in Int J Comput Vis 60(2):91–110, 2004) (c) classification of the SIFT vectors into learned “features” to form a histogram of detected features, and (d) classification of the feature histogram via state-of-the-art ensemble classification algorithms. The steps (a) to (c) compose the concatenated feature histogram (CFH) method. We apply three region detectors for part (a) above, including a newly developed principal curvature-based region (PCBR) detector. This detector finds stable regions of high curvature via a watershed segmentation algorithm. We compute a separate dictionary of learned features for each region detector, and then concatenate the histograms prior to the final classification step. We evaluate this classification methodology on a task of discriminating among four stonefly taxa, two of which, Calineuria and Doroneuria, are difficult even for experts to discriminate. The results show that the combination of all three detectors gives four-class accuracy of 82% and three-class accuracy (pooling Calineuria and Doro-neuria) of 95%. Each region detector makes a valuable contribution. In particular, our new PCBR detector is able to discriminate Calineuria and Doroneuria much better than the other detectors.

Stoichiometry and planktonic grazer composition over gradients of light, nutrients, and predation risk

Mechanisms that explain shifts in species composition over environmental gradients continue to intrigue ecologists. Ecological stoichiometry has recently provided a new potential mechanism linking resource (light and nutrient) supply gradients to grazer performance via elemental food-quality mechanisms. More specifically, it predicts that light and nutrient gradients should determine the relative dominance of P-rich taxa, such as Daphnia, in grazer assemblages. We tested this hypothesis in pond mesocosms (cattle tanks) by creating gradients of resource supply and predation risk, to which we added diverse assemblages of algal producer and zooplankton grazer species. We then characterized the end-point composition of grazer assemblages and quantity and elemental food quality of edible algae. We found that somatically P-rich Daphnia only dominated grazer assemblages in high-nutrient, no-predator treatments. In these ecosystems, P sequestered in producers exceeded a critical concentration. However, other grazers having even higher body P content did not respond similarly. These grazers were often abundant in low-nutrient environments with poorer food quality. At face value, this result is problematic for ecological stoichi- ometry because body composition did not correctly predict response of these other species. However, two potential explanations could maintain consistency with stoichiometric prin- ciples: species could differentially use a high-P resource (bacteria), or body composition might not always directly correlate with nutrient demands of grazers. Although our data cannot differentiate between these explanations, both suggest potential avenues for future empirical and theoretical study.

Evolution of aquatic insect behaviours across a gradient of disturbance predictability

Natural disturbance regimes—cycles of fire, flood, drought or other events—range from highly predictable (disturbances occur regularly in time or in concert with a proximate cue) to highly unpredictable. While theory predicts how populations should evolve under different degrees of disturbance predictability, there is little empirical evidence of how this occurs in nature. Here, we demonstrate local adaptation in populations of an aquatic insect occupying sites along a natural gradient of disturbance predictability, where predictability was defined as the ability of a proximate cue (rainfall) to signal a disturbance (flash flood). In controlled behavioural experiments, populations from predictable environments responded to rainfall events by quickly exiting the water and moving sufficiently far from the stream to escape flash floods. By contrast, populations from less predictable environments had longer response times and lower response rates, reflecting the uncertainty inherent to these environments. Analysis with signal detection theory showed that for 13 out of 15 populations, observed response times were an optimal compromise between the competing risks of abandoning versus remaining in the stream, mediated by the rainfall–flood correlation of the local environment. Our study provides the first demonstration that populations can evolve in response to differences in disturbance predictability, and provides evidence that populations can adapt to among-stream differences in flow regime.