A Lattice Genome framework links geometric and process “genes” to lattice “phenotypes” via correction‐calibrated high‐throughput simulations and a growing performance database. Genome‐driven retrieval and recombination of unit cells enables component‐level, regionally tailored multi‐objective design: stress fields are programmed under constant relative
Haoyuan Deng +8 more
wiley +1 more source
Effects of active forest management on host-seeking tick density and infection prevalence: a systematic review and meta-analysis. [PDF]
Hurd SN +4 more
europepmc +1 more source
Near-term investments in forest management support long-term carbon sequestration capacity in forests of the United States. [PDF]
Coulston JW +4 more
europepmc +1 more source
Adult Sex Ratio as a Demographic Feedback Linking Mating Systems, Parental Care, and Evolution
Breeding systems are some of the most diverse social behavior, and our team is investigation the evolutionary causes of this diversity. This review summarises our research carried out at the University of Bath. We argue that demographic components of wild populations, especially the adult sex ratio, plays a key role driving breeding system variation ...
Tamás Székely, Oscar G. Miranda
wiley +1 more source
Effects of Near-Natural Forest Management on Soil Microbial Communities in the Temperate-Subtropical Transition Zone of China. [PDF]
Zhang T, Dong X, Yang J, Li Z, Zhu J.
europepmc +1 more source
Devolution of forest management to local communities and its impacts on livelihoods and deforestation in Berau, Indonesia. [PDF]
Rochmayanto Y +7 more
europepmc +1 more source
1. Short background about Swedish forestry The forest covers 55 % of the total land area in Sweden. The forest area is 28 million ha according to FAO´s definition. According to the national definition (potential yield higher than 1 m3sk/ha and year) the area is 23 mill ha, of which 0.95 mill is formally protected from timber production, and another
openaire +1 more source
Forecasting Root Rot Disease through Predictive Microbial Functional Profiling
Predicting soil‐borne disease moves beyond observation with a framework that elevates microbial functional genes into reliable forecasting biomarkers. By coupling targeted qPCR assays for core stress‐response genes with machine learning, this method detects root rot risks in pre‐symptomatic soils with over 80% accuracy.
Chuan You +11 more
wiley +1 more source
Predicting habitat suitability of Dalbergia latifolia Roxb. (Indian rosewood) using MaxEnt: implications for conservation and sustainable forest management. [PDF]
Manohara TN +3 more
europepmc +1 more source

