Modelling water yields in response to logging and Representative Climate Futures

Abstract

Natural and human disturbance and climate change pose major challenges for resource management. This is relevant in natural forests where conflict can occur between water provision and industrial logging where conversion of old forests to young, fast-growing stands can dramatically reduce streamflow and water yield. We modelled changes in stream run-off and hence water yield from a forest catchment in response to clearcut logging with projected climate change (using a Representative Climate Futures [RCFs] approach). We focused on the Thomson Catchment which is the largest single catchment for the city of Melbourne, south-eastern Australia. Within this catchment, we targeted our analysis at montane ash-type eucalypt forests, as these receive the most rainfall and are subject to clearcutting. We used several forest management scenarios to model changes in water yield over time. For our analysis of projected climate change, we employed a range of RCFs that represent 'consensus', 'wettest' and 'driest' scenarios to model the impacts of multiple Representative Concentration Pathways (RCPs). Our initial spatial analysis revealed that 42% of the ash-type eucalypt forests in the Thomson Catchment have been logged. Under historical and continued logging, stream runoff decreases by 40,211 ML by 2090 compared with a hypothetical baseline if logging had ceased in 1995 and 34,059 ML if logging continues beyond 2019. These losses exceed the projected impacts of climate change under the consensus and wettest scenarios, but the driest scenarios are projected to exceed these losses, consisting of 49,998 ML and 69,474 ML for RCP 4.5 and RCP 8.5, respectively.We suggest native forest logging be excluded from the Thomson Catchment because of decreasing stream flows due to climate change and an increasing water demand due to human population growth. This study provides a quantitative approach for highlighting how resource conflicts can be magnified under climate change.

Key perspectives on early successional forests subject to stand-replacing disturbances

“…There can be other spatial effects associated with extensive areas of early successional forest. These include significantly reduced water yields and levels of carbon storage from watersheds dominated by large areas of early successional forest (Vertessy et al, 2001;Keith et al, 2017;Taylor et al, 2019). Other effects of early successional forest occurring across a high proportion of total forest cover include declines in species associated with older or intact forest (Gibson et al, 2011, reviewed by Watson et al, 2018.…”

Direct and indirect disturbance impacts in forests

“…Forests are among the world's most productive, diverse and functionally critical ecosystems. They constitute large, highquality water-catchments (Taylor et al 2019), store vast amounts of carbon crucial for climate change mitigation (Paustian et al 2016) and support a substantial proportion of the earth's biodiversity (Watson et al 2018). Natural wildfire regimes, characterised by distinct patterns of intensity, severity and frequency, are key ecological processes in forests and influence biodiversity (Bond et al 2005;Bowman et al 2009).…”

“…They constitute large, high‐quality water‐catchments (Taylor et al . 2019), store vast amounts of carbon crucial for climate change mitigation (Paustian et al . 2016) and support a substantial proportion of the earth's biodiversity (Watson et al .…”

Assessment of Future Water Yield and Water Purification Services in Data Scarce Region of Northwest China

“…The assessment of water ecosystem services is a key issue in the field of hydrology and watershed management [11]. Several methods are currently available to assess water ecosystem services [12]. Although many studies on water ecosystem services were conducted in northwest China, including water yield and water purification services [13][14][15][16][17][18], they have paid less attention to research on the condition of these services in the future and areas with limited data.…”