Snowpack, Tree Size, and Ecological Legacies Promote Seedling Establishment in Tree Islands at the Treeline

Ecosystems ◽  
2020 ◽  
Vol 23 (8) ◽  
pp. 1714-1725
Author(s):  
O. T. Fitzpatrick ◽  
M. Blade ◽  
L. A. Fishback ◽  
G. P. Kershaw ◽  
J. Muffly ◽  
...  

HortScience ◽  
1998 ◽  
Vol 33 (3) ◽  
pp. 553d-553
Author(s):  
C.R. Unrath

Historically, most airblast chemical applications to apple orchards used a single “average” water volume, resulting in variability of coverage with tree size and also the greatest variable in chemical thinning. This coverage variability can be eliminated by properly quantifying the tree canopy, as tree row volume (TRV), and relating that volume to airblast water rate for adequate coverge. Maximum typical tree height, cross-row limb spread, and between-row spacing are used to quantify the TRV. Further refinement is achieved by adjusting the water volume for tree canopy density. The North Carolina TRV model allows a density adjustment from 0.7 gal/1000 ft3 of TRV for young, very open tree canopies to 1.0 gal/1000 ft3 of TRV for large, thick tree canopies to deliver a full dilute application for maximum water application (to the point of run-off). Most dilute pesticide applications use 70% of full dilute to approach the point of drip (pesticide dilute) to not waste chemicals and reduce non-target environmental exposure. From the “chemical load” (i.e., lb/acre) calculated for the pesticide dilute application, the proper chemical load for lower (concentrate) water volumes can be accurately determined. Another significant source of variability is thinner application response is spray distribution to various areas of the tree. This variability is related to tree configuration, light, levels, fruit set, and natural thinning vs. the need for chemical thinning. Required water delivery patterns are a function of tree size, form, spacing, and density, as well as sprayer design (no. of nozzles and fan size). The TRV model, density adjustments, and nozzle patterns to effectively hit the target for uniform crop load will be addressed.



2009 ◽  
Vol 25 (2) ◽  
pp. 107-121 ◽  
Author(s):  
Jan H. D. Wolf ◽  
S. Robbert Gradstein ◽  
Nalini M. Nadkarni

Abstract:The sampling of epiphytes is fraught with methodological difficulties. We present a protocol to sample and analyse vascular epiphyte richness and abundance in forests of different structure (SVERA). Epiphyte abundance is estimated as biomass by recording the number of plant components in a range of size cohorts. Epiphyte species biomass is estimated on 35 sample-trees, evenly distributed over six trunk diameter-size cohorts (10 trees with dbh > 30 cm). Tree height, dbh and number of forks (diameter > 5 cm) yield a dimensionless estimate of the size of the tree. Epiphyte dry weight and species richness between forests is compared with ANCOVA that controls for tree size. SChao1 is used as an estimate of the total number of species at the sites. The relative dependence of the distribution of the epiphyte communities on environmental and spatial variables may be assessed using multivariate analysis and Mantel test. In a case study, we compared epiphyte vegetation of six Mexican oak forests and one Colombian oak forest at similar elevation. We found a strongly significant positive correlation between tree size and epiphyte richness or biomass at all sites. In forests with a higher diversity of host trees, more trees must be sampled. Epiphyte biomass at the Colombian site was lower than in any of the Mexican sites; without correction for tree size no significant differences in terms of epiphyte biomass could be detected. The occurrence of spatial dependence, at both the landscape level and at the tree level, shows that the inclusion of spatial descriptors in SVERA is justified.



1998 ◽  
Vol 8 (2) ◽  
pp. 397-410 ◽  
Author(s):  
Karen A. Kainer ◽  
Mary L. Duryea ◽  
Nazaré Costa de Macêdo ◽  
Kimberlyn Williams


2021 ◽  
Vol 22 (15) ◽  
pp. 8172
Author(s):  
Orarat Ginsawaeng ◽  
Michal Gorka ◽  
Alexander Erban ◽  
Carolin Heise ◽  
Franziska Brueckner ◽  
...  

During seed germination, desiccation tolerance is lost in the radicle with progressing radicle protrusion and seedling establishment. This process is accompanied by comprehensive changes in the metabolome and proteome. Germination of Arabidopsis seeds was investigated over 72 h with special focus on the heat-stable proteome including late embryogenesis abundant (LEA) proteins together with changes in primary metabolites. Six metabolites in dry seeds known to be important for seed longevity decreased during germination and seedling establishment, while all other metabolites increased simultaneously with activation of growth and development. Thermo-stable proteins were associated with a multitude of biological processes. In the heat-stable proteome, a relatively similar proportion of fully ordered and fully intrinsically disordered proteins (IDP) was discovered. Highly disordered proteins were found to be associated with functional categories development, protein, RNA and stress. As expected, the majority of LEA proteins decreased during germination and seedling establishment. However, four germination-specific dehydrins were identified, not present in dry seeds. A network analysis of proteins, metabolites and amino acids generated during the course of germination revealed a highly connected LEA protein network.



2021 ◽  
pp. 1-36
Author(s):  
Carol A. Rolando ◽  
Brian Richardson ◽  
Thomas S.H. Paul ◽  
Chanatda Somchit

Abstract Exotic conifers are rapidly spreading in many regions of New Zealand, as well as in many other countries, with detrimental impacts on both natural ecosystems and some productive sector environments. Herbicides, in particular the active ingredient (a.i.) triclopyr, are an important tool to manage invasive conifers, yet there is a paucity of information that quantifies the amount of herbicide required to kill trees of different sizes when applied as a basal bark treatment. Two sequential experiments were conducted to define the amount of triclopyr required to kill individual invasive Pinus contorta trees of different sizes when applied in a methylated seed oil to bark (either the whole stem or base of the tree) and to determine which tree size variates (height (HT), diameter at breast height (DBH), crown diameter (CD)), or derived attributes (crown area, crown volume index) best characterised this dose-response relationship. The outcomes of the dose-response research were compared to field operations where triclopyr was applied to the bark of trees from an aerial platform. Applying the herbicide to the whole stem, as opposed to the base of the tree only, significantly increased treatment efficacy. The tree size variates DBH, CD, crown area and crown volume index all provided good fits to the tree mortality data, with >91% prediction accuracy. Of these variates, crown diameter provided the most practical measure of tree size for ease of in-field calculation of dose by an operator. Herbicide rates used in field operations were 7 to 8 times higher than lethal doses calculated from experimental data. Our results highlight the potential for substantial reductions in herbicide rates for exotic conifer control, especially if dose-response data are combined with remotely sensed quantitative measurements of canopy area or volume using new precision technologies such as unmanned aerial vehicles.



2021 ◽  
Vol 13 (1) ◽  
pp. 131
Author(s):  
Franziska Taubert ◽  
Rico Fischer ◽  
Nikolai Knapp ◽  
Andreas Huth

Remote sensing is an important tool to monitor forests to rapidly detect changes due to global change and other threats. Here, we present a novel methodology to infer the tree size distribution from light detection and ranging (lidar) measurements. Our approach is based on a theoretical leaf–tree matrix derived from allometric relations of trees. Using the leaf–tree matrix, we compute the tree size distribution that fit to the observed leaf area density profile via lidar. To validate our approach, we analyzed the stem diameter distribution of a tropical forest in Panama and compared lidar-derived data with data from forest inventories at different spatial scales (0.04 ha to 50 ha). Our estimates had a high accuracy at scales above 1 ha (1 ha: root mean square error (RMSE) 67.6 trees ha−1/normalized RMSE 18.8%/R² 0.76; 50 ha: 22.8 trees ha−1/6.2%/0.89). Estimates for smaller scales (1-ha to 0.04-ha) were reliably for forests with low height, dense canopy or low tree height heterogeneity. Estimates for the basal area were accurate at the 1-ha scale (RMSE 4.7 tree ha−1, bias 0.8 m² ha−1) but less accurate at smaller scales. Our methodology, further tested at additional sites, provides a useful approach to determine the tree size distribution of forests by integrating information on tree allometries.



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