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Emma Ladouceur

Publications and source records attributed to Emma Ladouceur.

3 recordsLinked to original sources

Facilitating comparable research in seedling functional ecology

Ecologists have worked to ascribe function to the variation found in plant populations, communities and ecosystems across environments for at least the past century. The vast body of research in functional ecology has drastically improved understanding of how individuals respond to their environment, communities are assembled and ecosystems function. However, with limited exceptions, few studies have quantified differences in plant function during the earliest stages of the plant life cycle, and fewer have tested how this early variability shapes populations, communities and ecosystems. Drawing from the literature and our collective experience, we describe the current state of knowledge in seedling functional ecology and provide examples of how this subdiscipline can enrich our fundamental understanding of plant function across levels of organisation. To inspire progressive work in this area, we also outline key considerations involved in seedling functional research (who, what, when, where and how to measure seedling traits) and identify remaining challenges and gaps in understanding around methodological approaches. Within this conceptual synthesis, we highlight three critical areas in seedling ecology for future research to target. First, given wide variation in the definition of a ‘seedling’, we provide a standard definition based on seed reserve dependence while emphasising the need to measure ontogenetic variation more clearly both within and following the seedling stage. Second, studies demonstrate that seedlings can be studied in multiple media (e.g. soil, agar, filter paper) and conditions (e.g. field, greenhouse, laboratory). We recommend that researchers select methods based on explicit goals, yet follow standard guidelines to reduce methodological noise across studies. Third, research is critically needed to assess the implications of different methodologies on trait measurement and compatibility across studies. By highlighting the importance of seedling functional ecology and suggesting pathways to address key challenges, we aim to inspire future research that generates useful and comparable data on seedling functional ecology. This work is critical to explain variation within and among populations, communities and ecosystems and integrate this most vulnerable stage of plant life into ecological frameworks.

Methods in Ecology & Evolution

Testing the hierarchy of predictability in grassland restoration across a gradient of environmental severity

Ecological restoration is critical for recovering degraded ecosystems but is challenged by variable success and low predictability. Understanding which outcomes are more predictable and less variable following restoration can improve restoration effectiveness. Recent theory asserts that the predictability of outcomes would follow an order from most to least predictable from coarse to fine community properties (physical structure > taxonomic diversity > functional composition > taxonomic composition) and that predictability would increase with more severe environmental conditions constraining species establishment. We tested this “hierarchy of predictability” hypothesis by synthesizing outcomes along an aridity gradient with 11 grassland restoration projects across the United States. We used 1829 vegetation monitoring plots from 227 restoration treatments, spread across 52 sites. We fit generalized linear mixed-effects models to predict six indicators of restoration outcomes as a function of restoration characteristics (i.e., seed mixes, disturbance, management actions, time since restoration) and used variance explained by models and model residuals as proxies for restoration predictability. We did not find consistent support for our hypotheses. Physical structure was among the most predictable outcomes when the response variable was relative abundance of grasses, but unpredictable for total canopy cover. Similarly, one dimension of taxonomic composition related to species identities was unpredictable, but another dimension of taxonomic composition indicating whether exotic or native species dominated the community was highly predictable. Taxonomic diversity (i.e., species richness) and functional composition (i.e., mean trait values) were intermittently predictable. Predictability also did not increase consistently with aridity. The dimension of taxonomic composition related to the identity of species in restored communities was more predictable (i.e., smaller residuals) in more arid sites, but functional composition was less predictable (i.e., larger residuals), and other outcomes showed no significant trend. Restoration outcomes were most predictable when they related to variation in dominant species, while those responding to rare species were harder to predict, indicating a potential role of scale in restoration predictability. Overall, our results highlight additional factors that might influence restoration predictability and add support to the importance of continuous monitoring and active management beyond one-time seed addition for successful grassland restoration in the United States.

Continental United States

Knowledge sharing for shared success in the decade on ecosystem restoration

The Decade on Ecosystem Restoration aims to provide the means and incentives for upscaling restoration efforts worldwide. Although ecosystem restoration is a broad, interdisciplinary concept, effective ecological restoration requires sound ecological knowledge to successfully restore biodiversity and ecosystem services in degraded landscapes. We emphasize the critical role of knowledge and data sharing to inform synthesis for the most robust restoration science possible. Such synthesis is critical for helping restoration ecologists better understand how context affects restoration outcomes, and to increase predictive capacity of restoration actions. This predictive capacity can help to provide better information for evidence-based decision-making, and scale-up approaches to meet ambitious targets for restoration. We advocate for a concerted effort to collate species-level, fine-scale, ecological community data from restoration studies across a wide range of environmental and ecological gradients. Well-articulated associated metadata relevant to experience and social or landscape contexts can further be used to explain outcomes. These data could be carefully curated and made openly available to the restoration community to help to maximize evidence-based knowledge sharing, enable flexible re-use of existing data and support predictive capacity in ecological community responses to restoration actions. We detail how integrated data, analysis and knowledge sharing via synthesis can support shared success in restoration ecology by identifying successful and unsuccessful outcomes across diverse systems and scales. We also discuss potential interdisciplinary solutions and approaches to overcome challenges associated with bringing together subfields of restoration practice. Sharing this knowledge and data openly can directly inform actions and help to improve outcomes for the Decade on Ecosystem Restoration.

Ecological Solutions and Evidence