scholarly journals Fingerprints of high-dimensional coexistence in complex ecosystems

2019 ◽  
Author(s):  
Matthieu Barbier ◽  
Claire de Mazancourt ◽  
Michel Loreau ◽  
Guy Bunin

AbstractThe coexistence of many competing species is a long-standing puzzle in ecology. Classic niche theory explains coexistence by trade-offs between a few essential species traits. Here we study an unexplored frontier of this theory: we assume that coexistence is intrinsically high-dimensional, arising from many traits and trade-offs at once. Species interactions then appear almost random, but their disorder hides a diffuse statistical structure: competitors that become successful start by subtly favoring each other, and partitioning their impacts on other species. We validate our quantitative predictions using data from grassland biodiversity experiments. We conclude that a high biodiversity can be attained through a pattern of collective organization that cannot be understood at the species level, but exhibits the fingerprint of high-dimensional interactions.

2019 ◽  
Author(s):  
E. Fernando Cagua ◽  
Audrey Lustig ◽  
Jason M. Tylianakis ◽  
Daniel B. Stouffer

AbstractWhat determines whether or not a species is a generalist or a specialist? Evidence that the environment can influence species interactions is rapidly accumulating. However, a systematic link between environment and the number of partners a species interacts with has been elusive so far. Presumably, because environmental gradients appear to have contrasting effects on species depending on the environmental variable. Here, we test for a relationship between the stresses imposed by the environment, instead of environmental gradients directly, and species specialisation using a global dataset of plant-pollinator interactions. We found that the environment can play a significant effect on specialisation, even when accounting for community composition, likely by interacting with species’ traits and evolutionary history. Species that have a large number of interactions are more likely to focus on a smaller number of, presumably higher-quality, interactions under stressful environmental conditions. Contrastingly, the specialists present in multiple locations are more likely to broaden their niche, presumably engaging in opportunistic interactions to cope with increased environmental stress. Indeed, many apparent specialists effectively behave as facultative generalists. Overall, many of the species we analysed are not inherently generalist or specialist. Instead, species’ level of specialisation should be considered on a relative scale depending on where they are found and the environmental conditions at that location.


2021 ◽  
Vol 9 ◽  
Author(s):  
Martin Drechsler

An important mechanism of species co-existence in spatially structured landscapes is the competition-colonisation trade-off which states that co-existence of competing species is possible if, all other things equal, the better competitor is the worse coloniser. The effectiveness of this trade-off for the facilitation of co-existence, however, is likely to depend on the spatial arrangement of the habitat, because too strong agglomeration of the habitat may overly benefit the strong competitor (being the poor disperser), implying extinction of the inferiour competitor, while too much dispersion of the habitat may drive the superiour competitor (being the inferiour coloniser) to extinction. In working landscapes, biodiversity conservation is often induced through conservation payments that offset the forgone profits incurred by the conservation measure. To control the spatial arrangement of conservation measures and habitats in a conservation payment scheme, the agglomeration bonus has been proposed to provide financial incentives for allocating conservation measures in the vicinity of other sites with conservation measures. This paper presents a generic spatially explicit ecological-economic simulation model to explore the ability of the agglomeration bonus to cost-effectively conserve multiple competing species that differ by their competition strengths, their colonisation rates and their dispersal ranges. The interacting effects of the agglomeration bonus and different species traits and their trade-offs on the species richness in the model landscape are analysed. Recommendations for the biodiversity-maximising design of agglomeration bonus schemes are derived.


2021 ◽  
pp. 1-12
Author(s):  
Jian Zheng ◽  
Jianfeng Wang ◽  
Yanping Chen ◽  
Shuping Chen ◽  
Jingjin Chen ◽  
...  

Neural networks can approximate data because of owning many compact non-linear layers. In high-dimensional space, due to the curse of dimensionality, data distribution becomes sparse, causing that it is difficulty to provide sufficient information. Hence, the task becomes even harder if neural networks approximate data in high-dimensional space. To address this issue, according to the Lipschitz condition, the two deviations, i.e., the deviation of the neural networks trained using high-dimensional functions, and the deviation of high-dimensional functions approximation data, are derived. This purpose of doing this is to improve the ability of approximation high-dimensional space using neural networks. Experimental results show that the neural networks trained using high-dimensional functions outperforms that of using data in the capability of approximation data in high-dimensional space. We find that the neural networks trained using high-dimensional functions more suitable for high-dimensional space than that of using data, so that there is no need to retain sufficient data for neural networks training. Our findings suggests that in high-dimensional space, by tuning hidden layers of neural networks, this is hard to have substantial positive effects on improving precision of approximation data.


2013 ◽  
Vol 53 (8) ◽  
pp. 796 ◽  
Author(s):  
Karl Behrendt ◽  
Oscar Cacho ◽  
James M. Scott ◽  
Randall Jones

This study addresses the problem of balancing the trade-offs between the need for animal production, profit, and the goal of achieving persistence of desirable species within grazing systems. The bioeconomic framework applied in this study takes into account the impact of climate risk and the management of pastures and grazing rules on the botanical composition of the pasture resource, a factor that impacts on livestock production and economic returns over time. The framework establishes the links between inputs, the state of the pasture resource and outputs, to identify optimal pasture development strategies. The analysis is based on the application of a dynamic pasture resource development simulation model within a seasonal stochastic dynamic programming framework. This enables the derivation of optimum decisions within complex grazing enterprises, over both short-term tactical (such as grazing rest) and long-term strategic (such as pasture renovation) time frames and under climatic uncertainty. The simulation model is parameterised using data and systems from the Cicerone Project farmlet experiment. Results indicate that the strategic decision of pasture renovation should only be considered when pastures are in a severely degraded state, whereas the tactical use of grazing rest or low stocking rates should be considered as the most profitable means of maintaining adequate proportions of desirable species within a pasture sward. The optimal stocking rates identified reflected a pattern which may best be described as a seasonal saving and consumption cycle. The optimal tactical and strategic decisions at different pasture states, based on biomass and species composition, varies both between seasons and in response to the imposed soil fertility regime. Implications of these findings at the whole-farm level are discussed in the context of the Cicerone Project farmlets.


2014 ◽  
Vol 281 (1796) ◽  
pp. 20141733 ◽  
Author(s):  
Alexandra Alvergne ◽  
Virpi Lummaa

The negative wealth–fertility relationship brought about by market integration remains a puzzle to classic evolutionary models. Evolutionary ecologists have argued that this phenomenon results from both stronger trade-offs between reproductive and socioeconomic success in the highest social classes and the comparison of groups rather than individuals. Indeed, studies in contemporary low fertility settings have typically used aggregated samples that may mask positive wealth–fertility relationships. Furthermore, while much evidence attests to trade-offs between reproductive and socioeconomic success, few studies have explicitly tested the idea that such constraints are intensified by market integration. Using data from Mongolia, a post-socialist nation that underwent mass privatization, we examine wealth–fertility relationships over time and across a rural–urban gradient. Among post-reproductive women, reproductive fitness is the lowest in urban areas, but increases with wealth in all regions. After liberalization, a demographic–economic paradox emerges in urban areas: while educational attainment negatively impacts female fertility in all regions, education uniquely provides socioeconomic benefits in urban contexts. As market integration progresses, socio-economic returns to education increase and women who limit their reproduction to pursue education get wealthier. The results support the view that selection favoured mechanisms that respond to opportunities for status enhancement rather than fertility maximization.


Author(s):  
Joshua Simmons ◽  
Kristen Splinter

Physics-based numerical models play an important role in the estimation of storm erosion, particularly at beaches for which there is little historical data. However, the increasing availability of pre-and post-storm data for multiple events and at a number of beaches around the world has opened the possibility of using data-driven approaches for erosion prediction. Both physics-based and purely data-driven approaches have inherent strengths and weaknesses in their ability to predict storm-induced erosion. It is vital that coastal managers and modelers are aware of these trade-offs as well as methods to maximise the value from each modelling approach in an increasingly data-rich environment. In this study, data from approximately 40 years of coastal monitoring at Narrabeen-Collaroy Beach (SE Australia)has been used to evaluate the individual performance of the numerical erosion models SBEACH and XBeach, and a data-driven modelling technique. The models are then combined using a simple weighting technique to provide a hybrid estimate of erosion.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/v53dZiO8Y60


2018 ◽  
Vol 2 ◽  
pp. e25343
Author(s):  
José Augusto Salim ◽  
Antonio Saraiva ◽  
Kayna Agostini ◽  
Marina Wolowski ◽  
Allan Veiga ◽  
...  

The Brazilian Plant-Pollinator Interactions Network*1 (REBIPP) aims to develop scientific and teaching activities in plant-pollinator interaction. The main goals of the network are to: generate a diagnosis of plant-pollinator interactions in Brazil; integrate knowledge in pollination of natural, agricultural, urban and restored areas; identify knowledge gaps; support public policy guidelines aimed at the conservation of biodiversity and ecosystem services for pollination and food production; and encourage collaborative studies among REBIPP participants. To achieve these goals the group has resumed and built on previous works in data standard definition done under the auspices of the IABIN-PTN (Etienne Américo et al. 2007) and FAO (Saraiva et al. 2010) projects (Saraiva et al. 2017). The ultimate goal is to standardize the ways data on plant-pollinator interactions are digitized, to facilitate data sharing and aggregation. A database will be built with standardized data from Brazilian researchers members of the network to be used by the national community, and to allow sharing data with data aggregators. To achieve those goals three task groups of specialists with similar interests and background (e.g botanists, zoologists, pollination biologists) have been created. Each group is working on the definition of the terms to describe plants, pollinators and their interactions. The glossary created explains their meaning, trying to map the suggested terms into Darwin Core (DwC) terms, and following the TDWG Standards Documentation Standard*2 in definition. Reaching a consensus on terms and their meaning among members of each group is challenging, since researchers have different views and concerns about which data are important to be included into a standard. That reflects the variety of research questions that underlie different projects and the data they collect. Thus, we ended up having a long list of terms, many of them useful only in very specialized research protocols and experiments, sometimes rarely collected or measured. Nevertheless we opted to maintain a very comprehensive set of terms, so that a large number of researchers feel that the standard meets their needs and that the databases based on it are a suitable place to store their data, thus encouraging the adoption of the data standard. An update of the work will soon be available at REBIPP website and will be open for comments and contributions. This proposal of a data standard is also being discussed within the TDWG Biological Interaction Data Interest Group*3 in order to propose an international standard for species interaction data. The importance of interaction data for guiding conservation practices and ecosystem services provision management has led to the proposal of defining Essential Biodiversity Variables (EBVs) related to biological interactions. Essential Biodiversity Variables (Pereira et al. 2013) were developed to identify key measurements that are required to monitoring biodiversity change. EBVs act as intermediate abstract layer between primary observations (raw data) and indicators (Niemeijer 2002). Five EBV classes have been defined in an initial stage: genetic composition, species populations, species traits, community composition, ecosystem function and ecosystem structure. Each EBV class defines a list of candidate EBVs for biodiversity change monitoring (Fig. 1). Consequently, digitalization of such data and making them available online are essential. Differences in sampling protocols may affect data scalability across space and time, hence imposing barriers to the full use of primary data and EBVs calculation (Henry et al. 2008). Thus, common protocols and methods should be adopted as the most straightforward approach to promote integration of collected data and to allow calculation of EBVs (Jürgens et al. 2011). Recently a Workshop was held by GLOBIS B*4 (GLOBal Infrastructures for Supporting Biodiversity research) to discuss Species Interactions EBVs (February, 26-28, Bari, Italy). Plant-pollinator interactions deserved a lot of attention and REBIPP's work was presented there. As an outcome we expect to define specific EBVs for interactions, and use plant-pollinators as an example, considering pairwise interactions as well as interaction network related variables. The terms in the plant-pollinator data standard under discussion at REBIPP will provide information not only on EBV related with interactions, but also on other four EBV classes: species populations, species traits, community composition, ecosystem function and ecosystem structure. As we said, some EBVs for specific ecosystem functions (e.g. pollination) lay beyond interactions network structures. The EBV 'Species interactions' (EBV class 'Community composition') should incorporate other aspects such as frequency (Vázquez et al. 2005), duration and empirical estimates of interaction strengths (Berlow et al. 2004). Overall, we think the proposed plant-pollinator interaction data standard which is currently being developed by REBIPP will contribute to data aggregation, filling many data gaps and can also provide indicators for long-term monitoring, being an essential source of data for EBVs.


2019 ◽  
pp. 266-284
Author(s):  
Gary G. Mittelbach ◽  
Brian J. McGill

Just as the dispersal of individuals may link the dynamics of populations in space, the dispersal of species among communities may link local communities into a metacommunity. Four different perspectives characterize how dispersal rates, environmental heterogeneity, and species traits interact to influence diversity in metacommunities. These perspectives are: patch dynamics, species sorting, mass effects, and the neutral perspective. The neutral perspective stands in stark contrast to the other three perspectives in that it assumes that niche differences between species are unimportant and that species are demographically identical in terms of their birth, death, and dispersal rates. Under the neutral perspective, species diversity is maintained by a balance between speciation, extinction, and dispersal. Although neutral theory is incompatible with realistic modes and rates of speciation, it has been enormously influential in focusing our attention on the linkages between species interactions on local scales, and evolutionary and biogeographic processes occurring on large scales.


2020 ◽  
Vol 117 (8) ◽  
pp. 4243-4251 ◽  
Author(s):  
Emily S. Bellis ◽  
Elizabeth A. Kelly ◽  
Claire M. Lorts ◽  
Huirong Gao ◽  
Victoria L. DeLeo ◽  
...  

Host–parasite coevolution can maintain high levels of genetic diversity in traits involved in species interactions. In many systems, host traits exploited by parasites are constrained by use in other functions, leading to complex selective pressures across space and time. Here, we study genome-wide variation in the staple crop Sorghum bicolor (L.) Moench and its association with the parasitic weed Striga hermonthica (Delile) Benth., a major constraint to food security in Africa. We hypothesize that geographic selection mosaics across gradients of parasite occurrence maintain genetic diversity in sorghum landrace resistance. Suggesting a role in local adaptation to parasite pressure, multiple independent loss-of-function alleles at sorghum LOW GERMINATION STIMULANT 1 (LGS1) are broadly distributed among African landraces and geographically associated with S. hermonthica occurrence. However, low frequency of these alleles within S. hermonthica-prone regions and their absence elsewhere implicate potential trade-offs restricting their fixation. LGS1 is thought to cause resistance by changing stereochemistry of strigolactones, hormones that control plant architecture and below-ground signaling to mycorrhizae and are required to stimulate parasite germination. Consistent with trade-offs, we find signatures of balancing selection surrounding LGS1 and other candidates from analysis of genome-wide associations with parasite distribution. Experiments with CRISPR–Cas9-edited sorghum further indicate that the benefit of LGS1-mediated resistance strongly depends on parasite genotype and abiotic environment and comes at the cost of reduced photosystem gene expression. Our study demonstrates long-term maintenance of diversity in host resistance genes across smallholder agroecosystems, providing a valuable comparison to both industrial farming systems and natural communities.


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