Analyzing temporal and spatial forest carbon storage using Google Plus Code: a case study of Zijin Mountain National Forest Park, China.

BACKGROUND: It is always a challenging job to compare forest resources as there is not a standardized spatial unit with location information. Google Plus Code, the newest alphanumeric geocoding system, uses 20 specifically selected letters and numbers to assign a unique global ID to every cell at different levels of a hierarchical grid system which is established based on latitude and longitude. It can be used as a standardized, unique global geospatial unit to segment, locate, quantitate, evaluate, and compare natural resources with area, boundary, and location information embedded. RESULTS: For this proof-of-concept case study, forest inventory data from 1987, 2002, and 2019 for the Zijin Mountain National Forest Park in Jiangsu Province, China was analyzed based on Google Plus Code grid/cell. This enabled the quantification of carbon storage at each cell allowing for the comparison of estimated carbon storage at same or different locations over time. CONCLUSIONS: This methodology is used to quantify the impacts of changing forest conditions and forest management activities on carbon storage with high spatial accuracy through the 32-year study period. Furthermore, this technique could be used for providing technical support and validation of carbon credit quantification and management.

Water quality effects of clearcut harvesting and forest fertilization with best management practices.

Nine small (2.5 ha) and four large (70-135 ha) watersheds were instrumented in 1999 to evaluate the effects of silvicultural practices with application of best management practices (BMPs) on stream water quality in East Texas, USA. Two management regimes were implemented in 2002: (i) conventional, with clearcutting, herbicide site preparation, and BMPs and (ii) intensive, which added subsoiling, aerial broadcast fertilization, and an additional herbicide application. Watershed effects were compared with results from a study on the same small watersheds in 1981, in which two combinations of harvesting and mechanical site preparation without BMPs or fertilization were evaluated. Clearcutting with conventional site preparation resulted in increased nitrogen losses on the small watersheds by about 1 additional kg ha(-1) each of total Kjeldahl nitrogen (TKN) and nitrate-nitrogen (NO(3)-N) in 2003. First-year losses were not significantly increased on the large watershed with a conventional site preparation with BMPs. Fertilization resulted in increased runoff losses in 2003 on the intensive small watersheds by an additional 0.77, 2.33, and 0.36 kg ha(-1) for NO(3)-N, TKN, and total phosphorus, respectively. Total loss rates of ammonia nitrogen (NH(4)-N) and NO(3)-N were low overall and accounted for only approximately 7% of the applied N. Mean loss rates from treated watersheds were much lower than rainfall inputs of about 5 kg ha(-1) TKN and NO(3)-N in 2003. Aerial fertilization of the 5-yr-old stand on another large watershed did not increase nutrient losses. Intensive silvicultural practices with BMPs did not significantly impair surface water quality with N and P.

Roofing as a source of nonpoint water pollution.

Sixteen wooden structures with two roofs each were installed to study runoff quality for four commonly used roofing materials (wood shingle, composition shingle, painted aluminum, and galvanized iron) at Nacogdoches, Texas. Each roof, either facing NW or SE, was 1.22 m wide x 3.66 m long with a 25.8% roof slope. Thus, there were 32 alternatively arranged roofs, consisting of four roof types x two aspects x four replicates, in the study. Runoff from the roofs was collected through galvanized gutters, downspouts, and splitters. The roof runoff was compared to rainwater collected by a wet/dry acid rain collector for the concentrations of eight water quality variables, i.e. Cu(2+), Mn(2+), Pb(2+), Zn(2+), Mg(2+), Al(3+), EC and pH. Based on 31 storms collected between October 1997 and December 1998, the results showed: (1) concentrations of pH, Cu, and Zn in rainwater already exceed the EPA freshwater quality standards even without pollutant inputs from roofs, (2) Zn and Cu, the two most serious pollutants in roof runoff, exceeded the EPA national freshwater water quality standards in virtually 100% and more than 60% of the samples, respectively, (3) pH, EC, and Zn were the only three variables significantly affected by roofing materials, (4) differences in Zn concentrations were significant among all roof types and between all roof runoff and rainwater samples, (5) although there were no differences in Cu concentrations among all roof types and between roof runoff and rainwater, all means and medians of runoff and rainwater exceeded the national water quality standards, (6) water quality from wood shingles was the worst among the roof types studied, and (7) although SE is the most frequent and NW the least frequent direction for incoming storms, only EC, Mg, Mn, and Zn in wood shingle runoff from the SE were significantly higher than those from the NW; the two aspects affected no other elements in runoff from the other three roof types. Also, Zn concentrations from new wood-shingle roofs were significantly higher than those from aged roofs of a previous study. The study demonstrated that roofs could be a serious source of nonpoint water pollution. Since Zn is the most serious water pollutant and wood shingle is the worst of the four roof types, using less compounds and materials associated with Zn along with good care and maintenance of roofs are critical in reducing Zn pollution in roof runoff.