Modeling the Cumulative Watershed Effects of Forest Management Strategies

摘要: There is increasing concern over the possibility of adverse cumulative watershed effects from intensive forest management. It impractical to address many aspects problem experimentally because do so would require studying large watersheds for 100 yr or more. One such aspect long-term effect management strategies on erosion and sedimentation resultant damage fish habitat. Is dispersing activities in time space an effective way minimize effects? To this problem, Monte Carlo simulations were conducted four hypothetical 10 000-ha fifth-order forested watersheds: one was left undisturbed, completely clearcut roaded yr, with cutting starting at head progressing toward mouth, another cut rate 1% each year beginning watershed’s mouth upstream, a year, individual areas being widely dispersed throughout watershed. These patterns repeated succeeding centuries, rebuilding one-third road network every yr. The parameters governing based recent data coastal Oregon northwestern California, Mass wasting, most important source sediment that environment, only hillslope process modeled. simulation results suggest (i) greatest differences between appeared first related primarily treatment. By second when all had been treated, principal difference logging timing impacts. (ii) Dispersing harvest units did not significantly reduce effects. (iii) frequency bed elevation changes 1 4 cm dramatically increased by logging. uncertainty model. properties are essential characterization meteorological inputs can be used account hydrologic geomorphic parameters. Paired-watershed experiments frequently investigate land use processes. Normally paired-watershed assumed more real than those obtained computer simulations. That assumption should scrutinized little carefully. record natural interplay relevant They so, however, location during relatively short period time. Therefore, statistical inferences studies apply study conditions operating periods. All else extrapolation professional judgement, inference.