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Abstract Two of the major factors that control the composition of herbaceous plant communities are competition for limiting soil resources and herbivory. We present results from a 14-year full factorial experiment in a tallgrass prairie ecosystem that crossed nitrogen (N) addition with fencing to exclude white-tailed deer,Odocoileus virginianus, from half the plots. Deer presence was associated with only modest decreases in aboveground plant biomass (14% decrease; −45 ± 19 g m⁻²) with no interaction with N addition. N addition at 5.44 and 9.52 g N m⁻² year⁻¹led to increases in biomass. There were weak increases in species richness associated with deer presence, but only for no or low added N (1 and 2 g N m⁻² year⁻¹). However, the presence of deer greatly impacted the abundances of some of the dominant perennial forb species, but not the dominant grasses. Deer presence increased the abundance of the forbArtemisia ludovicianaby 34 ± 12 SE g m⁻²(94%) and decreased the forbSolidago rigidaby 32 ± 13 SE g m⁻²(79%). We suggest that these changes may have resulted from trade-offs in plant competitive ability for soil N versus resistance to deer herbivory. Field observations suggest deer acted as florivores, mainly consuming the flowers of susceptible forb species. The preferential consumption of flowers of forbs that seem to be superior N competitors appears to create an axis of interspecific niche differentiation. The overpopulation of white-tailed deer in many tallgrass reserves likely structures the abundance of forb species. 

ABSTRACT Biotic complexity, encompassing both competitive interactions within trophic levels and consumptive interactions among trophic levels, plays a fundamental role in maintaining ecosystem stability. While theory and experiments have established that plant diversity enhances ecosystem stability, the role of consumers in the diversity–stability relationships remains elusive. In a decade‐long grassland biodiversity experiment, we investigated how heterotrophic consumers (e.g., insects and fungi) interact with plant diversity to affect the temporal stability of plant community biomass. Plant diversity loss reduces community stability due to increased synchronisation among species but enhances the population‐level stability of the remaining plant species. Reducing trophic complexity via pesticide treatments does not directly affect either community‐ or population‐level stability but further amplifies plant species synchronisation. Our findings demonstrate that the loss of arthropod or fungal consumers can destabilise plant communities by exacerbating synchronisation, underscoring the crucial role of trophic complexity in maintaining ecological stability. 

Agriculture’s global environmental impacts are widely expected to continue expanding, driven by population and economic growth and dietary changes. This Review highlights climate change as an additional amplifier of agriculture’s environmental impacts, by reducing agricultural productivity, reducing the efficacy of agrochemicals, increasing soil erosion, accelerating the growth and expanding the range of crop diseases and pests, and increasing land clearing. We identify multiple pathways through which climate change intensifies agricultural greenhouse gas emissions, creating a potentially powerful climate change–reinforcing feedback loop. The challenges raised by climate change underscore the urgent need to transition to sustainable, climate-resilient agricultural systems. This requires investments that both accelerate adoption of proven solutions that provide multiple benefits, and that discover and scale new beneficial processes and food products. 

While both species richness and ecosystem stability increase with area, how these scaling patterns are linked remains unclear. Our theoretical and empirical analyses of plant and fish communities show that the spatial scaling of ecosystem stability is determined primarily by the scaling of species asynchrony, which is in turn driven by the scaling of species richness. In wetter regions, plant species richness and ecosystem stability both exhibit faster accumulation with area, implying potentially greater declines in biodiversity and stability following habitat loss. The decline in ecosystem stability after habitat loss can be delayed, creating a stability debt mirroring the extinction debt of species. By unifying two foundational scaling laws in ecology, our work underscores that ongoing biodiversity loss may destabilize ecosystems across spatial scales. 

Abstract Plant diversity effects on community productivity often increase over time. Whether the strengthening of diversity effects is caused by temporal shifts in species-level overyielding (i.e., higher species-level productivity in diverse communities compared with monocultures) remains unclear. Here, using data from 65 grassland and forest biodiversity experiments, we show that the temporal strength of diversity effects at the community scale is underpinned by temporal changes in the species that yield. These temporal trends of species-level overyielding are shaped by plant ecological strategies, which can be quantitatively delimited by functional traits. In grasslands, the temporal strengthening of biodiversity effects on community productivity was associated with increasing biomass overyielding of resource-conservative species increasing over time, and with overyielding of species characterized by fast resource acquisition either decreasing or increasing. In forests, temporal trends in species overyielding differ when considering above- versus belowground resource acquisition strategies. Overyielding in stem growth decreased for species with high light capture capacity but increased for those with high soil resource acquisition capacity. Our results imply that a diversity of species with different, and potentially complementary, ecological strategies is beneficial for maintaining community productivity over time in both grassland and forest ecosystems. 

Abstract To determine which types of plant traits might better explain ecosystem functioning and plant evolutionary histories, we compiled 42 traits for each of 15 perennial species in a biodiversity experiment. We used every possible combination of three traits to cluster species. Across these 11,480 combinations, clusters generated using tissue %Ca, %N and %K best mapped onto phylogeny. Moreover, for the 15 best combinations of three traits, 82% of traits were chemical, 16% morphological and 2% metabolic. The diversity‐dependence of ecosystem productivity was better explained by the %Ca, %N and %K clusters: compared to adding a new species at random, adding a species from an absent cluster/clade better‐explained gains in productivity. Species number impacted productivity only when all clusters were present. Our results suggest that tissue elemental chemistry might be more phylogenetically conserved and more strongly related to ecosystem functioning than commonly measured morphological and physiological traits, a possibility that merits exploration. 

Abstract Mounting evidence suggests that plant–soil feedbacks (PSF) may determine plant community structure. However, we still have a poor understanding of how predictions from short‐term PSF experiments compare with outcomes of long‐term field experiments involving competing plants. We conducted a reciprocal greenhouse experiment to examine how the growth of prairie grass species depended on the soil communities cultured by conspecific or heterospecific plant species in the field. The source soil came from monocultures in a long‐term competition experiment (LTCE; Cedar Creek Ecosystem Science Reserve, MN, USA). Within the LTCE, six species of perennial prairie grasses were grown in monocultures or in eight pairwise competition plots for 12 years under conditions of low or high soil nitrogen availability. In six cases, one species clearly excluded the other; in two cases, the pair appeared to coexist. In year 15, we gathered soil from all 12 soil types (monocultures of six species by two nitrogen levels) and grew seedlings of all six species in each soil type for 7 weeks. Using biomass estimates from this greenhouse experiment, we predicted coexistence or competitive exclusion using pairwise PSFs, as derived by Bever and colleagues, and compared model predictions to observed outcomes within the LTCE. Pairwise PSFs among the species pairs ranged from negative, which is predicted to promote coexistence, to positive, which is predicted to promote competitive exclusion. However, these short‐term PSF predictions bore no systematic resemblance to the actual outcomes of competition observed in the LTCE. Other forces may have more strongly influenced the competitive interactions or critical assumptions that underlie the PSF predictions may not have been met. Importantly, the pairwise PSF score derived by Bever et al. is only valid when the two species exhibit an internal equilibrium, corresponding to the Lotka–Volterra competition outcomes of stable coexistence and founder control. Predicting the other two scenarios, competitive exclusion by either species irrespective of initial conditions, requires measuring biomass in uncultured soil, which is methodologically challenging. Subject to several caveats that we discuss, our results call into question whether long‐term competitive outcomes in the field can be predicted from the results of short‐term PSF experiments. 

Modeling fire spread as an infection process is intuitive: An ignition lights a patch of fuel, which infects its neighbor, and so on. Infection models produce nonlinear thresholds, whereby fire spreads only when fuel connectivity and infection probability are sufficiently high. These thresholds are fundamental both to managing fire and to theoretical models of fire spread, whereas applied fire models more often apply quasi-empirical approaches. Here, we resolve this tension by quantifying thresholds in fire spread locally, using field data from individual fires ( n = 1,131) in grassy ecosystems across a precipitation gradient (496 to 1,442 mm mean annual precipitation) and evaluating how these scaled regionally (across 533 sites) and across time (1989 to 2012 and 2016 to 2018) using data from Kruger National Park in South Africa. An infection model captured observed patterns in individual fire spread better than competing models. The proportion of the landscape that burned was well described by measurements of grass biomass, fuel moisture, and vapor pressure deficit. Regionally, averaging across variability resulted in quasi-linear patterns. Altogether, results suggest that models aiming to capture fire responses to global change should incorporate nonlinear fire spread thresholds but that linear approximations may sufficiently capture medium-term trends under a stationary climate.