Structural holes, innovation and the distribution of ideas

We model knowledge diffusion in a population of agents situated on a network, interacting only over direct ties. Some agents are by nature traders, others are by nature "givers": traders demand a quid pro quo for information transfer; givers do not. We are interested in efficiency of diffusion and explore the interplay between the structure of the population (proportion of traders), the network structure (clustering, path length and degree distribution), and the scarcity of knowledge. We find that at the global level, trading (as opposed to giving) reduces efficiency. At the individual level, highly connected agents do well when knowledge is scarce, agents in clustered neighbourhoods do well when it is abundant. The latter finding is connected to the debate on structural holes and social capital

Networks as emergent structures from bilateral collaboration

In this paper we model the formation of innovation networks as they emerge from bilateral actions. The e.ectiveness of a bilateral collaboration is determined by cognitive, relational and structural embeddedness. Innovation results from the recombination of knowledge held by the partners to the collaboration, and the extent to which agents ’ knowledge complement each others is an issue of cognitive embeddedness. Previous collaborations (relational embeddedness) increase the probability of a successful collaboration; as does information gained from common third parties (structural embeddedness). As a result of repeated alliance formation, a network emerges whose properties are studied, together with those of the process of knowledge creation. Two features are central to the innovation process: how agents pool their knowledge resources; and how agents derive information about potential partners. We focus on the interplay between these two dimensions, and find that they both matter. The networks that emerge are not random, but in certain parts of the parameter space have properties of small worlds

HETEROFOR 1.0: A spatially explicit model for exploring the response of structurally complex forests to uncertain future conditions-Part 2: Phenology and water cycle

Climate change affects forest growth in numerous and sometimes opposite ways, and the resulting trend is often difficult to predict for a given site. Integrating and structuring the knowledge gained from the monitoring and experimental studies into process-based models is an interesting approach to predict the response of forest ecosystems to climate change. While the first generation of models operates at stand level, one now needs spatially explicit individual-based approaches in order to account for individual variability, local environment modification and tree adaptive behaviour in mixed and uneven-Aged forests that are supposed to be more resilient under stressful conditions. The local environment of a tree is strongly influenced by the neighbouring trees, which modify the resource level through positive and negative interactions with the target tree. Among other things, drought stress and vegetation period length vary with tree size and crown position within the canopy. In this paper, we describe the phenology and water balance modules integrated in the tree growth model HETEROFOR (HETEROgenous FORest) and evaluate them on six heterogeneous sessile oak and European beech stands with different levels of mixing and development stages and installed on various soil types. More precisely, we assess the ability of the model to reproduce key phenological processes (budburst, leaf development, yellowing and fall) as well as water fluxes. Two two-phase models differing regarding their response function to temperature during the chilling period (optimum and sigmoid functions) and a simplified one-phase model are. used to predict budburst date. The two-phase model with the optimum function is the least biased (overestimation of 2.46 d), while the one-phase model best accounts for the interannual variability (Pearson's r D 0:68). For the leaf development, yellowing and fall, predictions and observations are in accordance. Regarding the water balance module, the predicted throughfall is also in close agreement with the measurements (Pearson's r D 0:856; biasD 1:3 %), and the soil water dynamics across the year are well reproduced for all the study sites (Pearson's r was between 0.893 and 0.950, and bias was between 1:81 and 9:33 %). The model also reproduced well the individual transpiration for sessile oak and European beech, with similar performances at the tree and stand scale (Pearson's r of 0.84 0.85 for sessile oak and 0.88 0.89 for European beech). The good results of the model assessment will allow us to use it reliably in projection studies to evaluate the impact of climate change on tree growth in structurally complex stands and test various management strategies to improve forest resilience. © 2020 Author(s)

RETRIEVAL OF FOREST WATER POTENTIAL FROM L-BAND VEGETATION OPTICAL DEPTH

peer reviewedA retrieval methodology for forest water potential from ground-based L-band radiometry is proposed. It contains the estimation of the gravimetric and the relative water content of a forest stand and tests in situ- and model-based functions to transform these estimates into forest water potential. The retrieval is based on vegetation optical depth data from a tower-based experiment of the SMAPVEX 19-21 campaign for the period from April to October 2019 at Harvard Forest, MA, USA. In addition, comparison and validation with in situ measurements on leaf and xylem water potential as well as on leaf wetness and complex permittivity are foreseen to understand limitations and potentials of the proposed approach. As a first result the radiometer-based water potential estimates of the forest stand are concurrent in time and similar in value with their in situ (xylem) counterparts from single trees in the radiometer footprint

Peer influence in network markets: a theoretical and empirical analysis

Network externalities spur the growth of networks and the adoption of network goods in two ways. First, they make it more attractive to join a network the larger its installed base. Second, they create incentives for network members to actively recruit new members. Despite indications that the latter "peer effect" can be more important for network growth than the installed-base effect, it has so far been largely ignored in the literature. We address this gap using game-theoretical models. When all early adopters can band together to exert peer influence-an assumption that fits, e.g., the case of firms supporting a technical standard-we find that the peer effect induces additional growth of the network by a factor. When, in contrast, individuals exert peer influence in small groups of size n, the increase in network size is by an additive constant-which, for small networks, can amount to a large relative increase. The difference between small, local, personal networks and large, global, anonymous networks arises endogenously from our analysis. Fundamentally, the first type of networks is "tie-reinforcing," the other, "tie-creating". We use survey data from users of the Internet services, Skype and eBay, to illustrate the main logic of our theoretical results. As predicted by the model, we find that the peer effect matters strongly for the network of Skype users-which effectively consists of numerous small sub-networks-but not for that of eBay users. Since many network goods give rise to small, local networks

Does polycystic ovarian morphology influence the response to treatment with pulsatile GnRH in functional hypothalamic amenorrhea?

BACKGROUND: Pulsatile GnRH therapy is the gold standard treatment for ovulation induction in women having functional hypothalamic amenorrhea (FHA). The use of pulsatile GnRH therapy in FHA patients with polycystic ovarian morphology (PCOM), called “FHA-PCOM”, has been little studied in the literature and results remain contradictory. The aim of this study was to compare the outcomes of pulsatile GnRH therapy for ovulation induction between FHA and “FHA-PCOM” patients in order to search for an eventual impact of PCOM. METHODS: Retrospective study from August 2002 to June 2015, including 27 patients with FHA and 40 “FHA-PCOM” patients (85 and 104 initiated cycles, respectively) treated by pulsatile GnRH therapy for induction ovulation. RESULTS: The two groups were similar except for markers of PCOM (follicle number per ovary, serum Anti-Müllerian Hormone level and ovarian area), which were significantly higher in patients with “FHA-PCOM”. There was no significant difference between the groups concerning the ovarian response: with equivalent doses of GnRH, both groups had similar ovulation (80.8 vs 77.7 %, NS) and excessive response rates (12.5 vs 10.6 %, NS). There was no significant difference in on-going pregnancy rates (26.9 vs 20 % per initiated cycle, NS), as well as in miscarriage, multiple pregnancy or biochemical pregnancy rates. CONCLUSION: Pulsatile GnRH seems to be a successful and safe method for ovulation induction in “FHA-PCOM” patients. If results were confirmed by prospective studies, GnRH therapy could therefore become a first-line treatment for this specific population, just as it is for women with FHA without PCOM