The Unique Contribution of Rothamsted to Ecological Research at Large Temporal Scales

Long-term trends in migrating Brassicogethes aeneus in the UK

BACKGROUND

The pollen beetle (Brassicogethes aeneus) causes significant yield loss in oilseed rape (Brassica napus). Predicting population changes remains a scientific challenge, especially since its phenology and abundance varies dramatically over space and time. We used generalized additive models to investigate the long-term trends in pollen beetle annual, seasonal and monthly counts from Rothamsted 12.2 m suction-traps. We hypothesised that the beetle's abundance is positively related to the area of oilseed rape at a national and regional level. We used random forest models to investigate the inter-generational relationship within years.

RESULTS

Although Brassicogethes aeneus annual counts and area of oilseed rape grown in the UK both increased by 162% and 113%, respectively, over the time period studied, they were not significantly related. The size of the immigrating pollen beetle population (up to 1 June) can be explained both by the size of the population in the previous summer and prevailing winter temperatures, indicating a positive feedback mechanism.

CONCLUSION

Currently, pollen beetle numbers continue to increase in the UK, meaning that control issues may persist. However the relationship between counts in spring, during the susceptible phase of the crop, and counts in the previous summer indicates that it may be possible to forecast the counts of the spring migration of Brassicogethes aeneus a few months in advance using suction-trap samples, which could aid decisions on control options. © 2023 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

A new Rothamsted long-term field experiment for the twenty-first century: principles and practice

Agriculture faces potentially competing societal demands to produce food, fiber and fuel while reducing negative environmental impacts and delivering regulating, supporting and cultural ecosystem services. This necessitates a new generation of long-term agricultural field experiments designed to study the behavior of contrasting cropping systems in terms of multiple outcomes. We document the principles and practices of a new long-term experiment of this type at Rothamsted, established at two contrasting sites in 2017 and 2018, and report initial yield data at the crop and system level. The objective of the Large-Scale Rotation Experiment was to establish gradients of system properties and outcomes to improve our fundamental understanding of UK cropping systems. It is composed of four management factors-phased rotations, cultivation (conventional vs reduced tillage), nutrition (additional organic amendment vs standard mineral fertilization) and crop protection (conventional vs smart crop protection). These factors were combined in a balanced design resulting in 24 emergent cropping systems at each site and can be analyzed at the level of the system or component management factors. We observed interactions between management factors and with the environment on crop yields, justifying the systems level, multi-site approach. Reduced tillage resulted in lower wheat yields but the effect varied with rotation, previous-crop and site. Organic amendments significantly increased spring barley yield by 8% on average though the effect again varied with site. The plowed cropping systems tended to produce higher caloric yield overall than systems under reduced tillage. Additional response variables are being monitored to study synergies and trade-offs with outcomes other than yield at the cropping system level. The experiment has been established as a long-term resource for inter-disciplinary research. By documenting the design process, we aim to facilitate the adoption of similar approaches to system-scale agricultural experimentation to inform the transition to more sustainable cropping systems.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13593-023-00914-8.

Agricultural intensification and climate change have increased the threat from weeds

Weeds represent a significant threat to crop yields and global food security. We analysed data on weed competition from the world's longest running agricultural experiment to ask whether potential yield losses from weeds have increased in response to management and environmental change since the advent of the Green Revolution in the 1960s. On plots where inorganic nitrogen fertiliser has been applied, potential yield losses from weeds have consistently increased since 1969. This was explained by a warming climate, measured as air temperature averaged over the growing season for the weeds, and a shift towards shorter crop cultivars. Weeds also reduced yield proportionally more on plots with higher rates of nitrogen which had higher yields when weeds were controlled; the relative benefit of herbicides was, therefore, proportional to potential crop yield. Reducing yield losses from weed competition is increasingly challenging because of the evolution of herbicide resistance. Our results demonstrate that weeds now represent a greater inherent threat to crop production than before the advent of herbicides and integrated, sustainable solutions to weed management are urgently needed to protect the high yield potential of modern crop genotypes.

Changes in the analysis of temporal community dynamics data: a 29-year literature review

BACKGROUND

Understanding how biological communities change over time is of increasing importance as Earth moves into the Anthropocene. A wide variety of methods are used for multivariate community analysis and are variously applied to research that aims to characterise temporal dynamics in community composition. Understanding these methods and how they are applied is useful for determining best practice in community ecology.

METHODOLOGY

We reviewed the ecological literature from 1990 to 2018 that used multivariate methods to address questions of temporal community dynamics. For each paper that fulfilled our search criteria, we recorded the types of multivariate analysis used to characterise temporal community dynamics in addition to the research aim, habitat type, location, taxon and the experimental design.

RESULTS

Most studies had relatively few temporal replicates; the median number was seven time points. Nearly 70% of studies applied more than one analysis method; descriptive methods such as bar graphs and ordination were the most commonly applied methods. Surprisingly, the types of analyses used were only related to the number of temporal replicates, but not to research aim or any other aspects of experimental design such as taxon, or habitat or year of study.

CONCLUSIONS

This review reveals that most studies interested in understanding community dynamics use relatively short time series meaning that several, more sophisticated, temporal analyses are not widely applicable. However, newer methods using multivariate dissimilarities are growing in popularity and many can be applied to time series of any length.

Contrasting population structure and demographic history of cereal aphids in different environmental and agricultural landscapes

Genetic diversity of populations has important ecological and evolutionary consequences, whose understanding is fundamental to improve the sustainability of agricultural production. Studies of how differences in agricultural management and environment influence the population structure of insect pests are central to predict outbreaks and optimize control programs. Here, we have studied the population genetic diversity and evolution of Sitobion avenae and Sitobion miscanthi, which are among the most relevant aphid pests of cereals across Europe and Asia, respectively. We have used genotyping by sequencing (GBS) to identify genome-wide single nucleotide polymorphisms (SNPs) to infer the geographic structure and migration patterns. In the present study, we show that the population structure in present-day populations is different from that described in previous studies, which suggest that they have evolved recently possibly as a response to human-induced changes in agriculture. This study shows that S. avenae in England is predominantly parthenogenetic and there has been a demographic and spatial expansion of a single genetic cluster, which could correspond with the insecticide resistance superclone identified in previous studies. Conversely, in China, S. miscanthi populations are mostly cyclical parthenogenetic, with one sexual stage in autumn to produce overwintering eggs, and there are six genetically differentiated subpopulations and high genetic differentiation between geographic locations, which suggests that further taxonomical research is needed. Unlike S. avenae in England, there is no evidence for insecticide resistance and there is no predominance of a single lineage in S. miscanthi in China.

Unlocking the potential of historical abundance datasets to study biomass change in flying insects

Trends in insect abundance are well established in some datasets, but far less is known about how abundance measures translate into biomass trends. Moths (Lepidoptera) provide particularly good opportunities to study trends and drivers of biomass change at large spatial and temporal scales, given the existence of long-term abundance datasets. However, data on the body masses of moths are required for these analyses, but such data do not currently exist.To address this data gap, we collected empirical data in 2018 on the forewing length and dry mass of field-sampled moths, and used these to train and test a statistical model that predicts the body mass of moth species from their forewing lengths (with refined parameters for Crambidae, Erebidae, Geometridae and Noctuidae).Modeled biomass was positively correlated, with high explanatory power, with measured biomass of moth species (R 2 = 0.886 ± 0.0006, across 10,000 bootstrapped replicates) and of mixed-species samples of moths (R 2 = 0.873 ± 0.0003), showing that it is possible to predict biomass to an informative level of accuracy, and prediction error was smaller with larger sample sizes.Our model allows biomass to be estimated for historical moth abundance datasets, and so our approach will create opportunities to investigate trends and drivers of insect biomass change over long timescales and broad geographic regions.

Plant-microbe networks in soil are weakened by century-long use of inorganic fertilizers

Understanding the changes in plant-microbe interactions is critically important for predicting ecosystem functioning in response to human-induced environmental changes such as nitrogen (N) addition. In this study, the effects of a century-long fertilization treatment (> 150 years) on the networks between plants and soil microbial functional communities, detected by GeoChip, in grassland were determined in the Park Grass Experiment at Rothamsted Research, UK. Our results showed that plants and soil microbes have a consistent response to long-term fertilization-both richness and diversity of plants and soil microbes are significantly decreased, as well as microbial functional genes involved in soil carbon (C), nitrogen (N) and phosphorus (P) cycling. The network-based analyses showed that long-term fertilization decreased the complexity of networks between plant and microbial functional communities in terms of node numbers, connectivity, network density and the clustering coefficient. Similarly, within the soil microbial community, the strength of microbial associations was also weakened in response to long-term fertilization. Mantel path analysis showed that soil C and N contents were the main factors affecting the network between plants and microbes. Our results indicate that century-long fertilization weakens the plant-microbe networks, which is important in improving our understanding of grassland ecosystem functions and stability under long-term agriculture management.

Climate-induced phenology shifts linked to range expansions in species with multiple reproductive cycles per year

Advances in phenology (the annual timing of species’ life-cycles) in response to climate change are generally viewed as bioindicators of climate change, but have not been considered as predictors of range expansions. Here, we show that phenology advances combine with the number of reproductive cycles per year (voltinism) to shape abundance and distribution trends in 130 species of British Lepidoptera, in response to ~0.5 °C spring-temperature warming between 1995 and 2014. Early adult emergence in warm years resulted in increased within- and between-year population growth for species with multiple reproductive cycles per year (n = 39 multivoltine species). By contrast, early emergence had neutral or negative consequences for species with a single annual reproductive cycle (n = 91 univoltine species), depending on habitat specialisation. We conclude that phenology advances facilitate polewards range expansions in species exhibiting plasticity for both phenology and voltinism, but may inhibit expansion by less flexible species.

Many species’ life cycles have moved earlier in the year because of climate change, but we do not know the consequences for range expansions. The authors show that these advances promote range expansions in species with multiple reproductive cycles per year, but not in species with only one.

Spatial and habitat variation in aphid, butterfly, moth and bird phenologies over the last half century

Global warming has advanced the timing of biological events, potentially leading to disruption across trophic levels. The potential importance of phenological change as a driver of population trends has been suggested. To fully understand the possible impacts, there is a need to quantify the scale of these changes spatially and according to habitat type. We studied the relationship between phenological trends, space and habitat type between 1965 and 2012 using an extensive UK dataset comprising 269 aphid, bird, butterfly and moth species. We modelled phenologies using generalized additive mixed models that included covariates for geographical (latitude, longitude, altitude), temporal (year, season) and habitat terms (woodland, scrub, grassland). Model selection showed that a baseline model with geographical and temporal components explained the variation in phenologies better than either a model in which space and time interacted or a habitat model without spatial terms. This baseline model showed strongly that phenologies shifted progressively earlier over time, that increasing altitude produced later phenologies and that a strong spatial component determined phenological timings, particularly latitude. The seasonal timing of a phenological event, in terms of whether it fell in the first or second half of the year, did not result in substantially different trends for butterflies. For moths, early season phenologies advanced more rapidly than those recorded later. Whilst temporal trends across all habitats resulted in earlier phenologies over time, agricultural habitats produced significantly later phenologies than most other habitats studied, probably because of nonclimatic drivers. A model with a significant habitat-time interaction was the best-fitting model for birds, moths and butterflies, emphasizing that the rates of phenological advance also differ among habitats for these groups. Our results suggest the presence of strong spatial gradients in mean seasonal timing and nonlinear trends towards earlier seasonal timing that varies in form and rate among habitat types.