Oyster recruitment dataset

Dear data users,
This repository contains 3 sets of files corresponding to the data analysis (R Script) and dataset (xlsx or csv files) for 3 sections of this paper.

Attached are the following pairs of R script and dataset for the section of:

----> R script: R_official_oysterrecruitment_percentage.R
---->dataset: merged_data_oct2021_forEA.csv
The variable names and description of each variable contained in this data are as follows. *Please refer to the PhD thesis or Leong et al 2022 Restoration Ecology and thesis for specific description and methods of calculation for each variable.
estuary * - categorical variables of estuary -either Port Hacking, Crookhaven River or Hunter River
tile_id - unique replicate of each tile where the response variable (oyster counts and percentages) where collected from
reef_id - unique replicate of each tile where the response variable (oyster counts and percentages) where collected from
area* - reef area
dist.to.edge * - distance of each tile to the nearest patch edge in meters
elevation* - surface elevation of the base of each tile relative to mean sea level
prox.index* - proximity index of each reef in relation to other reefs on a landscape scale
iso.index* - proximity index of each reef in relation to other reefs on a landscape scale
circle* - circularity of each reef
frac* - two-dimensional fractional dimensionality of each reef
liveoys_oct2020 - live counts of oysters on each tile at the end of the experiment
deadoys_oct2020 - dead counts of oysters on each tile at the end of the experiment
totoys_oct2020 - total (live + dead) counts of oysters on each tile at the end of the experiment
percent_live_oct2020 – live / (live + dead) *100% oysters on each tile at the end of the experiment

----> R script: R_official_abiotic_biotic_comparison.R
---->dataset: comparing abiotic and biotic_factors_noattributes_6jan2022.xlsx (31.82 KB)

estuary * - categorical variables of estuary -either Port Hacking, Crookhaven River or Hunter River
tile_id - unique replicate of each tile where the response variable (oyster counts and percentages) where collected from
reef_id - unique replicate of each tile where the response variable (oyster counts and percentages) where collected from
liveoys_aug2020 - live counts of oysters on each tile when the abiotic variables where measured
totoys_aug2020 percent_live_aug2020 - live counts of oysters on each tile when the abiotic variables where measured
deadoys_aug2020 – dead counts of oysters on each tile when the abiotic variables where measured
cover_area – total cover area (in mm2) oysters on each tile when the abiotic variables where measured
sed.rate – sedimentation rate (grams/ day) of sediment traps deployed next to tile replicates.
cov.temp_logger – Covariation of temperature (no unit) based upon on temperature measured by temperature logger attached to selected tile replicates for a specific deployment period
q5_logger – 5th quartile of daily temperature in Celsius measured by temperature logger attached to selected tile replicates for a specific deployment period
q95_logger – 95th quartile of daily temperature in Celsius measured by temperature logger attached to selected tile replicates for a specific deployment period

----> R script: regional recruitment_R script.R
--->dataset: regional recruitment_for R.csv
The variable names and description of each variable contained in this dataset are as the following. For detailed information on how variables collected in this dataset, please refer to PhD thesis and Leong et al 2023/2024 Ecological Applications publication and thesis.
estuary - categorical variables of estuary -either Port Hacking, Crookhaven River, Hunter River, Shell Point (Georges River), Bermagui and Hawkesbury River
est_type - categorical variables of estuary type as either “non-sed” (not-sedimented heavy estuary) or “sed” (sedimented heavy estuary)
tile_id - unique replicate of each tile where the response variable (oyster counts and percentages) where collected from
elevation - surface elevation of the base of each tile relative to mean sea level
totrec_all - counts of total oyster recruits on the all surfaces per tile (not used for the analysis in thesis and Leong et al 2023 Ecological Applications)
totrec_top - counts total oyster recruits on the top surface per tile (not used for the analysis in thesis and Leong et al 2023 Ecological Applications)
totrec_deadonlytop – counts of dead oyster recruits on the top surface per tile (not used for the analysis in thesis and Leong et al 2023 Ecological Applications)
totrec_liveonly - live counts of dead oyster recruits on the top surface per tile (not used for the analysis in thesis and Leong et al 2023 Ecological Applications)
totrec_per – percentage live counts (live/total *100%) of oyster recruits on all surface of each tile
sediment_shell – dry weight of sediment collected in sediment trap next to each tile

For any queries regarding the contents of the file above, please email first co-author, Dr. Rick Leong at [e-mail]

For dataset pertaining to , please email corresponding author and/or co-author Dr. Mitchell Gibbs for permission and data analysis files.

致数据使用者：
本仓库包含3组文件，分别对应本文3个章节的数据分析代码（R脚本（R Script））与数据集（xlsx（Excel电子表格格式）或csv（逗号分隔值文件））。
以下为对应章节的R脚本与数据集配对文件：

----> R脚本：R_official_oysterrecruitment_percentage.R
----> 数据集：merged_data_oct2021_forEA.csv
本数据集包含的变量名称与各变量说明如下。各变量的具体说明与计算方法，请参见博士学位论文或Leong等人2022年发表于《Restoration Ecology》的论文及学位论文。
estuary*：河口（estuary）分类变量，可选值为Port Hacking、Crookhaven River或Hunter River
tile_id：用于采集响应变量（牡蛎计数与占比）的每个样块（tile）的唯一标识
reef_id：用于采集响应变量（牡蛎计数与占比）的每个样块的唯一礁体（reef）标识
area*：礁体面积
dist.to.edge*：每个样块至最近斑块边缘的距离（单位：米）
elevation*：每个样块基底相对于平均海平面的表面高程
prox.index*：景观尺度下各礁体与其他礁体的邻近度指数
iso.index*：景观尺度下各礁体与其他礁体的邻近度指数
circle*：每个礁体的圆度
frac*：每个礁体的二维分形维数（fractal dimensionality）
liveoys_oct2020：实验结束时每个样块上的活牡蛎计数
deadoys_oct2020：实验结束时每个样块上的死牡蛎计数
totoys_oct2020：实验结束时每个样块上的牡蛎总计数（活+死）
percent_live_oct2020：实验结束时每个样块上的活牡蛎占比（活/(活+死)×100%）

----> R脚本：R_official_abiotic_biotic_comparison.R
----> 数据集：comparing abiotic and biotic_factors_noattributes_6jan2022.xlsx（31.82 KB）

estuary*：河口（estuary）分类变量，可选值为Port Hacking、Crookhaven River或Hunter River
tile_id：用于采集响应变量（牡蛎计数与占比）的每个样块的唯一标识
reef_id：用于采集响应变量（牡蛎计数与占比）的每个样块的唯一礁体标识
liveoys_aug2020：测定非生物变量（abiotic variable）时每个样块上的活牡蛎计数
totoys_aug2020：测定非生物变量时每个样块上的牡蛎总计数
percent_live_aug2020：测定非生物变量时每个样块上的活牡蛎占比
deadoys_aug2020：测定非生物变量时每个样块上的死牡蛎计数
cover_area：测定非生物变量时每个样块上的牡蛎总覆盖面积（单位：mm²）
sed.rate：紧邻样块重复样方的沉积物捕集器（sediment trap）的沉积速率（单位：克/天）
cov.temp_logger：基于特定部署周期内附着于选定样块重复样方的温度记录仪（temperature logger）所测得的温度计算得到的温度协变值（无单位）
q5_logger：特定部署周期内附着于选定样块重复样方的温度记录仪所测得的日温度的5分位数（单位：摄氏度）
q95_logger：特定部署周期内附着于选定样块重复样方的温度记录仪所测得的日温度的95分位数（单位：摄氏度）

----> R脚本：regional recruitment_R script.R
----> 数据集：regional recruitment_for R.csv
本数据集包含的变量名称与各变量说明如下。有关本数据集变量采集的详细信息，请参见博士学位论文以及Leong等人2023/2024年发表于《Ecological Applications》的论文及学位论文。
estuary：河口（estuary）分类变量，可选值为Port Hacking、Crookhaven River、Hunter River、Shell Point（Georges River）、Bermagui及Hawkesbury River
est_type：河口类型分类变量，可选值为"non-sed"（非重度沉积河口）或"sed"（重度沉积河口）
tile_id：用于采集响应变量（牡蛎计数与占比）的每个样块的唯一标识
elevation：每个样块基底相对于平均海平面的表面高程
totrec_all：每个样块所有表面上的牡蛎幼体总计数（本研究学位论文及Leong等人2023年发表于《Ecological Applications》的论文未将其用于分析）
totrec_top：每个样块顶面的牡蛎幼体总计数（本研究学位论文及Leong等人2023年发表于《Ecological Applications》的论文未将其用于分析）
totrec_deadonlytop：每个样块顶面的死牡蛎幼体计数（本研究学位论文及Leong等人2023年发表于《Ecological Applications》的论文未将其用于分析）
totrec_liveonly：每个样块顶面的活牡蛎幼体计数（本研究学位论文及Leong等人2023年发表于《Ecological Applications》的论文未将其用于分析）
totrec_per：每个样块所有表面上的牡蛎幼体活个体占比（活个体/总个体×100%）
sediment_shell：每个样块旁沉积物捕集器中收集的沉积物干重

若对上述文件内容有任何疑问，请联系第一作者Rick Leong博士，邮箱：[e-mail]。
若需获取相关数据集，请联系通讯作者及/或共同作者Mitchell Gibbs博士以获取使用许可与数据分析文件。