Plant communities have undergone dramatic changes in recent centuries, although not all such changes fit with the dominant biodiversity-crisis narrative used to describe them. At the global scale, ...future declines in plant species diversity are highly likely given habitat conversion in the tropics, although few extinctions have been documented for the Anthropocene to date (<0.1%). Nonnative species introductions have greatly increased plant species richness in many regions of the world at the same time that they have led to the creation of new hybrid polyploid species by bringing previously isolated congeners into close contact. At the local scale, conversion of primary vegetation to agriculture has decreased plant diversity, whereas other drivers of change-e.g., climate warming, habitat fragmentation, and nitrogen deposition-have highly context-dependent effects, resulting in a distribution of temporal trends with a mean close to zero. These results prompt a reassessment of how conservation goals are defined and justified.
1. A long-term perspective is needed to understand how disturbance is affecting plant communities in human-dominated landscapes. Increased human disturbance often results in declining local native ...species richness, gains in exotic species and a decline in beta diversity. However, it is far from certain whether a general decline in plant diversity is occurring across all disturbed landscapes, and knowledge gaps remain concerning how the spread of exotic species influences beta diversity over long time-scales. 2. We resurveyed 184 vegetation plots in three broad vegetation types on southern Vancouver Island, Canada, originally surveyed in the late 1960s. This landscape has experienced a high degree of human disturbance over the past 40 years due to urbanization. We examined changes in total diversity, local diversity and beta diversity over time. We also compiled information on the traits of each species and tested for correlations between traits and plant species success over four decades. 3. We found striking increases in local and total plant species richness driven by both native and exotic species. The most successful species tended to be exotic, disturbance tolerant, shade tolerant and shrubs. Biotic homogenization occurred, but not as a result of exotic species colonization, instead being significantly correlated with gains in native species. The loss in beta diversity has resulted in a shrinking of the gradient of vegetation types, blurring the distinction between them. 4. Synthesis. Our study shows that human-mediated disturbance is the dominant driver of plant community changes, but the net result has actually been an increase in richness, for each plot and for all plots pooled, and for both natives and exotics, despite a decline in variability among plant communities on the landscape. Contrary to conventional definitions of biotic homogenization, this decline in beta diversity was not correlated with the spread of exotic species, but with the colonization of common, disturbance-tolerant natives.
Growing concern about biodiversity loss underscores the need to quantify and understand temporal change. Here, we review the opportunities presented by biodiversity time series, and address three ...related issues: (i) recognizing the characteristics of temporal data; (ii) selecting appropriate statistical procedures for analysing temporal data; and (iii) inferring and forecasting biodiversity change. With regard to the first issue, we draw attention to defining characteristics of biodiversity time series—lack of physical boundaries, uni-dimensionality, autocorrelation and directionality—that inform the choice of analytic methods. Second, we explore methods of quantifying change in biodiversity at different timescales, noting that autocorrelation can be viewed as a feature that sheds light on the underlying structure of temporal change. Finally, we address the transition from inferring to forecasting biodiversity change, highlighting potential pitfalls associated with phase-shifts and novel conditions.
Effective conservation of rare species requires reasonable knowledge of population locations. However, surveys for rare species can be time-intensive and therefore expensive. We test a methodology ...using stacked species distribution models (S-SDMs) to efficiently discover the greatest number of new rare species’ occurrences possible. We used S-SDMs for 22 rare plant species in southern Ontario, Canada to predict the best survey locations among individual 1-ha cells. For each cell, we weighted distribution model outputs by accuracy and species rarity to create an efficiency value. We used these efficiency values as an index to determine the locations of our field surveys. We conducted field surveys in multi-species cells, “MSC” (areas with high predicted efficiency for multiple species) and single species cells, “SSC” (areas with high probability for only one species) to determine the relative efficiency of a multi-species survey approach. MSC were more than twice as likely as SSC to have at least one rare plant species discovered. Efficiency ranks were also useful in directing surveyors toward incidental discoveries of other rare species that were not modeled. Our technique of using S-SDMs can help direct surveys to more efficiently find rare species occurrences.
Stylophorum diphyllum (Michx.) Nutt. is an endangered plant of rich floodplain forests in southern Ontario, Canada. Prior to 2015 there were only four known populations in Ontario. I built a species ...distribution model (SDM) based on the known occurrences, and tested it by surveying 156 forest sites that varied in their predicted suitability. An indicator species analysis showed that sites predicted to be suitable had significantly higher frequency and abundance of common species usually associated with S. diphyllum, demonstrating the ability of the SDM to pinpoint similar habitat, although none of these sites contained S. diphyllum. The most important predictors used by the SDM to determine habitat suitability were growing season precipitation, surficial geology, and soil texture. I discovered a new population of S. diphyllum more than 50 km north of the known populations, at one of the sites not predicted to be suitable. This demonstrates a clear example of SDM overfitting, which may occur when models are built based on few, spatially limited occurrence records. Nonetheless, the key environmental predictors remained the same in an updated SDM including the new record. Stylophorum diphyllum provides a case study of both the value and the limitations of using SDMs to predict suitable habitat for very rare and geographically restricted plants, and the need for more rare plant surveys even in human-dominated landscapes.
Theory suggests that species with different traits will respond differently to landscape fragmentation. Studies have shown that the presence of species in fragments of varying size, shape and ...connectivity is dependent on plant traits related to dispersal ability, persistence and disturbance tolerance. However, the role of traits in determining long-term plant community changes in response to changing landscape context is not well understood. We used data from resurveys of 184 plots to test the ability of nine plant traits to predict colonizations and extirpations between 1968 and 2009 based on the surrounding landscape context. We related apparent colonizations and extirpations to road density, naturally vegetated area and patch shape and then tested for significant relationships between a tendency for positive or negative associations and plant traits. Exotic, herbaceous, annual, shade-intolerant species and species with higher specific leaf area were more likely than others to colonize plots with higher road density, lower amount of naturally vegetated area and higher edgeto-area ratio. However, extirpations were rarely predictable based on traits. The role of landscape context in structuring plant community change over the past four decades in the 184 plots resurveyed was largely mediated by colonization events, suggesting that trait-based extirpations occur with a longer post-fragmentation time lag or, alternatively, that extirpation is more stochastic with respect to plant traits than is colonization.
Species distribution models (SDMs) are widely used in ecology. In theory, SDMs capture (at least part of) species' ecological niches and can be used to make inferences about the distribution of ...suitable habitat for species of interest. Because habitat suitability is expected to influence population demography, SDMs have been used to estimate a variety of population parameters, from occurrence to genetic diversity. However, a critical look at the ability of SDMs to predict independent data across different aspects of population biology is lacking. Here, we systematically reviewed the literature, retrieving 201 studies that tested predictions from SDMs against independent assessments of occurrence, abundance, population performance, and genetic diversity. Although there is some support for the ability of SDMs to predict occurrence (~53% of studies depending on how support was assessed), the predictive performance of these models declines progressively from occurrence to abundance, to population mean fitness, to genetic diversity. At the same time, we observed higher success among studies that evaluated performance for single versus multiple species, pointing to a possible publication bias. Thus, the limited accuracy of SDMs reported here may reflect the best‐case scenario. We discuss the limitations of these models and provide specific recommendations for their use for different applications going forward. However, we emphasize that predictions from SDMs, especially when used to inform conservation decisions, should be treated as hypotheses to be tested with independent data rather than as stand‐ins for the population parameters we seek to know.
Predicting the future ecological impact of global change drivers requires understanding how these same drivers have acted in the past to produce the plant populations and communities we see today. ...Historical ecological data sources have made contributions of central importance to global change biology, but remain outside the toolkit of most ecologists. Here we review the strengths and weaknesses of four unconventional sources of historical ecological data: land survey records, "legacy" vegetation data, historical maps and photographs, and herbarium specimens. We discuss recent contributions made using these data sources to understanding the impacts of habitat disturbance and climate change on plant populations and communities, and the duration of extinction—colonization time lags in response to landscape change. Historical data frequently support inferences made using conventional ecological studies (e.g., increases in warm-adapted species as temperature rises), but there are cases when the addition of different data sources leads to different conclusions (e.g., temporal vegetation change not as predicted by chronosequence studies). The explicit combination of historical and contemporary data sources is an especially powerful approach for unraveling long-term consequences of multiple drivers of global change. Despite the limitations of historical data, which include spotty and potentially biased spatial and temporal coverage, they often represent the only means of characterizing ecological phenomena in the past and have proven indispensable for characterizing the nature, magnitude, and generality of global change impacts on plant populations and communities.
The Neolithic Plant Invasion Hypothesis MacDougall, Andrew S.; McCune, Jenny L.; Eriksson, Ove ...
The New phytologist,
October 2018, Letnik:
220, Številka:
1
Journal Article
Recenzirano
Odprti dostop
A long-standing hypothesis is that many European plants invade temperate grasslands globally because they are introduced simultaneously with pastoralism and cultivation, to which they are ...‘preadapted’ after millennia of exposure dating to the Neolithic era (‘Neolithic Plant Invasion Hypothesis’ (NPIH)). These ‘preadaptations’ are predicted to maximize their performance relative to native species lacking this adaptive history. Here, we discuss the explanatory relevance of the NPIH, clarifying the importance of evolutionary context vs other mechanisms driving invasion. The NPIH makes intuitive sense given established connections between invasion and agricultural-based perturbation. However, tests are often incomplete given the need for performance contrasts between home and away ranges, while controlling for other mechanisms. Weemphasize six NPIH-based predictions, centring on trait similarity of invaders between home vs away populations, and differing perturbation responses by invading and native plants. Although no research has integrated all six predictions, we highlight studies suggesting preadaptation influences on invasion. Given that many European grasslands are creations of human activity from the past, current invasions by these flora may represent the continuation of processes dating to the Neolithic. Ironically, European Neolithic-derived grasslands are becoming rarer, reflecting changes in management and illustrating the importance of human influences on these species.
Optimizing ecological surveys for conservation Hanson, Jeffrey O.; McCune, Jenny L.; Chadès, Iadine ...
The Journal of applied ecology,
January 2023, 2023-01-00, 20230101, Letnik:
60, Številka:
1
Journal Article
Recenzirano
Conservation decisions must be made with limited funding and incomplete information. Ecological surveys can help reduce uncertainty and, in turn, potentially lead to better management decisions. ...However, conducting surveys can reduce funds available for implementing management actions and, in turn, can potentially lead to worse conservation outcomes.
Here we develop a value of information framework to evaluate and optimize survey plans. Our framework evaluates survey plans based on their ability to improve how likely resulting protected area systems are to secure species of interest, and accounts for survey and land acquisition costs. Using an example of eight imperilled plant species in Middlesex County (Ontario, Canada), we assessed our framework against conventional approaches for designing survey plans that involve selecting places with (i) maximal geographic coverage, (ii) diverse environmental conditions, (iii) highly uncertain information, (iv) high imperilled species richness and (v) low protected area establishment costs.
We found that optimized survey plans could improve the protected area system by, on average, 57.52% (0.21 SD) (up to 105.25%) over conventional survey approaches. These optimized plans could also improve the protected area system by, on average, 19.91% (up to 32.37%) over simply prioritizing based on existing information. Survey plans designed using conventional approaches, in many cases, led to a worse protected area system than simply using existing information. Such conventional approaches performed the worst when they allocated a large percentage of the available budget to data collection.
Synthesis and applications. Our findings demonstrate that conventional approaches for designing ecological surveys can impede conservation efforts by squandering funds on data that have little chance of improving decision making. Indeed, conventional approaches for designing surveys had the poorest performance under limited budgets, which are typical in real world planning exercises. We recommend that conservation practitioners carefully consider how data collection efforts can potentially improve conservation decisions, and also the costs associated with data collection. By applying the principles of value of information, our framework enables conservation practitioners to cost‐effectively collect data in places that will maximize conservation outcomes.
Our findings demonstrate that conventional approaches for designing ecological surveys can impede conservation efforts by squandering funds on data that have little chance of improving decision making. Indeed, conventional approaches for designing surveys had the poorest performance under limited budgets, which are typical in real world planning exercises. We recommend that conservation practitioners carefully consider how data collection efforts can potentially improve conservation decisions, and also the costs associated with data collection. By applying the principles of value of information, our framework enables conservation practitioners to cost‐effectively collect data in places that will maximize conservation outcomes.
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