Trait‐based tests of coexistence mechanisms Adler, Peter B; Fajardo, Alex; Kleinhesselink, Andrew R ...
Ecology letters,
October 2013, Volume:
16, Issue:
10
Journal Article
Peer reviewed
Recent functional trait studies have shown that trait differences may favour certain species (environmental filtering) while simultaneously preventing competitive exclusion (niche partitioning). ...However, phenomenological trait‐dispersion analyses do not identify the mechanisms that generate niche partitioning, preventing trait‐based prediction of future changes in biodiversity. We argue that such predictions require linking functional traits with recognised coexistence mechanisms involving spatial or temporal environmental heterogeneity, resource partitioning and natural enemies. We first demonstrate the limitations of phenomenological approaches using simulations, and then (1) propose trait‐based tests of coexistence, (2) generate hypotheses about which plant functional traits are likely to interact with particular mechanisms and (3) review the literature for evidence for these hypotheses. Theory and data suggest that all four classes of coexistence mechanisms could act on functional trait variation, but some mechanisms will be stronger and more widespread than others. The highest priority for future research is studies of interactions between environmental heterogeneity and trait variation that measure environmental variables at within‐community scales and quantify species' responses to the environment in the absence of competition. Evidence that similar trait‐based coexistence mechanisms operate in many ecosystems would simplify biodiversity forecasting and represent a rare victory for generality over contingency in community ecology.
Understanding how annual climate variation affects population growth rates across a species’ range may help us anticipate the effects of climate change on species distribution and abundance. We ...predict that populations in warmer or wetter parts of a species’ range should respond negatively to periods of above average temperature or precipitation, respectively, whereas populations in colder or drier areas should respond positively to periods of above average temperature or precipitation. To test this, we estimated the population sensitivity of a common shrub species, big sagebrush (Artemisia tridentata), to annual climate variation across its range. Our analysis includes 8,175 observations of year-to-year change in sagebrush cover or production from 131 monitoring sites in western North America. We coupled these observations with seasonal weather data for each site and analyzed the effects of spring through fall temperatures and fall through spring accumulated precipitation on annual changes in sagebrush abundance. Sensitivity to annual temperature variation supported our hypothesis: years with above average temperatures were beneficial to sagebrush in colder locations and detrimental to sagebrush in hotter locations. In contrast, sensitivity to precipitation did not change significantly across the distribution of sagebrush. This pattern of responses suggests that regional abundance of this species may be more limited by temperature than by precipitation. We also found important differences in how the ecologically distinct subspecies of sagebrush responded to the effects of precipitation and temperature. Our model predicts that a short-term temperature increase could produce an increase in sagebrush cover at the cold edge of its range and a decrease in cover at the warm edge of its range. This prediction is qualitatively consistent with predictions from species distribution models for sagebrush based on spatial occurrence data, but it provides new mechanistic insight and helps estimate how much and how fast sagebrush cover may change within its range.
When species simultaneously compete with two or more species of competitor, higher‐order interactions (HOIs) can lead to emergent properties not present when species interact in isolated pairs. To ...extend ecological theory to multi‐competitor communities, ecologists must confront the challenges of measuring and interpreting HOIs in models of competition fit to data from nature. Such efforts are hindered by the fact that different studies use different definitions, and these definitions have unclear relationships to one another. Here, we propose a distinction between ‘soft’ HOIs, which identify possible interaction modification by competitors, and ‘hard’ HOIs, which identify interactions uniquely emerging in systems with three or more competitors. We show how these two classes of HOI differ in their motivation and interpretation, as well as the tests one uses to identify them in models fit to data. We then show how to operationalise this structure of definitions by analysing the results of a simulated competition experiment underlain by a consumer resource model. In the course of doing so, we clarify the challenges of interpreting HOIs in nature, and suggest a more precise framing of this research endeavour to catalyse further investigations.
Over the last half century, ecologists’ desire to move beyond the limitations of building a theory of community ecology through pairwise interactions has repeatedly energized interest in higher‐order interactions. Each time, however, logistical challenges and shifting definitions have halted progress. Here, we propose a practical and justifiable structure of definitions for higher‐order interactions and show how this structure can be implemented in an experimental context.
Mitigating ecosystem service (ES) trade‐offs is a key management goal in locations where stakeholders value different and potentially conflicting ecosystem services (ESs). However, studies are not ...often designed to examine how local management actions address ES trade‐offs, and therefore do not provide options that can alleviate conflict.
In semi‐arid rangelands, we examined the potential for managers to mitigate trade‐offs between livestock production and water quality. To move away from solutions that offer cattle removal as a singular management strategy, we examined how cattle presence, plus two elements of rotational grazing—the length of time cattle spend on rangeland (i.e. duration), and the season grazed (i.e. timing), affected stream Escherichia coli (E. coli concentrations). We also modelled how grazing duration and timing affected the ability to meet regulatory benchmarks for water quality throughout a grazing season.
Grazing duration controlled the length of time E. coli concentrations were high in streams. In short‐ and medium‐duration systems, E. coli concentrations were high for shorter periods of time than in long‐duration systems, resulting in fewer violations of national and state water quality standards.
Stream E. coli concentrations showed a consistent seasonal pattern, starting low in spring, peaking in summer and declining towards fall. Thus, grazing during spring or fall, rather than in summer, reduced the number of days that E. coli levels exceeded water quality standards.
Our results suggest that reducing the grazing duration and shifting its timing are complementary strategies that can mitigate the trade‐offs between livestock grazing and water quality without fencing‐off riparian areas or removing cattle from pastures with streams.
Synthesis and applications. In this study, we found grazing duration and timing can be used as tools to mitigate ecosystem service (ES) trade‐offs between cattle production and water quality in rangeland streams. Shorter grazing durations reduced the number of days E. coli levels were above regulatory limits, as did grazing that occurred either early or late in the season. These results support the idea that rotational grazing can be an effective strategy to manage water quality in semi‐arid rangelands. They also highlight the need for more grazing studies that incorporate gradients of duration and timing into study designs.
In this study, we found grazing duration and timing can be used as tools to mitigate ecosystem service (ES) trade‐offs between cattle production and water quality in rangeland streams. Shorter grazing durations reduced the number of days E. coli levels were above regulatory limits, as did grazing that occurred either early or late in the season. These results support the idea that rotational grazing can be an effective strategy to manage water quality in semi‐arid rangelands. They also highlight the need for more grazing studies that incorporate gradients of duration and timing into study designs.
Turnover in species composition and the dominant functional strategies in plant communities across environmental gradients is a common pattern across biomes, and is often assumed to reflect shifts in ...trait optima. However, the extent to which community‐wide trait turnover patterns reflect changes in how plant traits affect the vital rates that ultimately determine fitness remain unclear.
We tested whether shifts in the community‐weighted means of four key functional traits across an environmental gradient in a southern California grassland reflect variation in how these traits affect species' germination and fecundity across the landscape.
We asked whether models that included trait–environment interactions help explain variation in two key vital rates (germination rates and fecundity), as well as an integrative measure of fitness incorporating both vital rates (the product of germination rate and fecundity). To do so, we planted seeds of 17 annual plant species at 16 sites in cleared patches with no competitors, and quantified the lifetime seed production of 1360 individuals. We also measured community composition and a variety of abiotic variables across the same sites. This allowed us to evaluate whether observed shifts in community‐weighted mean traits matched the direction of any trait–environment interactions detected in the plant performance experiment.
We found that commonly measured plant functional traits do help explain variation in species responses to the environment—for example, high‐SLA species had a demographic advantage (higher germination rates and fecundity) in sites with high soil Ca:Mg levels, while low‐SLA species had an advantage in low Ca:Mg soils. We also found that shifts in community‐weighted mean traits often reflect the direction of these trait–environment interactions, though not all trait–environment relationships at the community level reflect changes in optimal trait values across these gradients.
Synthesis. Our results show how shifts in trait–fitness relationships can give rise to turnover in plant phenotypes across environmental gradients, a fundamental pattern in ecology. We highlight the value of plant functional traits in predicting species responses to environmental variation, and emphasise the need for more widespread study of trait–performance relationships to improve predictions of community responses to global change.
सारांश
भौगोलि क परि स्थि तीनुसार वि वि ध वनस्पतींची वैशि ष्ट्ये, त्यांच्या गुणधर्मा त दि सणारे बदल, त्यातील प्रबळता हे पर्या वरणाला अनुसरुन त्यांचा टि काव लागून राहणे, त्याचप्रमाणे त्यांचे पुनरुत्पादन होणे ह्या दोन गरजांपोटी झालेले असतात असा आपला समज आहे. ह्यावि षयीचे संशोधन वर्षा नुवर्षे चालू आहे. परंतु ठोस स्पष्टीकरण अजून उपलब्ध नाही.
ह्या संबंधात आम्ही दक्षि ण कॅलि फोर्नि यातील गवताळ प्रदेशात एक संशोधन केले. त्यात काही वनस्पतींमध्ये होणाऱ्या बदलांवि षयी अभ्यास केला.
आमच्या ह्या संशोधनात आम्ही १६ वि वि ध प्रांतात, जमीन पूर्णपणे साफ करुन त्यात १७ प्रकारच्या वार्षि क (एक वर्षा त बि याणे तयार करणाऱ्या) वनस्पतींचे बि याणे पेरले. त्यातून १३६० झाडे उगवली. आमच्या अभ्यासाअंती आम्ही एक संख्याशास्त्रीय तक्ता तयार केला. झाडाची भौगोलि क परि स्थि ती आणि त्यांचे वि शि ष्ट गुणधर्म माहि ती असल्यास ती झाडे दक्षि ण कॅलि फोर्नि यात कशी वाढतील यावि षयीचा अंदाज बांधण्यासाठी हे संशोधन उपयोगी पडेल.
४ आमच्या तक्त्यानुसार झाडाचे गुणधर्म आणि पर्या वरणाची योग्य माहि ती दि ल्यास, एखादी वनस्पती एखाद्या ठि काणी कशी वाढेल आणि कि ती प्रमाणात पुनरुत्पादन करु शकेल ह्याचे भाकीत करता येऊ शकते. उदा. नाजूक/पातळ पानांची झाडे कॅल्शि अम‐मॅग्नेशि अमचे गुणोत्तर जास्त असलेल्या जमि नीत तर याउलट जाड पानांची झाडे कॅल्शि अम‐मॅग्नेशि अमचे गुणोत्तर कमी असलेल्या जमि नीत चांगली वाढतील. आमच्या नि रीक्षणात असे आढळून आले की, बहुतांश प्रदेशात प्रबळपणे आढळून येणारी झाडांची वैशि ष्ट्ये ही आमच्या तक्त्यानुसार भाकीत केलेलीच वैशि ष्ट्ये होती.
नि ष्कर्ष: वेगवेगळ्या पर्या वरणात वेगवेगळ्या वनस्पती आढळतात ह्याचे मुख्य कारण वि शि ष्ठ पर्या वरण हे वनस्पतीच्या त्या त्या गुणधर्मां ना पूरक असते. ह्या संबधी अधि क संशोधनाची गरज आहे एखाद्या प्रदेशात कुठल्या वनस्पती जोमाने वाढतील, त्याचप्रमाणे कुठल्या वनस्पतींना संभाव्य धोका आहे, ह्यावि षयीची माहि ती मि ळणे भवि ष्यकाळात उपयोगी पडेल. ह्यासाठी आमचे संशोधन मोलाचा हातभार लावेल.
Shifts in community‐weighted trait means are often assumed to reflect shifts in trait optima, but few studies have empirically tested this assumption. By pairing community surveys with a field experiment using annual plants in Southern California, we found that shifts in community‐weighted trait means are often—but not always—consistent with trait‐performance relationships across the landscape.
Theory predicts that strong indirect effects of environmental change will impact communities when niche differences between competitors are small and variation in the direct effects experienced by ...competitors is large, but empirical tests are lacking. Here we estimate negative frequency dependence, a proxy for niche differences, and quantify the direct and indirect effects of climate change on each species. Consistent with theory, in four of five communities indirect effects are strongest for species showing weak negative frequency dependence. Indirect effects are also stronger in communities where there is greater variation in direct effects. Overall responses to climate perturbations are driven primarily by direct effects, suggesting that single species models may be adequate for forecasting the impacts of climate change in these communities.
A number of modeling approaches have been developed to predict the impacts of climate change on species distributions, performance, and abundance. The stronger the agreement from models that ...represent different processes and are based on distinct and independent sources of information, the greater the confidence we can have in their predictions. Evaluating the level of confidence is particularly important when predictions are used to guide conservation or restoration decisions. We used a multi‐model approach to predict climate change impacts on big sagebrush (Artemisia tridentata), the dominant plant species on roughly 43 million hectares in the western United States and a key resource for many endemic wildlife species. To evaluate the climate sensitivity of A. tridentata, we developed four predictive models, two based on empirically derived spatial and temporal relationships, and two that applied mechanistic approaches to simulate sagebrush recruitment and growth. This approach enabled us to produce an aggregate index of climate change vulnerability and uncertainty based on the level of agreement between models. Despite large differences in model structure, predictions of sagebrush response to climate change were largely consistent. Performance, as measured by change in cover, growth, or recruitment, was predicted to decrease at the warmest sites, but increase throughout the cooler portions of sagebrush's range. A sensitivity analysis indicated that sagebrush performance responds more strongly to changes in temperature than precipitation. Most of the uncertainty in model predictions reflected variation among the ecological models, raising questions about the reliability of forecasts based on a single modeling approach. Our results highlight the value of a multi‐model approach in forecasting climate change impacts and uncertainties and should help land managers to maximize the value of conservation investments.
Ecological models are increasingly being used to forecast climate change impacts, yet it is difficult to determine which model may yield the best results for a future time period. We developed four independent models to forecast climate change impacts on big sagebrush and explore how model choice contributes to uncertainty. This multi‐model approach enabled us to produce an aggregate index of climate change vulnerability and uncertainty. Locations and conditions where models produced consistent predictions indicate that future warming will increase sagebrush cover across much of its current range, and only decrease cover in the hottest portions of the range.
Understanding the role of native biodiversity in controlling exotic species invasion is a critical goal in ecology. In terrestrial plant communities, most research has focused on the effects of ...native vascular plants on invasion by exotic vascular plants. However, in many ecosystems, native bryophytes and other non‐vascular plants are common and can affect the establishment, survival, and growth of vascular plants. A more complete picture of how native biodiversity affects exotic plant invasion demands that more studies measure the effects of native bryophytes on exotic vascular plants. Moreover, there is growing realization that the effects of native species on invaders can range from negative to positive and that a complete picture of interactions between native and exotic plants requires measuring interactions in multiple environments. We used both observational and experimental studies to quantify the effects of native bryophytes on vascular plants along a 200‐m environmental gradient in a coastal dune in northern California. We found a positive association between vascular plants and bryophytes across the environmental gradient. Our experiments with two exotic annual grass species showed the effects of bryophytes to be species‐specific and to vary with environmental context. Bryophytes facilitated the survival of one exotic grass species, Vulpia bromoides, at both ends of the environmental gradient. Bryophytes reduced the survival and inflorescence production of the other exotic grass, Bromus diandrus, at one end of the environmental gradient and had no effect at the other end. Our findings provide a test of the effects of native bryophytes on exotic vascular plant invasion and show that these effects can vary dramatically even across local environmental gradients.
Plant species can show considerable morphological and functional variation along environmental gradients. This intraspecific trait variation (ITV) can have important consequences for community ...assembly, biotic interactions, ecosystem functions and responses to global change. However, directly measuring ITV across many species and wide geographic areas is often infeasible. Thus, a method to predict spatial variation in a species’ functional traits could be valuable.
We measured specific leaf area (SLA), height and leaf area (LA) of grasses across California, covering 59 species at 230 sampling locations. We asked how these traits change along climate gradients within each species and used machine learning to predict local trait values for any species at any location based on phylogenetic position, local climate and that species’ mean traits. We then examined how much these local predictions alter patterns of assemblage‐level trait variation across the state.
Most species exhibited higher SLA and grew taller at higher temperatures and produced larger leaves in drier conditions. The random forests predicted spatial variation in functional traits very accurately, with correlations up to 0.97. Because trait records were spatially biased towards warmer areas, and these areas tend to have higher SLA individuals within each species, species means of SLA were upwardly biased. As a result, using species means over‐estimates SLA in the cooler regions of the state. Our results also suggest that height may be substantially under‐predicted in the warmest areas.
Synthesis. Using only species mean traits to characterize the functional composition of communities risks introducing substantial error into trait‐based estimates of ecosystem properties including decomposition rates or NPP. The high performance of random forests in predicting local trait values provides a way forward for estimating high‐resolution patterns of ITV without a massive data collection effort.
Grass species show strong variation in functional traits across their geographic ranges. Mapping this variation would be useful but doing so with direct empirical data is usually unfeasible. Random forests, trained with relatively sparse data across species' ranges, can accurately predict local trait values for a species given the local climate, species characteristics and phylogenetic position, allowing high‐resolution mapping of intraspecific trait variation.
Anthropogenic environmental change can affect species directly by altering physiological rates or indirectly by changing competitive outcomes. The unknown strength of competition-mediated indirect ...effects makes it difficult to predict species abundances in the face of ongoing environmental change. Theory developed with phenomenological competition models shows that indirect effects are weak when coexistence is strongly stabilized, but these models lack a mechanistic link between environmental change and species performance. To extend existing theory, we examined the relationship between coexistence and indirect effects in mechanistic resource competition models. We defined environmental change as a change in resource supply points and quantified the resulting competition-mediated indirect effects on species abundances. We found that the magnitude of indirect effects increases in proportion to niche overlap. However, indirect effects also depend on differences in how competitors respond to the change in resource supply, an insight hidden in nonmechanistic models. Our analysis demonstrates the value of using niche overlap to predict the strength of indirect effects and clarifies the types of indirect effects that global change can have on competing species.
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