Does dispersal control population densities in advection-dominated systems? A fresh look at critical assumptions and a direct test

Assessing population genetic structure of three New Zealand stream insects using mitochondrial and nuclear DNA markers

Assessing genetic differentiation among natural populations can aid understanding of dispersal patterns and connectivity among habitats. Several molecular markers have become increasingly popular in determining population genetic structure for this purpose. Here, we compared the resolution of mitochondrial cytochrome c oxidase subunit I (COI) and nuclear single nucleotide polymorphism (SNP) markers for detecting population structure among stream insects at small spatial scales. Individuals of three endemic taxa - Coloburiscus humeralis (Ephemeroptera), Zelandobius confusus (Plecoptera), and Hydropsyche fimbriata (Trichoptera) - were collected from forested streams that flow across open pasture in the North Island of New Zealand. Both COI and SNP data indicated limited population structure across the study area, and small differences observed among these species were likely related to their putative dispersal abilities. For example, fine-scale genetic differentiation between and among neighbouring stream populations for H. fimbriata suggests that gene flow, and hence dispersal, may be more limited for this species relative to the others. Based on the generally similar results provided by both types of markers, we suggest that either COI or SNP markers can provide suitable initial estimates of fine-scale population genetic differentiation in stream insects.

Regulation of open populations of a stream insect through larval density-dependence

In organisms with complex life cycles, the various stages occupy different habitats creating demographically open populations. The dynamics of these populations will depend on the occurrence and timing of stochastic influences relative to demographic density dependence, but understanding of these fundamentals, especially in the face of climate warming, has been hampered by the difficulty of empirical studies.

Using a logically feasible organism, we conducted a replicated density‐perturbation experiment to manipulate late‐instar larvae of nine populations of a stream caddisfly, Zelandopsyche ingens, and measured the resulting abundance over 2 years covering the complete life cycle of one cohort to evaluate influences on dynamics.

Negative density feedback occurred in the larval stage, and was sufficiently strong to counteract variation in abundance due to manipulation of larval density, adult caddis dispersal in the terrestrial environment as well as downstream drift of newly hatched and older larvae in the current. This supports theory indicating regulation of open populations must involve density dependence in local populations sufficient to offset variability associated with dispersal, especially during recruitment, and pinpoints the occurrence to late in the larval life cycle and driven by food resource abundance.

There were large variations in adult, egg mass and early instar abundance that were not related to abundance in the previous stage, or the manipulation, pointing to large stochastic influences. Thus, the results also highlight the complementary nature of stochastic and deterministic influences on open populations. Such density dependence will enhance population persistence in situations where variable dispersal and transitioning between life stages frequently creates mismatches between abundance and the local availability of resources, such as might become more common with climate warming.

Aquatic versus Terrestrial Insects: Real or Presumed Differences in Population Dynamics?

The study of insect populations is dominated by research on terrestrial insects. Are aquatic insect populations different or are they just presumed to be different? We explore the evidence across several topics. (1) Populations of terrestrial herbivorous insects are constrained most often by enemies, whereas aquatic herbivorous insects are constrained more by food supplies, a real difference related to the different plants that dominate in each ecosystem. (2) Population outbreaks are presumed not to occur in aquatic insects. We report three examples of cyclical patterns; there may be more. (3) Aquatic insects, like terrestrial insects, show strong oviposition site selection even though they oviposit on surfaces that are not necessarily food for their larvae. A novel outcome is that density of oviposition habitat can determine larval densities. (4) Aquatic habitats are often largely 1-dimensional shapes and this is presumed to influence dispersal. In rivers, drift by insects is presumed to create downstream dispersal that has to be countered by upstream flight by adults. This idea has persisted for decades but supporting evidence is scarce. Few researchers are currently working on the dynamics of aquatic insect populations; there is scope for many more studies and potentially enlightening contrasts with terrestrial insects.

Dispersal constraints for stream invertebrates: setting realistic timescales for biodiversity restoration

Biodiversity goals are becoming increasingly important in stream restoration. Typical models of stream restoration are based on the assumption that if habitat is restored then species will return and ecological processes will re-establish. However, a range of constraints at different scales can affect restoration success. Much of the research in stream restoration ecology has focused on habitat constraints, namely the in-stream and riparian conditions required to restore biota. Dispersal constraints are also integral to determining the timescales, trajectory and potential endpoints of a restored ecosystem. Dispersal is both a means of organism recolonization of restored sites and a vital ecological process that maintains viable populations. We review knowledge of dispersal pathways and explore the factors influencing stream invertebrate dispersal. From empirical and modeling studies of restoration in warm-temperate zones of New Zealand, we make predictions about the timescales of stream ecological restoration under differing levels of dispersal constraints. This process of constraints identification and timescale prediction is proposed as a practical step for resource managers to prioritize and appropriately monitor restoration sites and highlights that in some instances, natural recolonization and achievement of biodiversity goals may not occur.