Letter to Gene Teitelbaum regarding mailings for the Lucile Elliott Scholarship, September 23, 1982

A letter from Brian S. Polley to Gene Teitelbaum discussing Polley\u27s views on offering multiple opportunities for the 1982-1983 Lucile Elliott Scholarship

Variability in community productivity—mediating effects of vegetation attributes

Plant productivity varies through time in response to environmental fluctuations. Reducing variability in productivity requires an improved understanding of how plant community attributes interact with environmental fluctuations to influence plant growth dynamics. We evaluated links between two community attributes, species diversity and abundance‐weighted values of specific leaf area (SLA), and temporal variability in grassland productivity at patch (local) and aggregate (multipatch) spatial scales. Aggregate communities were created by combining patches of spatially distinct communities of perennial plant species from grassland biodiversity experiments in Texas, USA. Interannual variability in above‐ground net primary productivity (ANPP) of aggregate communities was analysed as a function of two multiplicative components, mean temporal variability in the ANPP of patches and temporal synchrony in ANPP dynamics among patches. We used regression analyses to determine whether temporal variability in aggregate ANPP and its components were correlated with either species diversity or community‐weighted SLA over 5 years. Temporal variability in ANPP of aggregate communities was strongly correlated with temporal variability in patch ANPP. Increasing mean SLA reduced ANPP variability of aggregate communities by increasing mean productivity. Increased temporal changes in patch‐scale SLA further reduced temporal variability in aggregate ANPP by reducing effects of precipitation fluctuations on productivity. Conversely, increasing species diversity over the narrow range measured increased temporal variability in aggregate ANPP. High diversity was associated with reduced dominance of temporally stable C4 grasses. Our results implicate means and patch‐scale temporal dynamics in community SLA as potential indicators of variability in grassland primary productivity through time

Species composition but not diversity explains recovery from the 2011 drought in Texas grasslands

Extreme droughts can have profound direct consequences for grassland ecosystems, but it is poorly known how ecosystems recover from drought and what ecological factors are associated with recovery. Recovery occurs when ecosystem functioning returns to values observed prior to a perturbation. Here, we tested for ecosystem recovery after an extreme drought in 2011 in previously established native and exotic experimental communities in Central Texas. Planted mixtures of all native and all exotic species were crossed with a summer irrigation treatment, with eight community compositions (random draws) per treatment. Prior to the drought, native plots had higher diversity than exotic plots, which sets up the prediction that the high-diversity native plots will recover more quickly than exotics. The extreme drought decreased rain-use efficiency ([RUE], annual biomass production per unit of rainfall) by 82%. Rain-use efficiency remained well below pre-drought levels during the growing season after the drought. However, on average, RUE recovered to pre-drought levels by the second growing season following drought. Exotic communities showed higher RUE than native communities, and irrigation significantly reduced RUE in both exotic and native communities across years. Interestingly, not all of the mixtures recovered from the drought, and recovery was associated with species composition, but not diversity. Rain-use efficiency recovery from drought was greatest in native communities in which the proportion of C3 forb biomass increased during and following drought and in exotic communities with a low proportion of short grass biomass. Extreme droughts can exert differential impacts on plant functional groups, leading to a drought legacy effect that reduces recovery with possible long-term repercussions

Biotic Regulation of CO2 Uptake–Climate Responses: Links to Vegetation Properties

Identifying the plant traits and patterns of trait distribution in communities that are responsible for biotic regulation of CO2 uptake–climate responses remains a priority for modeling terrestrial C dynamics. We used remotely sensed estimates of gross primary productivity (GPP) from plots planted to different combinations of perennial grassland species in order to determine links between traits and GPP–climate relationships. Climatic variables explained about 50% of the variance in temporal trends in GPP despite large variation in CO2 uptake among seasons, years, and plots of differing composition. GPP was highly correlated with contemporary changes in net radiation (Rn) and precipitation deficit (potential evapotranspiration minus precipitation) but was negatively correlated with precipitation summed over 210 days prior to flux measurements. Plots differed in GPP–Rn and GPP–water (deficit, precipitation) relationships. Accounting for differences in GPP–climate relationships explained an additional 11% of variance in GPP. Plot differences in GPP–Rn and GPP–precipitation slopes were linked to differences in community-level light-use efficiency (GEE*). Plot differences in GPP–deficit slopes were linked to differences in a species abundance-weighted index of specific leaf area (SLA). GEE* and weighted SLA represent vegetation properties that may regulate how CO2 uptake responds to climatic variation in grasslands

Spectrally derived values of community leaf dry matter content link shifts in grassland composition with change in biomass production

Leaf traits link environmental effects on plant species abundances to changes in ecosystem processes but are a challenge to measure regularly and over large areas. We used measurements of canopy reflectance from grassland communities to derive a regression model for one leaf trait, leaf dry matter content (LDMC). Partial least squares regression (PLSR) analysis was used to model community‐weighted (species abundance‐weighted) values of LDMC as a function of canopy reflectance in visible and near‐infrared (NIR) wavebands. The PLSR model then was applied to airborne measurements of canopy reflectance to determine how community LDMC interacts with inter‐annual variation in precipitation to influence the normalized difference vegetation index (NDVI), a surrogate of aboveground biomass production, of restored grassland during spring over 4 years. LDMC was well‐described by a PLSR model that included reflectance measurements located primarily in red edge and NIR portions of the spectrum. Community LDMC decreased as annual forb species became more abundant and was negatively correlated with maximum values of NDVI. Decreased precipitation reduced NDVI (biomass production) both by increasing community LDMC (LDMC response) and reducing the slope of the NDVI‐LDMC relationship (LDMC effect on NDVI). We find that grassland LDMC is well‐described by a regression model using canopy reflectance in red edge and NIR wavebands. Our results demonstrate the utility of spectral estimates of LDMC for discerning shifts in grassland composition and predicting consequences for production‐related ecosystem functions

Spectral Heterogeneity Predicts Local-Scale Gamma and Beta Diversity of Mesic Grasslands

Plant species diversity is an important metric of ecosystem functioning, but field assessments of diversity are constrained in number and spatial extent by labor and other expenses. We tested the utility of using spatial heterogeneity in the remotely-sensed reflectance spectrum of grassland canopies to model both spatial turnover in species composition and abundances (β diversity) and species diversity at aggregate spatial scales (γ diversity). Shannon indices of γ and β diversity were calculated from field measurements of the number and relative abundances of plant species at each of two spatial grains (0.45 m2 and 35.2 m2) in mesic grasslands in central Texas, USA. Spectral signatures of reflected radiation at each grain were measured from ground-level or an unmanned aerial vehicle (UAV). Partial least squares regression (PLSR) models explained 59–85% of variance in γ diversity and 68–79% of variance in β diversity using spatial heterogeneity in canopy optical properties. Variation in both γ and β diversity were associated most strongly with heterogeneity in reflectance in blue (350–370 nm), red (660–770 nm), and near infrared (810–1050 nm) wavebands. Modeled diversity was more sensitive by a factor of three to a given level of spectral heterogeneity when derived from data collected at the small than larger spatial grain. As estimated from calibrated PLSR models, β diversity was greater, but γ diversity was smaller for restored grassland on a lowland clay than upland silty clay soil. Both γ and β diversity of grassland can be modeled by using spatial heterogeneity in vegetation optical properties provided that the grain of reflectance measurements is conserved

Plant invasions differentially affected by diversity and dominant species in native- and exotic-dominated grasslands

Plant invasions are an increasingly serious global concern, especially as the climate changes. Here, we explored how plant invasions differed between native- and novel exotic-dominated grasslands with experimental addition of summer precipitation in Texas in 2009. Exotic species greened up earlier than natives by an average of 18 days. This was associated with a lower invasion rate early in the growing season compared to native communities. However, invasion rate did not differ significantly between native and exotic communities across all sampling times. The predictors of invasion rate differed between native and exotic communities, with invasion being negatively influenced by species richness in natives and by dominant species in exotics. Interestingly, plant invasions matched the bimodal pattern of precipitation in Temple, Texas, and did not respond to the pulse of precipitation during the summer. Our results suggest that we will need to take different approaches in understanding of invasion between native and exotic grasslands. Moreover, with anticipated increasing variability in precipitation under global climate change, plant invasions may be constrained in their response if the precipitation pulses fall outside the normal growing period of invaders