Search

Seasonal dynamics in the vertical distribution of leaf area index (LAI) may impact the seasonality of forest productivity in Amazonian forests. However, until recently, fine-scale observations critical to revealing ecological mechanisms underlying these changes have been lacking. To investigate fine-scale variation in leaf area with seasonality and drought we conducted monthly ground-based LiDAR surveys over 4 yr at an Amazon forest site. We analysed temporal changes in vertically structured LAI along axes of both canopy height and light environments. Upper canopy LAI increased during the dry season, whereas lower canopy LAI decreased. The low canopy decrease was driven by highly illuminated leaves of smaller trees in gaps. By contrast, understory LAI increased concurrently with the upper canopy. Hence, tree phenological strategies were stratified by height and light environments. Trends were amplified during a 2015-2016 severe El Niño drought. Leaf area low in the canopy exhibited behaviour consistent with water limitation. Leaf loss from short trees in high light during drought may be associated with strategies to tolerate limited access to deep soil water and stressful leaf environments. Vertically and environmentally structured phenological processes suggest a critical role of canopy structural heterogeneity in seasonal changes in Amazon ecosystem function.

Many regions on Earth are expected to become drier with climate change, which may impact nitrogen (N) cycling rates and availability. We used a meta-analytical approach on the results of field experiments that reduced precipitation and measured N supply (i.e., indices of N mineralization), soil microbial biomass, inorganic N pools (ammonium (NH4+) and nitrate (NO3−)), and nitrous oxide (N2O) emissions. We hypothesized that N supply and N2O emissions would be relatively insensitive to precipitation reduction and that reducing precipitation would increase extractable NH4+ and NO3− concentrations because microbial processes continue, whereas plant N uptake diminishes with drought. In support of this hypothesis, extractable NH4+ increased by 25% overall with precipitation reduction; NH4+ also increased significantly with increasing magnitude of precipitation reduction. In contrast, N supply and extractable NO3− did not change and N2O emissions decreased with reduced precipitation. Across studies microbial biomass appeared unchanged, yet from the diversity of studies, it was clear that proportionally smaller precipitation reductions increased microbial biomass, whereas larger proportional reductions in rainfall reduced microbial biomass; there was a positive intercept (P = 0.005) and a significant negative slope (P = 0.0002) for the regression of microbial biomass versus % precipitation reduction (LnR = −0.009 × (% precipitation reduction) + 0.4021). Our analyses imply that relative to other N variables, N supply is less sensitive to reduced precipitation, whereas processes producing N2O decline. Drought intensity and duration, through sustained N supply, may control how much N becomes vulnerable to loss via hydrologic and gaseous pathways upon rewetting dry soils.

Plants employ strategies of tolerance, endurance, and avoidance to cope with aridity in space and time, yet understanding the differential importance of such strategies in determining patterns of abundance across a heterogeneous landscape is a challenge. Are the species abundant in drier microhabitats also better able to survive drought? Are there relationships among occupied sites and temporal dynamics that derive from physiological capacities to cope with stress or dormancy during unfavorable periods? We used a restoration project conducted on two slope aspects in a subwatershed to test whether species that were more abundant on more water-limited S-facing slopes were also better able to survive an extreme drought. The attempt to place many species uniformly on different slope aspects provided an excellent opportunity to test questions of growth strategy, niche preference, and temporal dynamics. Perennial species that established and grew best on S-facing slopes also had greater increases in cover during years of drought, presumably by employing drought tolerance and endurance techniques. The opposite pattern emerged for annual species that employed drought-escape strategies, such that annuals that occupied S-facing slopes were less abundant during the drought than those that were more abundant on N-facing slopes. Our results clarify how different functional strategies interact with spatial and temporal heterogeneity to influence population and community dynamics and demonstrate how large restoration projects provide opportunities to test fundamental ecological questions.

Eddy covariance (EC) datasets have provided insight into climate determinants of net ecosystem productivity (NEP) and evapotranspiration (ET) in natural ecosystems for decades, but most EC studies were published in serial fashion such that one study's result became the following study's hypothesis. This approach reflects the hypothetico-deductive process by focusing on previously derived hypotheses. A synthesis of this type of sequential inference reiterates subjective biases and may amplify past assumptions about the role, and relative importance, of controls over ecosystem metabolism. Long-term EC datasets facilitate an alternative approach to synthesis: the use of inductive data-based analyses to re-examine past deductive studies of the same ecosystem. Here we examined the seasonal climate determinants of NEP and ET by analyzing a 15-year EC time-series from a subalpine forest using an ensemble of Artificial Neural Networks (ANNs) at the half-day (daytime/nighttime) time-step. We extracted relative rankings of climate drivers and driver-response relationships directly from the dataset with minimal a priori assumptions. The ANN analysis revealed temperature variables as primary climate drivers of NEP and daytime ET, when all seasons are considered, consistent with the assembly of past studies. New relations uncovered by the ANN approach include the role of soil moisture in driving daytime NEP during the snowmelt period, the nonlinear response of NEP to temperature across seasons, and the low relevance of summer rainfall for NEP or ET at the same daytime/nighttime time step. These new results offer a more complete perspective of climate-ecosystem interactions at this site than traditional deductive analyses alone.

Plants employ strategies of tolerance, endurance, and avoidance to cope with aridity in space and time, yet understanding the differential importance of such strategies in determining patterns of abundance across a heterogeneous landscape is a challenge. Are the species abundant in drier microhabitats also better able to survive drought? Are there relationships among occupied sites and temporal dynamics that derive from physiological capacities to cope with stress or dormancy during unfavorable periods? We used a restoration project conducted on two slope aspects in a subwatershed to test whether species that were more abundant on more water-limited S-facing slopes were also better able to survive an extreme drought. The attempt to place many species uniformly on different slope aspects provided an excellent opportunity to test questions of growth strategy, niche preference, and temporal dynamics. Perennial species that established and grew best on S-facing slopes also had greater increases in cover during years of drought, presumably by employing drought tolerance and endurance techniques. The opposite pattern emerged for annual species that employed drought-escape strategies, such that annuals that occupied S-facing slopes were less abundant during the drought than those that were more abundant on N-facing slopes. Our results clarify how different functional strategies interact with spatial and temporal heterogeneity to influence population and community dynamics and demonstrate how large restoration projects provide opportunities to test fundamental ecological questions.

Eddy covariance (EC) datasets have provided insight into climate determinants of net ecosystem productivity (NEP) and evapotranspiration (ET) in natural ecosystems for decades, but most EC studies were published in serial fashion such that one study's result became the following study's hypothesis. This approach reflects the hypothetico-deductive process by focusing on previously derived hypotheses. A synthesis of this type of sequential inference reiterates subjective biases and may amplify past assumptions about the role, and relative importance, of controls over ecosystem metabolism. Long-term EC datasets facilitate an alternative approach to synthesis: the use of inductive data-based analyses to re-examine past deductive studies of the same ecosystem. Here we examined the seasonal climate determinants of NEP and ET by analyzing a 15-year EC time-series from a subalpine forest using an ensemble of Artificial Neural Networks (ANNs) at the half-day (daytime/nighttime) time-step. We extracted relative rankings of climate drivers and driver-response relationships directly from the dataset with minimal a priori assumptions. The ANN analysis revealed temperature variables as primary climate drivers of NEP and daytime ET, when all seasons are considered, consistent with the assembly of past studies. New relations uncovered by the ANN approach include the role of soil moisture in driving daytime NEP during the snowmelt period, the nonlinear response of NEP to temperature across seasons, and the low relevance of summer rainfall for NEP or ET at the same daytime/nighttime time step. These new results offer a more complete perspective of climate-ecosystem interactions at this site than traditional deductive analyses alone.

© 2015 Society for Ecological Restoration Ecological restoration is a multibillion dollar industry critical for improving degraded habitat. However, most restoration is conducted without clearly defined success measures or analysis of costs. Outcomes are influenced by environmental conditions that vary across space and time, yet such variation is rarely considered in restoration planning. Here, we present a cost-effectiveness analysis of terrestrial restoration methods to determine how practitioners may restore the highest native plant cover per dollar spent. We recorded costs of 120 distinct methods and described success in terms of native versus non-native plant germination, growth, cover, and density. We assessed effectiveness using a basic, commonly used metric (% native plant cover) and developed an index of cost-effectiveness (% native cover per dollar spent on restoration). We then evaluated success of multiple methods, given environmental variation across topography and multiple years, and found that the most successful method for restoring high native plant cover is often different from the method that results in the largest area restored per dollar expended, given fixed mitigation budgets. Based on our results, we developed decision-making trees to guide practitioners through established phases of restoration-site preparation, seeding and planting, and maintenance. We also highlight where additional research could inform restoration practice, such as improved seasonal weather forecasts optimizing allocation of funds in time or valuation practices that include costs of specific outcomes in the collection of in lieu fees.

The role of time in ecology has a long history of investigation, but ecologists have largely restricted their attention to the influence of concurrent abiotic conditions on rates and magnitudes of important ecological processes. Recently, however, ecologists have improved their understanding of ecological processes by explicitly considering the effects of antecedent conditions. To broadly help in studying the role of time, we evaluate the length, temporal pattern, and strength of memory with respect to the influence of antecedent conditions on current ecological dynamics. We developed the stochastic antecedent modelling (SAM) framework as a flexible analytic approach for evaluating exogenous and endogenous process components of memory in a system of interest. We designed SAM to be useful in revealing novel insights promoting further study, illustrated in four examples with different degrees of complexity and varying time scales: stomatal conductance, soil respiration, ecosystem productivity, and tree growth. Models with antecedent effects explained an additional 18-28% of response variation compared to models without antecedent effects. Moreover, SAM also enabled identification of potential mechanisms that underlie components of memory, thus revealing temporal properties that are not apparent from traditional treatments of ecological time-series data and facilitating new hypothesis generation and additional research.

The role of time in ecology has a long history of investigation, but ecologists have largely restricted their attention to the influence of concurrent abiotic conditions on rates and magnitudes of important ecological processes. Recently, however, ecologists have improved their understanding of ecological processes by explicitly considering the effects of antecedent conditions. To broadly help in studying the role of time, we evaluate the length, temporal pattern, and strength of memory with respect to the influence of antecedent conditions on current ecological dynamics. We developed the stochastic antecedent modelling (SAM) framework as a flexible analytic approach for evaluating exogenous and endogenous process components of memory in a system of interest. We designed SAM to be useful in revealing novel insights promoting further study, illustrated in four examples with different degrees of complexity and varying time scales: stomatal conductance, soil respiration, ecosystem productivity, and tree growth. Models with antecedent effects explained an additional 18-28% of response variation compared to models without antecedent effects. Moreover, SAM also enabled identification of potential mechanisms that underlie components of memory, thus revealing temporal properties that are not apparent from traditional treatments of ecological time-series data and facilitating new hypothesis generation and additional research.

The success of non-native, invasive species may be due to release from natural enemies, superior competitive abilities, or both. In the Sonoran Desert, Erodium cicutarium has increased in abundance over the last 30 years. While native species in this flora exhibit a strong among-species trade-off between relative growth rate and water-use efficiency, E. cicutarium seems to have a higher relative growth rate for its water-use efficiency value relative to the pattern across native species. This novel trait combination could provide the non-native species with a competitive advantage in this water-limited environment. To test the hypothesis that E. cicutarium is able to achieve high growth rates due to release from native herbivores, we compared the effects of herbivory on E. cicutarium and its native congener, Erodium texanum. We also compared these two species across a range of environmental conditions, both in a common garden and in two distinct seasons in the field, using growth analysis, isotopic compositions and leaf-level gas exchange. Additionally, we compared the competitive abilities of the two Erodium species in a greenhouse experiment. We found no evidence of herbivory to either species. Physiological measurements in a common environment revealed that E. cicutarium was able to achieve high growth rates while simultaneously controlling leaf-level water loss. Non-native E. cicutarium responded to favourable conditions in the field with greater specific leaf area and leaf area ratio than native E. texanum. The non-native Erodium was a stronger competitor than its native congener in a greenhouse competition experiment. The ability to maintain relatively higher values of water-use efficiency:relative growth rate in comparison to the native flora may be what enables E. cictarium to outcompete native species in both wet and dry years, resulting in an increase in abundance in the highly variable Sonoran Desert.

The success of non-native, invasive species may be due to release from natural enemies, superior competitive abilities, or both. In the Sonoran Desert, Erodium cicutarium has increased in abundance over the last 30 years. While native species in this flora exhibit a strong among-species trade-off between relative growth rate and water-use efficiency, E. cicutarium seems to have a higher relative growth rate for its water-use efficiency value relative to the pattern across native species. This novel trait combination could provide the non-native species with a competitive advantage in this water-limited environment. To test the hypothesis that E. cicutarium is able to achieve high growth rates due to release from native herbivores, we compared the effects of herbivory on E. cicutarium and its native congener, Erodium texanum. We also compared these two species across a range of environmental conditions, both in a common garden and in two distinct seasons in the field, using growth analysis, isotopic compositions and leaf-level gas exchange. Additionally, we compared the competitive abilities of the two Erodium species in a greenhouse experiment. We found no evidence of herbivory to either species. Physiological measurements in a common environment revealed that E. cicutarium was able to achieve high growth rates while simultaneously controlling leaf-level water loss. Non-native E. cicutarium responded to favourable conditions in the field with greater specific leaf area and leaf area ratio than native E. texanum. The non-native Erodium was a stronger competitor than its native congener in a greenhouse competition experiment. The ability to maintain relatively higher values of water-use efficiency:relative growth rate in comparison to the native flora may be what enables E. cictarium to outcompete native species in both wet and dry years, resulting in an increase in abundance in the highly variable Sonoran Desert.