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Abstract Patches of plants in drylands can arise when larger plants facilitate recruitment via ‘nurse‐plant’ effects. Simultaneously, plant–soil feedback processes can increase soil nutrients beneath shrubs leading to spatial patterns known as ‘islands of fertility’ that may also promote plant performance. These phenomena shape dryland plant communities; however, their comparative relative influences on plant density and diversity remain poorly quantified.Using reciprocal soil transplants among pairs of unvegetated interspaces and neighbouring shrubs in combination with cover treatments—open interspace, shaded interspace, intact shrub canopy and trimmed shrub canopy—this study aimed to disentangle the influences of shading from soil properties in native plant recruitment under the foundation species of shrubsLarrea tridentata andNeltuma glandulosain the Chihuahuan Desert, NM, USA.Seedling density varied significantly across years in response to interannual climate variability and was consistently higher underL. tridentatathanN. glandulosa. Cover treatments, soil provenance, shrub species and spatial factors (study blocks) significantly affected seedling density, species richness and community structure. Shading from intact shrubs or shade clothes had a stronger effect on density and richness than soil provenance or shrub species. Seedling density and richness were also higher in soil from beneath shrubs regardless of shrub species, location (native or transplanted locations) or time (study year) since initial translocation.The density of seedlings emerging from shaded interspace soil was initially similar to that observed under intact shrubs indicating the importance of shading by nurse plants for recruitment. However, the effect of shade‐cloth canopy surrogates on seedling density in interspaces switched from positive to negative by the third year of the study, likely due to seed bank depletion.Synthesis. The significant influence of shading highlights the role of environmental factors in shaping plant communities of this dryland system, while the evidence of seed depletion combined with the influence of plot location suggests a concurrent influence of stochastic community assembly processes. Understanding how these processes interact to shape spatial and temporal patterns of vegetation community assembly and potentially reinforce alternate ecological states remains an important focus in dryland ecosystems.
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Propagating observation errors to enable scalable and rigorous enumeration of plant population abundance with aerial imagery
Abstract Estimating and monitoring plant population size is fundamental for ecological research, as well as conservation and restoration programs. High‐resolution imagery has potential to facilitate such estimation and monitoring. However, remotely sensed estimates typically have higher uncertainty than field measurements, risking biased inference on population status.We present a model that accounts for false negative (missed plants) and false positive (misclassified or double‐counted plants) error in counts from high‐resolution imagery via integration with ground data. We apply it to estimate the abundance of a foundational shrub species in post‐wildfire landscapes in the western United States. In these landscapes, plant recruitment is crucial for ecological recovery but locally patchy, motivating the use of spatially extensive measurements from unoccupied aerial systems (UAS). Integrating >16 ha of UAS imagery with >700 georeferenced field plots, we fit our model to generate insights into the prevalence and drivers of observation errors associated with classification algorithms used to distinguish individual plants, relationships between abundance and landscape context, and to generate spatially explicit maps of shrub abundance.Raw counts of plant abundance in high‐resolution imagery resulted in substantial false negative and false positive observation errors. The probability of detecting (p) adult plants (0.25 m tall) varied between sites within 0.52 < < 0.82, whereas the detection of smaller plants (<0.25 m) was lower, 0.03 < < 0.3. On average, we estimate that 19% of all detected plants were false positive errors, which varied spatially in relation to topographic predictors. Abundance declined toward the interior of previous wildfires and was positively associated with terrain roughness.Our study demonstrates that integrated models accounting for imperfect detection improve estimates of plant population abundance derived from inherently imperfect UAS imagery. We believe such models will further improve inference on plant population dynamics—relevant to restoration, wildlife habitat and related objectives—and echo previous calls for remote sensing applications to better differentiate between ecological and observational processes.
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- Award ID(s):
- 2207158
- PAR ID:
- 10592213
- Publisher / Repository:
- Methods in Ecology and Evolution
- Date Published:
- Journal Name:
- Methods in Ecology and Evolution
- Volume:
- 15
- Issue:
- 11
- ISSN:
- 2041-210X
- Page Range / eLocation ID:
- 2074 to 2086
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript
- Journal Article:
- https://doi.org/10.1111/2041-210X.14421
