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Abstract Reordering of abundances among species is a common response in communities whether affected by anthropogenic drivers or natural disturbance. However, understanding how competitive relationships drive community dynamics under global environmental change remains limited, primarily due to uncertainties related to changes in species interactions and the scarcity of long‐term observations. By combining long‐term data and time series analysis tools, we quantified the compositional dynamics and causal interactions among functional groups of an arid grassland community under chronic nutrient enrichment for 15 years following wildfire. We hypothesized that chronic nutrient addition would promote species reordering among dominant grasses and subordinate annual forbs after wildfire, thereby increasing biomass and compositional variation over the long term. Contrary to expectations, while the abundance of the dominant grassBouteloua eriopoda(black grama) declined immediately after the wildfire, the increase in annual forbs under N addition did not occur until a decade later. Convergent cross‐mapping revealed that annuals were causally influenced by black grama abundance and maintained relatively lower abundance in control plots. However, with N addition, this causal interaction from black grama to annuals disappeared. Accordingly, temporal variability of biomass and community composition increased as the abundance of annuals rose. Combined with evidence of precipitation response, these results imply that the competitive advantage of perennial plants over annual forbs could serve as a stabilizing mechanism for community variability by limiting the response of annuals to precipitation fluctuations. However, this stabilizing process is disrupted by the cumulative effects of chronic nitrogen addition. This long‐term experiment provides new insights into the destabilizing effects of community reordering, without changes in species richness, in response to anthropogenic nutrient loading. 

Abstract Dominant species play a key role in plant communities, influencing the abundance and richness of subordinate species through competitive and facilitative interactions. However, generalizations about the effects of dominant plant species in grasslands can be difficult due to the many differences among communities, such as abiotic conditions and regional species pools. To overcome this issue, we conducted a dominant species removal experiment in two semiarid grassland communities at the Sevilleta National Wildlife Refuge in central New Mexico. These communities had different dominant species but similar abiotic conditions and regional species pools. We studied the effects of removing dominant species on community composition, diversity, and aboveground net primary production (ANPP) over a 23‐year period. Our results showed that dominant grasses suppressed both richness and abundance of subordinate species. In the Chihuahuan Desert grassland, the loss ofBouteloua eriopodawas only partially compensated for by subordinate species, while in the Great Plains grassland, the loss ofBouteloua graciliswas fully compensated for after 16 years. Despite increased species richness, removing dominant species reduced ANPP and resulted in a negative relationship between species richness and ANPP in both grasslands. These results have important implications for ecosystem management and conservation, highlighting the potential impact of losing dominant species on subordinate species and community dynamics. 

Climate change amplifies the global water cycle, making droughts more frequent and more severe. The hot deserts of the U.S. rely on the stability and frequency of water availability in order to sustain biological communities, making these ecosystems incredibly vulnerable to anticipated alterations in the water cycle. This project seeks to understand which biotic and abiotic variables are principle in determining desert ecosystem sensitivity to drought? To answer these questions, we have installed a drought manipulation that will simulate an extreme drought event by reducing annual precipitation by 66% in seven desert sites. Plant abundance data are collected annually to track changes in the plant community. Data collection began in Spring 2018. Treatments at three Sevilleta sites began in Fall 2018 after data collection in October 2018. Treatments started at four sites in Arizona and California in March and April of 2019 and spring pretreatment data collection. The treatments will last for four years. 

Abstract QuestionsReordering of dominant species is an important mechanism of community response to global environmental change. We asked how wildfire (apulseevent) interacts with directional changes in climate (environmentalpresses) to affect plant community dynamics in a Chihuahuan Desert grassland. LocationSevilleta National Wildlife Refuge, Socorro County, New Mexico, USA. MethodsVegetation cover by species was measured twice each year from 1989 to 2019 along two permanently located 400‐m long line intercept transects, one in Chihuahuan Desert grassland, and the second in the ecotone between Chihuahuan Desert and Great Plains grasslands. Trends in community structure were plotted over time, and climate sensitivity functions were used to predict how changes in the Pacific Decadal Oscillation (PDO) affected vegetation dynamics. ResultsCommunity composition was undergoing gradual change in the absence of disturbance in the ecotone and desert grassland. These changes were related to the reordering of abundances between two foundation grasses,Bouteloua eriopodaandB. gracilis, that together account for >80% of above‐ground primary production. However, reordering varied over time in response to wildfire (apulse) and changes in the PDO (apress). Community dynamics were initially related to the warm and cool phases of the PDO, but in the ecotone these relationships changed following wildfire, which reset the system. ConclusionSpecies reordering is an important component of community dynamics in response to ecological presses. However, reordering is a complex, non‐linear process in response to ecological presses that may change over time and interact with pulse disturbances. 

Abstract Human activities are altering ecological communities around the globe. Understanding the implications of these changes requires that we consider the composition of those communities. However, composition can be summarized by many metrics which in turn are influenced by different ecological processes. For example, incidence‐based metrics strongly reflect species gains or losses, while abundance‐based metrics are minimally affected by changes in the abundance of small or uncommon species. Furthermore, metrics might be correlated with different predictors. We used a globally distributed experiment to examine variation in species composition within 60 grasslands on six continents. Each site had an identical experimental and sampling design: 24 plots × 4 years. We expressed compositional variation within each site—not across sites—using abundance‐ and incidence‐based metrics of the magnitude of dissimilarity (Bray–Curtis and Sorensen, respectively), abundance‐ and incidence‐based measures of the relative importance of replacement (balanced variation and species turnover, respectively), and species richness at two scales (per plot‐year [alpha] and per site [gamma]). Average compositional variation among all plot‐years at a site was high and similar to spatial variation among plots in the pretreatment year, but lower among years in untreated plots. For both types of metrics, most variation was due to replacement rather than nestedness. Differences among sites in overall within‐site compositional variation were related to several predictors. Environmental heterogeneity (expressed as the CV of total aboveground plant biomass in unfertilized plots of the site) was an important predictor for most metrics. Biomass production was a predictor of species turnover and of alpha diversity but not of other metrics. Continentality (measured as annual temperature range) was a strong predictor of Sorensen dissimilarity. Metrics of compositional variation are moderately correlated: knowing the magnitude of dissimilarity at a site provides little insight into whether the variation is driven by replacement processes. Overall, our understanding of compositional variation at a site is enhanced by considering multiple metrics simultaneously. Monitoring programs that explicitly incorporate these implications, both when designing sampling strategies and analyzing data, will have a stronger ability to understand the compositional variation of systems and to quantify the impacts of human activities.